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Topical Collection "Smart Grid"

Editor

Collection Editor
Prof. Dr. Neville R. Watson

Department of Electrical & Computer Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
Website | E-Mail
Fax: +64 3 364 2761
Interests: power quality; harmonics; electromagnetic transients; HVDC transmission; computer modelling of electrical power systems

Topical Collection Information

Dear Colleagues,

The need to deliver electricity to customers: reliably, safely and cost effectively and in a sustainable manner, is always with us. To do this given the multiplicity of constraints means the electrical power system must be carefully engineered, not only to meet today's needs, but for the foreseeable future. The Smart Grid initiative is really about making the grid smarter than it is already (as in many cases the grid is already "smart") so as to achieve these objectives. Many countries are devoting time and resources to this initiative due to the immense potential benefits. The perceived benefits are:

  • Improved reliability and resilience
  • Better operational efficiency
  • Better utilization of resources
  • Better utilization of assets
  • Adequate Power Quality

The term Smart Grid means different things to different people as the perceived benefits, and hence drivers, are different in different countries. Regardless of one's concept of a Smart Grid, the need for a reliable two-way communication system is central. Because of the entwining of both the electrical power system and communication system to form a Smart Grid the two streams to this collection are Smart Grid communications and Smart Grid electrical power system.

Papers in the relevant area of Smart Grid communications, including but not limited to the following, are invited:

  • Architectures and Models for Smart Grid
  • Smart Grid Sensors, Communications, Computing and Control
  • Cyber-Physical Wide-Area Monitoring, Protection & Control (Cyber-Physical WAMPAC)
  • Local-Area and Wide-Area networks for Smart Grids and Smart Metering
  • Demand Side Management, Demand Response, Dynamic Pricing
  • Communications support for Storage, Renewable Resources and Micro-Grids
  • Smart Grid Cyber Security and Privacy
  • Smart Grid Services and Management Models
  • Smart Grid Standards, Test-Beds and Field Trials

Papers in the relevant area of Smart Grid electrical power system, including but not limited to the following, are invited:

  • Resilience in the face of faults and disasters
  • Load management and Load Balancing
  • Customer participation
  • Integration of renewable technology
  • Security & Reliability of the electricity network
  • Smart Algorithms and Devices
  • Smart Grid Modelling
  • Application of Smart Grid concept to Homes, Distribution or Transmission Systems
  • Architectures for Smart Grids
  • Power Quality
  • Power Transmission in a Smart Grid

Prof. Dr. Neville R. Watson
Emeritus Professor Harsha Sirisena
Collection Editors

Manuscript Submission Information

Manuscripts for the topical collection can be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on this website. The topical collection considers regular research articles, short communications and review articles. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Please visit the Instructions for Authors page before submitting a manuscript. The article processing charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs).

Related Special Issues

Published Papers (113 papers)

2018

Jump to: 2017, 2016, 2015, 2014, 2013

Open AccessArticle A Privacy-Preserving Noise Addition Data Aggregation Scheme for Smart Grid
Energies 2018, 11(11), 2972; https://doi.org/10.3390/en11112972
Received: 27 September 2018 / Revised: 19 October 2018 / Accepted: 24 October 2018 / Published: 1 November 2018
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Abstract
Smart meters are applied to the smart grid to report instant electricity consumption to servers periodically; these data enable a fine-grained energy supply. However, these regularly reported data may cause some privacy problems. For example, they can reveal whether the house owner is
[...] Read more.
Smart meters are applied to the smart grid to report instant electricity consumption to servers periodically; these data enable a fine-grained energy supply. However, these regularly reported data may cause some privacy problems. For example, they can reveal whether the house owner is at home, if the television is working, etc. As privacy is becoming a big issue, people are reluctant to disclose this kind of personal information. In this study, we analyzed past studies and found that the traditional method suffers from a meter failure problem and a meter replacement problem, thus we propose a smart meter aggregation scheme based on a noise addition method and the homomorphic encryption algorithm, which can avoid the aforementioned problems. After simulation, the experimental results show that the computation cost on both the aggregator and smart meter side is reduced. A formal security analysis shows that the proposed scheme has semantic security. Full article
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Open AccessArticle Data-Driven Prediction of Load Curtailment in Incentive-Based Demand Response System
Energies 2018, 11(11), 2905; https://doi.org/10.3390/en11112905
Received: 1 October 2018 / Revised: 22 October 2018 / Accepted: 24 October 2018 / Published: 25 October 2018
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Abstract
Demand response, in which energy customers reduce their energy consumption at the request of service providers, is spreading as a new technology. However, the amount of load curtailment from each customer is uncertain. This is because an energy customer can freely decide to
[...] Read more.
Demand response, in which energy customers reduce their energy consumption at the request of service providers, is spreading as a new technology. However, the amount of load curtailment from each customer is uncertain. This is because an energy customer can freely decide to reduce his energy consumption or not in the current liberalized energy market. Because this uncertainty can cause serious problems in a demand response system, it is clear that the amount of energy reduction should be predicted and managed. In this paper, a data-driven prediction method of load curtailment is proposed, considering two difficulties in the prediction. The first problem is that the data is very sparse. Each customer receives a request for load curtailment only a few times a year. Therefore, the k-nearest neighbor method, which requires a relatively small amount of data, is mainly used in our proposed method. The second difficulty is that the characteristic of each customer is so different that a single prediction method cannot cover all the customers. A prediction method that provides remarkable prediction performance for one customer may provide a poor performance for other customers. As a result, the proposed prediction method adopts a weighted ensemble model to apply different models for different customers. The confidence of each sub-model is defined and used as a weight in the ensemble. The prediction is fully based on the electricity consumption data and the history of demand response events without demanding any other additional internal information from each customer. In the experiment, real data obtained from demand response service providers verifies that the proposed framework is suitable for the prediction of each customer’s load curtailment. Full article
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Open AccessArticle Random Violation Risk Degree Based Service Channel Routing Mechanism in Smart Grid
Energies 2018, 11(11), 2871; https://doi.org/10.3390/en11112871
Received: 25 September 2018 / Revised: 16 October 2018 / Accepted: 19 October 2018 / Published: 23 October 2018
PDF Full-text (3156 KB) | HTML Full-text | XML Full-text
Abstract
Smart gird, integrated power network with communication network, has brought an innovation of traditional power for future green energy. Optical fiber technology and synchronous digital hierarchy (SDH) technology is widely used in smart grid communication transmission network. It is a challenge to reduce
[...] Read more.
Smart gird, integrated power network with communication network, has brought an innovation of traditional power for future green energy. Optical fiber technology and synchronous digital hierarchy (SDH) technology is widely used in smart grid communication transmission network. It is a challenge to reduce impact of the availability of smart grid communication services caused by random failures and random time to repair. Firstly, we create a service channel violation risk degree (SCVRD) model to precisely track the violation risk change of communication service channel. It is denoted by the probability of service channel cumulative failure duration exceeding the prescribed duration. Secondly, a service channel violation risk degree routing mechanism is proposed to improve the availability of communication service. At last, the simulation is implemented with MATLAB and network data in one province are used as data instance. The simulation results show that the average service channel failure rate of availability-aware routing based on statistics (AAR-OS) algorithm and risk-aware provisioning algorithm are reduced by 15% and 6%, respectively. Full article
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Open AccessArticle Efficient and Provably Secure Key Agreement for Modern Smart Metering Communications
Energies 2018, 11(10), 2662; https://doi.org/10.3390/en11102662
Received: 18 September 2018 / Revised: 27 September 2018 / Accepted: 1 October 2018 / Published: 6 October 2018
PDF Full-text (889 KB) | HTML Full-text | XML Full-text
Abstract
Security in modern smart metering communications and in smart grid networks has been an area of interest recently. In this field, identity-based mutual authentication including credential privacy without active involvement of a trusted third party is an important building block for smart grid
[...] Read more.
Security in modern smart metering communications and in smart grid networks has been an area of interest recently. In this field, identity-based mutual authentication including credential privacy without active involvement of a trusted third party is an important building block for smart grid technology. Recently, several schemes have been proposed for the smart grid with various security features (e.g., mutual authentication and key agreement). Moreover, these schemes are said to offer session key security under the widely accepted Canetti-Krawczyk (CK) security model. Instead, we argue that all of them are still vulnerable under the CK model. To remedy the problem, we present a new provably secure key agreement model for smart metering communications. The proposed model preserves the security features and provides more resistance against a denial of service attack. Moreover, our scheme is pairing-free, resulting in highly efficient computational and communication efforts. Full article
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Open AccessArticle An Adaptive Weighted Pearson Similarity Measurement Method for Load Curve Clustering
Energies 2018, 11(9), 2466; https://doi.org/10.3390/en11092466
Received: 10 August 2018 / Revised: 30 August 2018 / Accepted: 12 September 2018 / Published: 17 September 2018
PDF Full-text (5765 KB) | HTML Full-text | XML Full-text
Abstract
Load curve data from advanced metering infrastructure record the consumers’ behavior. User consumption models help one understand a more intelligent power provisioning and clustering the load data is one of the popular approaches for building these models. Similarity measurements are important in the
[...] Read more.
Load curve data from advanced metering infrastructure record the consumers’ behavior. User consumption models help one understand a more intelligent power provisioning and clustering the load data is one of the popular approaches for building these models. Similarity measurements are important in the clustering model, but, load curve data is a time series style data, and traditional measurement methods are not suitable for load curve data. To cluster the load curve data more accurately, this paper applied an enhanced Pearson similarity for load curve data clustering. Our method introduces the ‘trend alteration point’ concept and integrates it with the Pearson similarity. By introducing a weight for Pearson distance, this method helps to keep the whole contour of the load data and the partial similarity. Based on the weighed Pearson distance, a weighed Pearson-based hierarchy clustering algorithm is proposed. Years of load curve data are used for evaluation. Several user consumption models are found and analyzed. Results show that the proposed method improves the accuracy of load data clustering. Full article
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Open AccessArticle Matching of Local Load with On-Site PV Production in a Grid-Connected Residential Building
Energies 2018, 11(9), 2409; https://doi.org/10.3390/en11092409
Received: 23 August 2018 / Revised: 7 September 2018 / Accepted: 10 September 2018 / Published: 12 September 2018
Cited by 1 | PDF Full-text (2325 KB) | HTML Full-text | XML Full-text
Abstract
Efficient utilization of renewable generation inside microgrids remains challenging. In most existing studies, the goal is to optimize the energy cost of microgrids by working in synergy with the main grid. This work aimed at maximizing the self-consumption of on-site photovoltaic (PV) generation
[...] Read more.
Efficient utilization of renewable generation inside microgrids remains challenging. In most existing studies, the goal is to optimize the energy cost of microgrids by working in synergy with the main grid. This work aimed at maximizing the self-consumption of on-site photovoltaic (PV) generation using an electrical storage, as well as demand response solutions, in a building that was also capable of interacting with the main grid. Ten-minute resolution data were used to capture the temporal behavior of the weather. Extensive mathematical models were employed to estimate the demand for hot-water consumption, space cooling, and heating loads. The proposed framework is cast as mixed-integer linear programming model while minimizing the interaction with the grid. To evaluate the effectiveness of the proposed framework, it was applied to a typical Finnish household. Matching indices were used to evaluate the degree of overlap between generation and demand under different PV penetrations and storage capacities. Despite negative correlation of PV generation with Finnish seasonal consumption, a significant portion of demand can be satisfied solely with on-site PV generation during the spring and summer seasons. Full article
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Open AccessArticle A Hybrid Machine Learning Model for Electricity Consumer Categorization Using Smart Meter Data
Energies 2018, 11(9), 2235; https://doi.org/10.3390/en11092235
Received: 30 July 2018 / Revised: 22 August 2018 / Accepted: 23 August 2018 / Published: 26 August 2018
PDF Full-text (1972 KB) | HTML Full-text | XML Full-text
Abstract
Time-series smart meter data can record precisely electricity consumption behaviors of every consumer in the smart grid system. A better understanding of consumption behaviors and an effective consumer categorization based on the similarity of these behaviors can be helpful for flexible demand management
[...] Read more.
Time-series smart meter data can record precisely electricity consumption behaviors of every consumer in the smart grid system. A better understanding of consumption behaviors and an effective consumer categorization based on the similarity of these behaviors can be helpful for flexible demand management and effective energy control. In this paper, we propose a hybrid machine learning model including both unsupervised clustering and supervised classification for categorizing consumers based on the similarity of their typical electricity consumption behaviors. Unsupervised clustering algorithm is used to extract the typical electricity consumption behaviors and perform fuzzy consumer categorization, followed by a proposed novel algorithm to identify distinct consumer categories and their consumption characteristics. Supervised classification algorithm is used to classify new consumers and evaluate the validity of the identified categories. The proposed model is applied to a real dataset of U.S. non-residential consumers collected by smart meters over one year. The results indicate that large or special institutions usually have their distinct consumption characteristics while others such as some medium and small institutions or similar building types may have the same characteristics. Moreover, the comparison results with other methods show the improved performance of the proposed model in terms of category identification and classifying accuracy. Full article
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Open AccessArticle Online Coordination of Plug-In Electric Vehicles Considering Grid Congestion and Smart Grid Power Quality
Energies 2018, 11(9), 2187; https://doi.org/10.3390/en11092187
Received: 17 July 2018 / Revised: 11 August 2018 / Accepted: 15 August 2018 / Published: 21 August 2018
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Abstract
This paper first introduces the impacts of battery charger and nonlinear load harmonics on smart grids considering random plug-in of electric vehicles (PEVs) without any coordination. Then, a new centralized nonlinear online maximum sensitivity selection-based charging algorithm (NOL-MSSCA) is proposed for coordinating PEVs
[...] Read more.
This paper first introduces the impacts of battery charger and nonlinear load harmonics on smart grids considering random plug-in of electric vehicles (PEVs) without any coordination. Then, a new centralized nonlinear online maximum sensitivity selection-based charging algorithm (NOL-MSSCA) is proposed for coordinating PEVs that minimizes the costs associated with generation and losses considering network and bus total harmonic distortion (THD). The aim is to first attend the high priority customers and charge their vehicles as quickly as possible while postponing the service to medium and low priority consumers to the off-peak hours, considering network, battery and power quality constraints and harmonics. The vehicles were randomly plugged at different locations during a period of 24 h. The proposed PEV coordination is based on the maximum sensitivity selection (MSS), which is the sensitivity of losses (including fundamental and harmonic losses) with respect to the PEV location (PEV bus). The proposed algorithm uses the decoupled harmonic power flow (DHPF) to model the nonlinear loads (including the PEV chargers) as current harmonic sources and computes the harmonic power losses, harmonic voltages and THD of the smart grid. The MSS vectors are easily determined using the entries of the Jacobian matrix of the DHPF program, which includes the spectrums of all injected harmonics by nonlinear electric vehicle (EV) chargers and nonlinear industrial loads. The sensitivity of the objective function (fundamental and harmonic power losses) to the PEVs were then used to schedule PEVs accordingly. The algorithm successfully controls the network THDv level within the standard limit of 5% for low and moderate PEV penetrations by delaying PEV charging activities. For high PEV penetrations, the installation of passive power filters (PPFs) is suggested to reduce the THDv and manage to fully charge the PEVs. Detailed simulations considering random and coordinated charging were performed on the modified IEEE 23 kV distribution system with 22 low voltage residential networks populated with PEVs that have nonlinear battery chargers. Simulation results are provided without/with filters for different penetration levels of PEVs. Full article
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Open AccessArticle Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings
Energies 2018, 11(8), 2165; https://doi.org/10.3390/en11082165
Received: 31 July 2018 / Revised: 15 August 2018 / Accepted: 17 August 2018 / Published: 19 August 2018
Cited by 3 | PDF Full-text (2448 KB) | HTML Full-text | XML Full-text
Abstract
Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also
[...] Read more.
Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also beneficial for making buildings sustainably greener on account of using V2B technology in conjunction with local photovoltaic (PV) generation. It is assumed that there is no local battery storage other than EVs and that the EV batteries are fully available for driving, so that the EVs batteries must be at the intended state of charge at the departure time announced by the EV driver. Our goal is to exploit the potential of the EV batteries capacity as much as possible in order to permit a large area of solar panels, so that even on sunny days all PV power can be used to supply the building needs or the EV charging at the parking lot. A system architecture and collaboration protocols that account for uncertainties in EV behaviour are proposed. The proposed approach is proven in simulation covering one year period for three locations in different climatic regions of the US, resulting in the electricity bill reductions of 15.8%, 9.1% and 4.9% for California, New Jersey and Alaska, respectively. These results are compared to state-of-the-art research in combining V2B with PV or wind power generation. It is concluded that the achieved electricity bill reductions are superior to the state-of-the-art, because previous work is based on problem formulations that exploit only a part of the potential EV battery capacity. Full article
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Open AccessArticle Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks
Energies 2018, 11(8), 2085; https://doi.org/10.3390/en11082085
Received: 4 July 2018 / Revised: 30 July 2018 / Accepted: 1 August 2018 / Published: 10 August 2018
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Abstract
The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can
[...] Read more.
The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security). Full article
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Open AccessArticle Exploiting Artificial Neural Networks for the Prediction of Ancillary Energy Market Prices
Energies 2018, 11(7), 1906; https://doi.org/10.3390/en11071906
Received: 28 June 2018 / Revised: 17 July 2018 / Accepted: 20 July 2018 / Published: 21 July 2018
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Abstract
The increase of distributed energy resources in the smart grid calls for new ways to profitably exploit these resources, which can participate in day-ahead ancillary energy markets by providing flexibility. Higher profits are available for resource owners that are able to anticipate price
[...] Read more.
The increase of distributed energy resources in the smart grid calls for new ways to profitably exploit these resources, which can participate in day-ahead ancillary energy markets by providing flexibility. Higher profits are available for resource owners that are able to anticipate price peaks and hours of low prices or zero prices, as well as to control the resource in such a way that exploits the price fluctuations. Thus, this study presents a solution in which artificial neural networks are exploited to predict the day-ahead ancillary energy market prices. The study employs the frequency containment reserve for the normal operations market as a case study and presents the methodology utilized for the prediction of the case study ancillary market prices. The relevant data sources for predicting the market prices are identified, then the frequency containment reserve market prices are analyzed and compared with the spot market prices. In addition, the methodology describes the choices behind the definition of the model validation method and the performance evaluation coefficient utilized in the study. Moreover, the empirical processes for designing an artificial neural network model are presented. The performance of the artificial neural network model is evaluated in detail by means of several experiments, showing robustness and adaptiveness to the fast-changing price behaviors. Finally, the developed artificial neural network model is shown to have better performance than two state of the art models, support vector regression and ARIMA, respectively. Full article
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Open AccessReview Peer to Peer Distributed Energy Trading in Smart Grids: A Survey
Energies 2018, 11(6), 1560; https://doi.org/10.3390/en11061560
Received: 27 April 2018 / Revised: 24 May 2018 / Accepted: 25 May 2018 / Published: 14 June 2018
Cited by 2 | PDF Full-text (1241 KB) | HTML Full-text | XML Full-text
Abstract
Due to the expansion of distributed renewable energy resources, peer to peer energy trading (P2P DET) is expected to be one of the key elements of next generation power systems. P2P DET can provide various benefits such as creating a competitive energy market,
[...] Read more.
Due to the expansion of distributed renewable energy resources, peer to peer energy trading (P2P DET) is expected to be one of the key elements of next generation power systems. P2P DET can provide various benefits such as creating a competitive energy market, reducing power outages, increasing overall efficiency of power systems and supplementing alternative sources of energy according to user preferences. Because of these promising advantages, P2P DET has attracted the attention of several researchers. Current research related to P2P DET include demand response optimization, power routing, network communication, security and privacy. This paper presents a review of the main research topics revolving around P2P DET. Particularly, we present a comprehensive survey of existing demand response optimization models, power routing devices and power routing algorithms. We also identify some key challenges faced in realizing P2P DET. Furthermore, we discuss state of the art enabling technologies such as Energy Internet, Blockchain and Software Defined Networking (SDN) and we provide insights into future research directions. Full article
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Open AccessArticle Static and Dynamic Networking of Smart Meters Based on the Characteristics of the Electricity Usage Information
Energies 2018, 11(6), 1532; https://doi.org/10.3390/en11061532
Received: 25 May 2018 / Revised: 8 June 2018 / Accepted: 8 June 2018 / Published: 12 June 2018
PDF Full-text (3705 KB) | HTML Full-text | XML Full-text
Abstract
The normal communication between smart meter and concentrator is a key factor influencing the normal function of users’ power consumption systems. To solve the communication failure of the smart meter caused by the signal conflict as well as the collected consecutive information abnormality
[...] Read more.
The normal communication between smart meter and concentrator is a key factor influencing the normal function of users’ power consumption systems. To solve the communication failure of the smart meter caused by the signal conflict as well as the collected consecutive information abnormality from the same smart meter, according to the chain optimization index, the networking method of static and dynamic combination proposed in this paper is first used to picked out the optimal relay for a smart meter belonging to multiple relay communication ranges. Meanwhile, the communication with other secondary relays is closed to avoid signal conflict. Then the paper forms different combinations of collected data and these combinations are trained in the extreme learning machine (ELM) to find the characteristics value of power consumption information. Finally, in MATLAB simulation, if ELM detects the abnormal information, new communication path could be promptly found through dynamic adjustment of chain optimization weighted coefficient and the weighted coefficient of the number of the relayed smart meters. It solves the problem of consecutive information abnormality from the same smart meter and raises the reliability of smart meter’s communication, having a significantly meaning to guarantee the normal function of users’ power consumption system. Full article
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Open AccessArticle Applications of Complex Network Analysis in Electric Power Systems
Energies 2018, 11(6), 1381; https://doi.org/10.3390/en11061381
Received: 14 March 2018 / Revised: 16 May 2018 / Accepted: 21 May 2018 / Published: 29 May 2018
PDF Full-text (3977 KB) | HTML Full-text | XML Full-text
Abstract
This paper provides a review of the research conducted on complex network analysis (CAN) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement
[...] Read more.
This paper provides a review of the research conducted on complex network analysis (CAN) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the center of mass (COM) concept from physics, and the recently developed controlled delivery grid (CDG) model. An IEEE 30 bus network was utilized as a case study. Results using MATLAB (MathWorks, Inc., Nattick, MA, USA) and PowerWorld (PowerWorld Corporation, Champaign, IL, USA) demonstrate the usefulness of the proposed approach for MGs placement. Full article
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Open AccessArticle Achieving Cost Minimization and Fairness in Multi-Supplier Smart Grid Environment
Energies 2018, 11(6), 1367; https://doi.org/10.3390/en11061367
Received: 14 April 2018 / Revised: 19 May 2018 / Accepted: 22 May 2018 / Published: 28 May 2018
Cited by 1 | PDF Full-text (429 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we study the energy management techniques in the smart grid with multiple energy providers. We seek to minimize the electricity cost. In this paper, the desired objectives are achieved through scheduling of different consumers to different utilities at different time
[...] Read more.
In this paper, we study the energy management techniques in the smart grid with multiple energy providers. We seek to minimize the electricity cost. In this paper, the desired objectives are achieved through scheduling of different consumers to different utilities at different time slots. We consider a practical system where multiple users can be allocated to a single utility, but, a user cannot be assigned to more than one utility. As a first goal, we formulate a sum cost minimization problem subject to independent generation capacity of each utility. A dual decomposition approach is exploited to find an efficient solution where the sub-gradient approach is adopted to update the dual variables. Later, a min-max based optimization framework is adopted to achieve the fairness among different customers. Moreover, suboptimal schemes are also designed to reduce the computational complexity. Simulation results are presented to validate the performance of the proposed solutions. Full article
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Open AccessArticle Value of Residential Investment in Photovoltaics and Batteries in Networks: A Techno-Economic Analysis
Energies 2018, 11(4), 1022; https://doi.org/10.3390/en11041022
Received: 7 April 2018 / Revised: 19 April 2018 / Accepted: 20 April 2018 / Published: 24 April 2018
Cited by 2 | PDF Full-text (6811 KB) | HTML Full-text | XML Full-text
Abstract
Australia has one of the highest rates of residential photovoltaics penetration in the world. The willingness of households to privately invest in energy infrastructure, and the maturing of battery technology, provides significant scope for more efficient energy networks. The purpose of this paper
[...] Read more.
Australia has one of the highest rates of residential photovoltaics penetration in the world. The willingness of households to privately invest in energy infrastructure, and the maturing of battery technology, provides significant scope for more efficient energy networks. The purpose of this paper is to evaluate the scope for promoting distributed generation and storage from within existing network spending. In this paper, a techno-economic analysis is conducted to evaluate the economic impacts on networks of private investment in energy infrastructure. A highly granular probabilistic model of households within a test area was developed and an economic evaluation of both household and network sectors performed. Results of this paper show that PV only installations carry the greatest private return and, at current battery prices, the economics of combined PV and battery systems is marginal. However, when network benefits arising from reducing residential evening peaks, improved reliability, and losses avoided are considered, this can more than compensate for private economic losses. The main conclusion of this paper is that there is significant scope for network benefits in retrofitting existing housing stock through the incentivization of a policy of a more rapid adoption of distributed generation and residential battery storage. Full article
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Open AccessArticle A Distributed Secondary Control Algorithm for Automatic Generation Control Considering EDP and Automatic Voltage Control in an AC Microgrid
Energies 2018, 11(4), 932; https://doi.org/10.3390/en11040932
Received: 8 March 2018 / Revised: 4 April 2018 / Accepted: 12 April 2018 / Published: 13 April 2018
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Abstract
This paper introduces a distributed secondary control algorithm for automatic generation control (AGC) and automatic voltage control (AVC), which aims at matching area generation to area load and minimizing the total generation cost in an alternating current (AC) microgrids. Firstly, the control algorithm
[...] Read more.
This paper introduces a distributed secondary control algorithm for automatic generation control (AGC) and automatic voltage control (AVC), which aims at matching area generation to area load and minimizing the total generation cost in an alternating current (AC) microgrids. Firstly, the control algorithm utilizes a continuous-time distributed algorithm to generate additional control variables to achieve frequency-voltage recovery for all distributed generators (DGs). Secondary, it solves the economic dispatch problem (EDP) by a distributed economic incremental algorithm in the secondary control level, which avoids the problem caused by communication speed inconsistency between secondary and tertiary control levels. This study also utilizes a fully distributed strategy based on secondary communication network to estimate the total load demand. In addition, the proposed algorithm can be used to realize a seamless handover from the islanded mode to the grid-connected mode, run under the condition of short time communication system out of action, and help to realize the plug and play function. Lastly, the stability of the proposed control algorithm is analyzed and proved, and the effectiveness of the method is verified in some case studies. Full article
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Open AccessArticle Probabilistic Steady-State Operation and Interaction Analysis of Integrated Electricity, Gas and Heating Systems
Energies 2018, 11(4), 917; https://doi.org/10.3390/en11040917
Received: 12 March 2018 / Revised: 2 April 2018 / Accepted: 5 April 2018 / Published: 12 April 2018
Cited by 1 | PDF Full-text (32902 KB) | HTML Full-text | XML Full-text
Abstract
The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are limited to integrated electricity and gas networks or integrated electricity and heating networks. This paper proposes a probabilistic steady-state analysis of integrated electricity, gas and heating networks (EGH-IES). Four typical
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The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are limited to integrated electricity and gas networks or integrated electricity and heating networks. This paper proposes a probabilistic steady-state analysis of integrated electricity, gas and heating networks (EGH-IES). Four typical operation modes of an EGH-IES are presented at first. The probabilistic energy flow problem of the EGS-IES considering its operation modes and correlated uncertainties in wind/solar power and electricity/gas/heat loads is then formulated and solved by the Monte Carlo method based on Latin hypercube sampling and Nataf transformation. Numerical simulations are conducted on a sample EGH-IES working in the “electricity/gas following heat” mode to verify the probabilistic analysis proposed in this paper and to study the effects of uncertainties and correlations on the operation of the EGH-IES, especially uncertainty transmissions among the subnetworks. Full article
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Open AccessArticle Power Transformer Operating State Prediction Method Based on an LSTM Network
Energies 2018, 11(4), 914; https://doi.org/10.3390/en11040914
Received: 30 March 2018 / Revised: 10 April 2018 / Accepted: 11 April 2018 / Published: 12 April 2018
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Abstract
The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the
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The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the transformer panorama information are analyzed. The degree of relative deterioration is used to characterize the deterioration of the transformer state. The membership relationship between the relative deterioration degree of each indicator and the transformer state is obtained through fuzzy processing. Through the long short-term memory (LSTM) network, the evolution of the transformer status is extracted, and a data-driven state prediction model is constructed to realize preliminary warning of a potential fault of the equipment. Through the LSTM network, the quantitative index and qualitative index are organically combined in order to perceive the corresponding relationship between the characteristic parameters and the operating state of the transformer. The results of different time-scale prediction cases show that the proposed method can effectively predict the operation status of power transformers and accurately reflect their status. Full article
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Open AccessReview Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions
Energies 2018, 11(3), 596; https://doi.org/10.3390/en11030596
Received: 3 February 2018 / Revised: 22 February 2018 / Accepted: 5 March 2018 / Published: 8 March 2018
Cited by 15 | PDF Full-text (1734 KB) | HTML Full-text | XML Full-text
Abstract
Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and
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Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and the operator. In this system, a priori knowledge about the energy load pattern can help reshape the load and cut the energy demand curve, thus allowing a better management and distribution of the energy in smart grid energy systems. Designing a computationally intelligent load forecasting (ILF) system is often a primary goal of energy demand management. This study explores the state of the art of computationally intelligent (i.e., machine learning) methods that are applied in load forecasting in terms of their classification and evaluation for sustainable operation of the overall energy management system. More than 50 research papers related to the subject identified in existing literature are classified into two categories: namely the single and the hybrid computational intelligence (CI)-based load forecasting technique. The advantages and disadvantages of each individual techniques also discussed to encapsulate them into the perspective into the energy management research. The identified methods have been further investigated by a qualitative analysis based on the accuracy of the prediction, which confirms the dominance of hybrid forecasting methods, which are often applied as metaheurstic algorithms considering the different optimization techniques over single model approaches. Based on extensive surveys, the review paper predicts a continuous future expansion of such literature on different CI approaches and their optimizations with both heuristic and metaheuristic methods used for energy load forecasting and their potential utilization in real-time smart energy management grids to address future challenges in energy demand management. Full article
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Open AccessArticle Secure Protocol and IP Core for Configuration of Networking Hardware IPs in the Smart Grid
Energies 2018, 11(3), 510; https://doi.org/10.3390/en11030510
Received: 23 January 2018 / Revised: 22 February 2018 / Accepted: 23 February 2018 / Published: 27 February 2018
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Abstract
Nowadays, the incorporation and constant evolution of communication networks in the electricity sector have given rise to the so-called Smart Grid, which is why it is necessary to have devices that are capable of managing new communication protocols, guaranteeing the strict requirements of
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Nowadays, the incorporation and constant evolution of communication networks in the electricity sector have given rise to the so-called Smart Grid, which is why it is necessary to have devices that are capable of managing new communication protocols, guaranteeing the strict requirements of processing required by the electricity sector. In this context, intelligent electronic devices (IEDs) with network architectures are currently available to meet the communication, real-time processing and interoperability requirements of the Smart Grid. The new generation IEDs include an Field Programmable Gate Array (FPGA), to support specialized networking switching architectures for the electric sector, as the IEEE 1588-aware High-availability Seamless Redundancy/Parallel Redundancy Protocol (HSR/PRP). Another advantage to using an FPGA is the ability to update or reconfigure the design to support new requirements that are being raised to the standards (IEC 61850). The update of the architecture implemented in the FPGA can be done remotely, but it is necessary to establish a cyber security mechanism since the communication link generates vulnerability in the case the attacker gains physical access to the network. The research presented in this paper proposes a secure protocol and Intellectual Property (IP) core for configuring and monitoring the networking IPs implemented in a Field Programmable Gate Array (FPGA). The FPGA based implementation proposed overcomes this issue using a light Layer-2 protocol fully implemented on hardware and protected by strong cryptographic algorithms (AES-GCM), defined in the IEC 61850-90-5 standard. The proposed secure protocol and IP core are applicable in any field where remote configuration over Ethernet is required for IP cores in FPGAs. In this paper, the proposal is validated in communications hardware for Smart Grids. Full article
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Open AccessArticle Improving Control Efficiency of Dynamic Street Lighting by Utilizing the Dual Graph Grammar Concept
Energies 2018, 11(2), 402; https://doi.org/10.3390/en11020402
Received: 5 December 2017 / Revised: 20 January 2018 / Accepted: 6 February 2018 / Published: 9 February 2018
Cited by 2 | PDF Full-text (450 KB) | HTML Full-text | XML Full-text
Abstract
The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The
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The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The system controls dimming of street lights which is based on traffic intensity. Each luminaire’s light level is adjusted individually to comply with the lighting norms to ensure safety. Benefits of applying the dual graph grammar are twofold. First, it increases expressive power of the mathematical model that the system uses. It becomes possible to take into account complex geographical distribution of sensors and logical dependencies among them. Second, it increases the system’s efficiency by reducing the problem size during run-time. Experimental results show a reduction of the computation time by a factor of 2.8. The approach has been verified in practice. Full article
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Open AccessArticle Smart Grid Applications for a Practical Implementation of IP over Narrowband Power Line Communications
Energies 2017, 10(11), 1782; https://doi.org/10.3390/en10111782
Received: 30 September 2017 / Revised: 29 October 2017 / Accepted: 30 October 2017 / Published: 6 November 2017
Cited by 3 | PDF Full-text (1168 KB) | HTML Full-text | XML Full-text
Abstract
Currently, Advanced Metering Infrastructure (AMI) systems have equipped the low voltage section with a communication system that is being used mainly for metering purposes, but it can be further employed for additional applications related to the Smart Grid (SG) concept. This paper explores
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Currently, Advanced Metering Infrastructure (AMI) systems have equipped the low voltage section with a communication system that is being used mainly for metering purposes, but it can be further employed for additional applications related to the Smart Grid (SG) concept. This paper explores the potential applications beyond metering of the available channel in a Power Line Communication-based AMI system. To that end, IP has been implemented over Narrow Band-Power Line Communication (NB-PLC) in a real microgrid, which includes an AMI system. A thorough review of potential applications for the SG that might be implemented for this representative case is included in order to provide a realistic analysis of the potentiality of NB-PLC beyond smart metering. The results demonstrate that existing AMI systems based on NB-PLC have the capacity to implement additional applications such as remote commands or status signals, which entails an added value for deployed AMI systems. Full article
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Open AccessArticle Data-Driven Optimization of Incentive-based Demand Response System with Uncertain Responses of Customers
Energies 2017, 10(10), 1537; https://doi.org/10.3390/en10101537
Received: 5 September 2017 / Revised: 25 September 2017 / Accepted: 28 September 2017 / Published: 4 October 2017
Cited by 1 | PDF Full-text (3083 KB) | HTML Full-text | XML Full-text
Abstract
Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP) can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of
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Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP) can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective. Full article
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Open AccessArticle A Data Analysis Technique to Estimate the Thermal Characteristics of a House
Energies 2017, 10(9), 1358; https://doi.org/10.3390/en10091358
Received: 5 July 2017 / Revised: 29 August 2017 / Accepted: 30 August 2017 / Published: 8 September 2017
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Abstract
Almost one third of the energy is used in the residential sector, and space heating is the largest part of energy consumption in our houses. Knowledge about the thermal characteristics of a house can increase the awareness of homeowners about the options to
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Almost one third of the energy is used in the residential sector, and space heating is the largest part of energy consumption in our houses. Knowledge about the thermal characteristics of a house can increase the awareness of homeowners about the options to save energy, for example by showing that there is room for improvement of the insulation level. However, calculating the exact value of these characteristics is not possible without precise thermal experiments. In this paper, we propose a method to automatically estimate two of the most important thermal characteristics of a house, i.e., the loss rate and the heat capacity, based on collected data about the temperature and gas usage. The method is evaluated with a data set that has been collected in a real-life case study. Although a ground truth is lacking, the analyses show that there is evidence that this method could provide a feasible way to estimate those values from the thermostat data. More detailed data about the houses in which the data was collected is required to draw stronger conclusions. We conclude that the proposed method is a promising way to add energy saving advice to smart thermostats. Full article
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Open AccessArticle A PMU-Based Method for Smart Transmission Grid Voltage Security Visualization and Monitoring
Energies 2017, 10(8), 1103; https://doi.org/10.3390/en10081103
Received: 26 June 2017 / Revised: 18 July 2017 / Accepted: 25 July 2017 / Published: 27 July 2017
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Abstract
With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading
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With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading margin using PMU data from a wide-area monitoring system (WAMS) to construct the voltage stability boundary (VSB) of a transmission grid. Specifically, a new approach for online loading margin estimation that considers system load trends is proposed based on the Thevenin equivalent (TE) technique and the Mobius transformation (MT) technique. A VSB is then computed by means of real-time PMU measurements and is presented in a complex load power space. VSB can be utilized as a visualization tool that is able to provide real-time visualization of the current voltage stability situation. The proposed method is fast and adequate for online voltage security assessment. Furthermore, it enables us to significantly increase a system operator’s situational awareness for operational decision making. Simulation studies were carried out using different sized power grid models under various operating conditions. The simulation results are shown to validate the capability of the proposed method. Full article
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Open AccessArticle The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management
Energies 2017, 10(7), 884; https://doi.org/10.3390/en10070884
Received: 1 June 2017 / Revised: 27 June 2017 / Accepted: 28 June 2017 / Published: 30 June 2017
Cited by 4 | PDF Full-text (2094 KB) | HTML Full-text | XML Full-text
Abstract
Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing
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Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation. Full article
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Open AccessArticle A Multiconductor Model of Power Line Communication in Medium-Voltage Lines
Energies 2017, 10(6), 816; https://doi.org/10.3390/en10060816
Received: 26 May 2017 / Revised: 9 June 2017 / Accepted: 12 June 2017 / Published: 15 June 2017
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Abstract
Most power line communication (PLC) models are designed to date simulate power lines as two-wire lines. However, in alternating current (AC) electrical distribution, the two-wire option is seldom applied, and medium-voltage lines are most often based on the three-phase configuration. In this context,
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Most power line communication (PLC) models are designed to date simulate power lines as two-wire lines. However, in alternating current (AC) electrical distribution, the two-wire option is seldom applied, and medium-voltage lines are most often based on the three-phase configuration. In this context, the influence of the ground, which constitutes another conductor with specific parameters, cannot be neglected. Two-wire models are characterized by limited accuracy, not allowing us to simulate certain major phenomena affecting PLC. This, for example, could embody the answer to the question of whether it is more advantageous to transmit a signal independently through each phase, reference the signal with respect to another phase or to use the ground as a reference. This paper discusses a multi-conductor model that eliminates the disadvantages outlined above; the proposed model exploits the multi-conductor telegrapher’s equations. In order to be able to include medium-voltage (MV)/ low-voltage (LV) transformers in medium-voltage network models, we constituted a transformer model. The designed models were validated on a real medium-voltage network. To be able to evaluate the suitability of the PLC, the noise in the medium voltage network was measured in order to determine the signal-to-noise ratio (SNR). Full article
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Open AccessArticle A Dual Half-Bridge Converter with Adaptive Energy Storage to Achieve ZVS over Full Range of Operation Conditions
Energies 2017, 10(4), 444; https://doi.org/10.3390/en10040444
Received: 1 December 2016 / Revised: 7 March 2017 / Accepted: 22 March 2017 / Published: 28 March 2017
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Abstract
The phase-shifted full-bridge (PSFB) converter is widely employed in high-power applications. However, circulating current, duty-cycle loss, secondary voltage oscillation, and narrow zero-voltage-switching (ZVS) range are the main drawbacks of the conventional PSFB converter. This paper proposes a novel full-bridge converter to improve the
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The phase-shifted full-bridge (PSFB) converter is widely employed in high-power applications. However, circulating current, duty-cycle loss, secondary voltage oscillation, and narrow zero-voltage-switching (ZVS) range are the main drawbacks of the conventional PSFB converter. This paper proposes a novel full-bridge converter to improve the performance of the conventional PSFB converter. The proposed converter contains two paralleled half-bridge inverters and an auxiliary inductor on the primary side. The rectifier stage is composed of six diodes connected with the form of full-bridge rectification. This structure allows the stored energy for ZVS operation to change adaptively with duty-cycle. The power can be transferred from the primary side to the secondary side during the whole period. Therefore, the requirement of output filter inductance is reduced and the circulating current is removed. The proposed converter is a good candidate for high power, high voltage and variable input voltage applications. The operation principle and performance are verified on a laboratory prototype. Full article
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Open AccessArticle Power Controlling, Monitoring and Routing Center Enabled by a DC-Transformer †
Energies 2017, 10(3), 403; https://doi.org/10.3390/en10030403
Received: 1 February 2017 / Revised: 13 March 2017 / Accepted: 14 March 2017 / Published: 21 March 2017
Cited by 1 | PDF Full-text (4120 KB) | HTML Full-text | XML Full-text
Abstract
The penetration of various types of renewable sources and on-site storage devices have recently focused attention towards DC power distribution in consumer grids to achieve the target of zero/positive energy buildings and communities. To achieve this target, the most important component is the
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The penetration of various types of renewable sources and on-site storage devices have recently focused attention towards DC power distribution in consumer grids to achieve the target of zero/positive energy buildings and communities. To achieve this target, the most important component is the DC consumer grid architecture which can integrate not only renewable sources and storage, but also enable the implementation in any conventional AC distribution network without any significant upgrade. To this end, a unique DC Transformer enabled DC microgrid architecture is presented in this paper. The architecture, called PCmRC (power controlling monitoring routing center) is proposed to manage distributed energy sources and storage at any stage and also directly interconnects the DC consumer grid with the conventional AC power grid. This paper also investigates detailed control algorithms of each component and the DC Transformer topology in addition to proposing four unique stages of grid operational modes to enhance the overall grid stability in any operational condition. The main objectives are to maximize the exploitation of renewable sources, to decrease reliance on fossil fuels, to boost the overall efficiency of the grid by reducing the power conversion losses and demand side management in all possible forms. The simulation platform is designed in MATLAB/Simulink. Simulation results of several types of case studies show the effectiveness of the proposed power distribution and management model. Full article
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Open AccessArticle International Electronical Committee (IEC) 61850 Mapping with Constrained Application Protocol (CoAP) in Smart Grids Based European Telecommunications Standard Institute Machine-to-Machine (M2M) Environment
Energies 2017, 10(3), 393; https://doi.org/10.3390/en10030393
Received: 19 September 2016 / Revised: 10 March 2017 / Accepted: 15 March 2017 / Published: 20 March 2017
Cited by 3 | PDF Full-text (3251 KB) | HTML Full-text | XML Full-text
Abstract
As power systems develop rapidly into smarter and more flexible configurations, so too must the communication technologies that support them. Machine-to-machine (M2M) communication in power systems enables information collection by combining sensors and communication protocols. In doing so, M2M technology supports communication between
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As power systems develop rapidly into smarter and more flexible configurations, so too must the communication technologies that support them. Machine-to-machine (M2M) communication in power systems enables information collection by combining sensors and communication protocols. In doing so, M2M technology supports communication between machines to improve power quality and protection coordination. When functioning in a “smart grid” environment, M2M has been labelled by the European Telecommunications Standard Institute (ETSI). International Electronical Committee (IEC) 61850 as the most important standard in power network systems. As evidence, this communication platform has been used for device data collection/control in substation automation systems and distribution automation systems. If the IEC 61850 information model were to be combined with a set of contemporary web protocols, the potential benefits would be enormous. Therefore, a constrained application protocol (CoAP) has been adopted to create an ETSI M2M communication architecture. CoAP is compared with other protocols (MQTT, SOAP) to demonstrate the validity of using it. This M2M communication technology is applied in an IEC61850, and use the OPNET Modeler 17.1 to demonstrate intercompatibility of CoAP Gateway. The proposed IEC 61850 and CoAP mapping scheme reduces the mapping time and improves throughput. CoAP is useful in the ETSI M2M environment where device capability is able to be limited. Full article
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Open AccessArticle Electric Field Simulations and Analysis for High Voltage High Power Medium Frequency Transformer
Energies 2017, 10(3), 371; https://doi.org/10.3390/en10030371
Received: 26 December 2016 / Revised: 5 March 2017 / Accepted: 10 March 2017 / Published: 16 March 2017
Cited by 3 | PDF Full-text (6362 KB) | HTML Full-text | XML Full-text
Abstract
The electronic power transformer (EPT) raises concerns for its notable size and volume reduction compared with traditional line frequency transformers. Medium frequency transformers (MFTs) are important components in high voltage and high power energy conversion systems such as EPTs. High voltage and high
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The electronic power transformer (EPT) raises concerns for its notable size and volume reduction compared with traditional line frequency transformers. Medium frequency transformers (MFTs) are important components in high voltage and high power energy conversion systems such as EPTs. High voltage and high power make the reliable insulation design of MFT more difficult. In this paper, the influence of wire type and interleaved winding structure on the electric field distribution of MFT is discussed in detail. The electric field distributions for six kinds of typical non-interleaved windings with different wire types are researched using a 2-D finite element method (FEM). The electric field distributions for one non-interleaved winding and two interleaved windings are also studied using 2-D FEM. Furthermore, the maximum electric field intensities are obtained and compared. The results show that, in this case study, compared with foil conductor, smaller maximum electric field intensity can be achieved using litz wire in secondary winding. Besides, interleaving can increase the maximum electric field intensity when insulation distance is constant. The proposed method of studying the electric field distribution and analysis results are expected to make a contribution to the improvement of electric field distribution in transformers. Full article
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Open AccessArticle A Novel High-Frequency Voltage Standing-Wave Ratio-Based Grounding Electrode Line Fault Supervision in Ultra-High Voltage DC Transmission Systems
Energies 2017, 10(3), 309; https://doi.org/10.3390/en10030309
Received: 28 December 2016 / Revised: 21 February 2017 / Accepted: 28 February 2017 / Published: 5 March 2017
Cited by 1 | PDF Full-text (4000 KB) | HTML Full-text | XML Full-text
Abstract
In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC) transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR) is proposed in this paper. The VSWR is defined considering a
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In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC) transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR) is proposed in this paper. The VSWR is defined considering a lossless transmission line, and the characteristics of the VSWR under different conditions are analyzed. It is shown that the VSWR equals 1 when the terminal resistance completely matches the characteristic impedance of the line, and when a short circuit fault occurs on the grounding electrode line, the VSWR will be greater than 1. The VSWR will approach positive infinity under metallic earth fault conditions, whereas the VSWR in non-metallic earth faults will be smaller. Based on these analytical results, a fault supervision criterion is formulated. The effectiveness of the proposed VSWR-based fault supervision technique is verified with a typical UHVDC project established in Power Systems Computer Aided Design/Electromagnetic Transients including DC(PSCAD/EMTDC). Simulation results indicate that the proposed strategy can reliably identify the grounding electrode line fault and has strong anti-fault resistance capability. Full article
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Open AccessArticle A Dynamic Economic Dispatch Model for Uncertain Power Demands in an Interconnected Microgrid
Energies 2017, 10(3), 300; https://doi.org/10.3390/en10030300
Received: 9 November 2016 / Revised: 21 February 2017 / Accepted: 22 February 2017 / Published: 3 March 2017
Cited by 3 | PDF Full-text (1597 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a dynamic economic dispatch (DED) model with sharing of responsibility for supply–demand balance under uncertain demands in a microgrid (MG). For developing the proposed model, an energy band operation scheme, including a tie-line flow (TLF) contraction between the
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In this paper, we propose a dynamic economic dispatch (DED) model with sharing of responsibility for supply–demand balance under uncertain demands in a microgrid (MG). For developing the proposed model, an energy band operation scheme, including a tie-line flow (TLF) contraction between the main grid and the microgrid (MG), is constructed for preventing considerable changes in the TLFs caused by DED optimization. The proposed scheme generalizes the relationship between TLF contractions and MG operational costs. Moreover, a chance-constrained approach is applied to prevent short- and over-supply risks caused by unpredictable demands in the MG. Based on this approach, it is possible to determine the reasonable ramping capability versus operational cost under uncertain power demands in the MG. Full article
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Open AccessArticle Optimal Cooperative Management of Energy Storage Systems to Deal with Over- and Under-Voltages
Energies 2017, 10(3), 293; https://doi.org/10.3390/en10030293
Received: 4 January 2017 / Revised: 24 February 2017 / Accepted: 28 February 2017 / Published: 2 March 2017
Cited by 5 | PDF Full-text (5868 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an optimal cooperative voltage control approach, which coordinates storage units in a distribution network. This technique is developed for storage systems’ active power management with a local strategy to provide robust voltage control and a distributed strategy to deliver optimal
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This paper presents an optimal cooperative voltage control approach, which coordinates storage units in a distribution network. This technique is developed for storage systems’ active power management with a local strategy to provide robust voltage control and a distributed strategy to deliver optimal storage utilization. Accordingly, three control criteria based on predefined node voltage limits are used for network operation including normal, over-voltage, and under-voltage control modes. The contribution of storage units for voltage support is determined using the control modes and the coordination strategies proposed in this paper. This technique is evaluated in two case studies to assess its capability. Full article
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Open AccessReview Multi-Objective Planning Techniques in Distribution Networks: A Composite Review
Energies 2017, 10(2), 208; https://doi.org/10.3390/en10020208
Received: 13 July 2016 / Revised: 16 January 2017 / Accepted: 31 January 2017 / Published: 12 February 2017
Cited by 12 | PDF Full-text (1197 KB) | HTML Full-text | XML Full-text
Abstract
Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming
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Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper. Full article
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Open AccessArticle Implementation and Assessment of a Decentralized Load Frequency Control: Application to Power Systems with High Wind Energy Penetration
Energies 2017, 10(2), 151; https://doi.org/10.3390/en10020151
Received: 12 October 2016 / Revised: 29 November 2016 / Accepted: 13 December 2016 / Published: 24 January 2017
Cited by 3 | PDF Full-text (3511 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify
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This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify the electrical power demand of a variety of thermostatically-controlled loads, maintaining minimum comfort levels and minimizing both infrastructure requirements and primary reserves from the supply side. This low-cost hardware solution avoids any additional wiring, extending the wireless sensor-actuator network technology towards small customers, which account for over a 30% share of the current power demand. Frequency excursions are collected by each individual load controller, considering not only the magnitude of the frequency deviation, but also their evolution over time. Based on these time-frequency excursion characteristics, controllers are capable of modifying the power consumption of thermostatically-controlled loads by switching them off and on, thus contributing to primary frequency control in power systems with higher generation unit oscillations as a consequence of relevant wind power integration. Field tests have been carried out in a laboratory environment to assess the load controller performance, as well as to evaluate the electrical and thermal response of individual loads under frequency deviations. These frequency deviations are estimated from power systems with a high penetration of wind energy, which are more sensitive to frequency oscillations and where demand response can significantly contribute to mitigate these frequency excursions. The results, also included in the paper, evaluate the suitability of the proposed load controllers and their suitability to decrease frequency excursions from the demand side in a decentralized manner. Full article
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Open AccessArticle A Lyapunov Stability Theory-Based Control Strategy for Three-Level Shunt Active Power Filter
Energies 2017, 10(1), 112; https://doi.org/10.3390/en10010112
Received: 16 November 2016 / Revised: 5 January 2017 / Accepted: 10 January 2017 / Published: 18 January 2017
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Abstract
The three-phase three-wire neutral-point-clamped shunt active power filter (NPC-SAPF), which most adopts classical closed-loop feedback control methods such as proportional-integral (PI), proportional-resonant (PR) and repetitive control, can only output 1st–25th harmonic currents with 10–20 kHz switching frequency. The reason for this is that
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The three-phase three-wire neutral-point-clamped shunt active power filter (NPC-SAPF), which most adopts classical closed-loop feedback control methods such as proportional-integral (PI), proportional-resonant (PR) and repetitive control, can only output 1st–25th harmonic currents with 10–20 kHz switching frequency. The reason for this is that the controller design must make a compromise between system stability and harmonic current compensation ability under the condition of less than 20 kHz switching frequency. To broaden the bandwidth of the compensation current, a Lyapunov stability theory-based control strategy is presented in this paper for NPC-SAPF. The proposed control law is obtained by constructing the switching function on the basis of the mathematical model and the Lyapunov candidate function, which can avoid introducing closed-loop feedback control and keep the system globally asymptotically stable. By means of the proposed method, the NPC-SAPF has compensation ability for the 1st–50th harmonic currents, the total harmonic distortion (THD) and each harmonic content of grid currents satisfy the requirements of IEEE Standard 519-2014. In order to verify the superiority of the proposed control strategy, stability conditions of the proposed strategy and the representative PR controllers are compared. The simulation results in MATLAB/Simulink (MathWorks, Natick, MA, USA) and the experimental results obtained on a 6.6 kVA NPC-SAPF laboratory prototype validate the proposed control strategy. Full article
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Open AccessArticle Robustness Area Technique Developing Guidelines for Power System Restoration
Energies 2017, 10(1), 99; https://doi.org/10.3390/en10010099
Received: 28 November 2016 / Revised: 22 December 2016 / Accepted: 4 January 2017 / Published: 13 January 2017
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Abstract
This paper proposes a novel energy based technique called the Robustness Area (RA) technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs). The motivation is on account of the latest blackouts in Brazil, where the local
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This paper proposes a novel energy based technique called the Robustness Area (RA) technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs). The motivation is on account of the latest blackouts in Brazil, where the local Independent System Operator (ISO) encountered difficulties related to circuit disconnections during the restoration. The technique identifies vulnerable and robust buses, pointing out system areas that should be firstly reinforced during PSR, in order to enhance system stability. A Brazilian power system restoration area is used to compare the guidelines adopted by the ISO with a more suitable new plan indicated by the RA tool. Active power and reactive power load margin and standing phase angle show the method efficiency as a result of a well balanced system configuration, enhancing the restoration performance. Time domain simulations for loop closures and severe events also show the positive impact that the proposed tool brings to PSRs. Full article
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2016

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Open AccessArticle A Feedback Passivation Design for DC Microgrid and Its DC/DC Converters
Energies 2017, 10(1), 14; https://doi.org/10.3390/en10010014
Received: 22 October 2016 / Revised: 27 November 2016 / Accepted: 13 December 2016 / Published: 23 December 2016
Cited by 3 | PDF Full-text (2818 KB) | HTML Full-text | XML Full-text
Abstract
There are difficulties in analyzing the stability of microgrids since they are located on various network structures. However, considering that the network often consists of passive elements, the passivity theory is applied in this paper to solve the above-mentioned problem. It has been
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There are difficulties in analyzing the stability of microgrids since they are located on various network structures. However, considering that the network often consists of passive elements, the passivity theory is applied in this paper to solve the above-mentioned problem. It has been formerly shown that when the network is weakly strictly positive real (WSPR), the DC microgrid is stable if all interfaces between the microgrid and converters are made to be passive, which is called interface passivity. Then, the feedback passivation method is proposed for the controller design of various DC–DC converters to achieve the interface passivity. The interface passivity is different from the passivity of closed-loop systems on which the passivity based control (PBC) concentrates. The feedback passivation design is detailed for typical buck converters and boost converters in terms of conditions that the controller parameters should satisfy. The theoretical results are verified by a hardware-in-loop real-time labotray (RTLab) simulation of a DC microgrid with four generators. Full article
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Open AccessArticle Improved Direct Deadbeat Voltage Control with an Actively Damped Inductor-Capacitor Plant Model in an Islanded AC Microgrid
Energies 2016, 9(11), 978; https://doi.org/10.3390/en9110978
Received: 7 October 2016 / Revised: 13 November 2016 / Accepted: 14 November 2016 / Published: 22 November 2016
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Abstract
A direct deadbeat voltage control design method for inverter-based microgrid applications is proposed in this paper. When the inductor-capacitor (LC) filter output voltage is directly controlled using voltage source inverters (VSIs), the plant dynamics exhibit second-order resonant characteristics with a load current disturbance.
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A direct deadbeat voltage control design method for inverter-based microgrid applications is proposed in this paper. When the inductor-capacitor (LC) filter output voltage is directly controlled using voltage source inverters (VSIs), the plant dynamics exhibit second-order resonant characteristics with a load current disturbance. To effectively damp the resonance caused by the output LC filter, an active damping strategy that does not cause additional energy loss is utilized. The proposed direct deadbeat voltage control law is devised from a detailed, actively damped LC plant model. The proposed deadbeat control method enhances voltage control performance owing to its better disturbance rejection capability than the conventional deadbeat or proportional-integral-based control methods. The most important advantage of the proposed deadbeat control method is that it makes the deadbeat control more robust by bringing discrete closed-loop poles closer to the origin. Simulation and experimental results are shown to verify the enhanced voltage control performance and stability of the proposed voltage control method. Full article
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Open AccessArticle Multi-Objective Distribution Network Expansion Incorporating Electric Vehicle Charging Stations
Energies 2016, 9(11), 909; https://doi.org/10.3390/en9110909
Received: 31 August 2016 / Revised: 21 October 2016 / Accepted: 27 October 2016 / Published: 3 November 2016
Cited by 5 | PDF Full-text (4005 KB) | HTML Full-text | XML Full-text
Abstract
The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of
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The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of the economic cost minimization into three objectives with the additional maximization of the charging station utilization, and maximization of the reliability level. Compared with the existing models, it captures the interactive impacts between charging infrastructures planning and distribution network planning from the aspects of economy, utilization, and reliability. A multi-stage search strategy is designed to solve the multi-objective problem. The models and the strategy are demonstrated by the test case. The results show that the proposed planning framework can make a trade-off among the three objectives, and offer a perspective to effectively integrate the network constraints from both the transportation network and distribution network. Full article
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Open AccessArticle Enhanced Multi-Objective Energy Optimization by a Signaling Method
Energies 2016, 9(10), 807; https://doi.org/10.3390/en9100807
Received: 2 August 2016 / Revised: 19 September 2016 / Accepted: 22 September 2016 / Published: 10 October 2016
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Abstract
In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization
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In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance of these methods with the use of multi-dimensional signaling is also compared with this technique, which has previously been shown to boost metaheuristics performance for single-objective problems. Hence, multi-dimensional signaling is adapted and implemented here for the proposed multi-objective problem. In addition, parallel computing is used to mitigate the methods’ computational execution time. To validate the proposed techniques, a realistic case study for a chosen area of the northern region of Portugal is considered, namely part of Vila Real distribution grid (233-bus). It is assumed that this grid is managed by an energy aggregator entity, with reasonable amount of electric vehicles (EVs), several distributed generation (DG), customers with demand response (DR) contracts and energy storage systems (ESS). The considered case study characteristics took into account several reported research works with projections for 2020 and 2050. The findings strongly suggest that the signaling method clearly improves the results and the Pareto front region quality. Full article
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Open AccessArticle A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier
Energies 2016, 9(10), 778; https://doi.org/10.3390/en9100778
Received: 12 June 2016 / Revised: 29 August 2016 / Accepted: 8 September 2016 / Published: 27 September 2016
Cited by 7 | PDF Full-text (8765 KB) | HTML Full-text | XML Full-text
Abstract
Machine learning techniques have been widely used in transient stability prediction of power systems. When using the post-fault dynamic responses, it is difficult to draw a definite conclusion about how long the duration of response data used should be in order to balance
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Machine learning techniques have been widely used in transient stability prediction of power systems. When using the post-fault dynamic responses, it is difficult to draw a definite conclusion about how long the duration of response data used should be in order to balance the accuracy and speed. Besides, previous studies have the problem of lacking consideration for the confidence level. To solve these problems, a hierarchical method for transient stability prediction based on the confidence of ensemble classifier using multiple support vector machines (SVMs) is proposed. Firstly, multiple datasets are generated by bootstrap sampling, then features are randomly picked up to compress the datasets. Secondly, the confidence indices are defined and multiple SVMs are built based on these generated datasets. By synthesizing the probabilistic outputs of multiple SVMs, the prediction results and confidence of the ensemble classifier will be obtained. Finally, different ensemble classifiers with different response times are built to construct different layers of the proposed hierarchical scheme. The simulation results show that the proposed hierarchical method can balance the accuracy and rapidity of the transient stability prediction. Moreover, the hierarchical method can reduce the misjudgments of unstable instances and cooperate with the time domain simulation to insure the security and stability of power systems. Full article
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Open AccessArticle Operation Cost Minimization of Droop-Controlled AC Microgrids Using Multiagent-Based Distributed Control
Energies 2016, 9(9), 717; https://doi.org/10.3390/en9090717
Received: 6 July 2016 / Revised: 15 August 2016 / Accepted: 29 August 2016 / Published: 6 September 2016
Cited by 5 | PDF Full-text (7814 KB) | HTML Full-text | XML Full-text
Abstract
Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power
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Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power rating of the power converters. With various primary source for the distributed generator (DG), factors that are closely related to the operation cost, such as fuel cost of the generators and losses should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent-based distributed method is proposed to minimize the operation cost in AC microgrids. In the microgrid, each DG is acting as an agent which regulates the power individually using a novel power regulation method based on frequency scheduling. An optimal power command is obtained through carefully designed consensus algorithm by using sparse communication links only among neighbouring agents. Experimental results for different cases verified that the proposed control strategy can effectively reduce the operation cost. Full article
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Open AccessEditor’s ChoiceArticle A Conservation Voltage Reduction Scheme for a Distribution Systems with Intermittent Distributed Generators
Energies 2016, 9(9), 666; https://doi.org/10.3390/en9090666
Received: 5 July 2016 / Revised: 16 August 2016 / Accepted: 17 August 2016 / Published: 23 August 2016
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Abstract
In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers.
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In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers. Therefore, an unexpected under-voltage violation can occur due to the variation of active power output from the intermittent DGs. In order to prevent the under-voltage violation and improve the CVR effect, a new reactive power controller which complies with the IEEE Std. 1547TM, and a parameter determination method for the controller are proposed. In addition, an optimal power flow (OPF) problem to determine references for the resources of CVR is formulated with consideration of the intermittent DGs. The proposed method is validated using a modified IEEE 123-node test feeder. With the proposed method, the voltages of the test system are maintained to be greater than the lower bound, even though the active power outputs of the DGs are varied. Moreover, the CVR effect is improved compared to that used with the conventional reactive power control methods. Full article
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Open AccessArticle A Statistical Framework for Automatic Leakage Detection in Smart Water and Gas Grids
Energies 2016, 9(9), 665; https://doi.org/10.3390/en9090665
Received: 7 July 2016 / Revised: 9 August 2016 / Accepted: 11 August 2016 / Published: 23 August 2016
Cited by 1 | PDF Full-text (579 KB) | HTML Full-text | XML Full-text
Abstract
In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution
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In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution grids, the gap between power grids and water/gas grids is notably wide. For this purpose, in this paper, a framework for leakage identification is presented. The framework is composed of three sections aimed at the extraction and the selection of features and at the detection of leakages. A variation of the Sequential Feature Selection (SFS) algorithm is used to select the best performing features within a set, including, also, innovative temporal ones. The leakage identification is based on novelty detection and exploits the characterization of a normality model. Three statistical approaches, The Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and One-Class Support Vector Machine (OC-SVM), are adopted, under a comparative perspective. Both residential and office building environments are investigated by means of two datasets. One is the Almanac of Minutely Power dataset (AMPds), and it provides water and gas data consumption at 1, 10 and 30 min of time resolution; the other is the Department of International Development (DFID) dataset, and it provides water and gas data consumption at 30 min of time resolution. The achieved performance, computed by means of the Area Under the Curve (AUC), reaches 90 % in the office building case study, thus confirming the suitability of the proposed approach for applications in smart water and gas grids. Full article
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Open AccessArticle An Algorithmic Game Approach for Demand Side Management in Smart Grid with Distributed Renewable Power Generation and Storage
Energies 2016, 9(8), 654; https://doi.org/10.3390/en9080654
Received: 2 May 2016 / Revised: 5 August 2016 / Accepted: 6 August 2016 / Published: 18 August 2016
Cited by 4 | PDF Full-text (538 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on
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In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on more challenging scenarios in which jobs are non-interruptible and non-power-shiftable. In addition, as more and more newly-built homes have rooftop solar arrays, it is assumed that all users are equipped with a solar-plus-battery system in this paper. Thus, power can be drawn from the battery as needed to reduce the cost of electricity or to lower the overall system load. With a quadratic load-dependent cost function, this paper first shows that the electricity cost minimization problem in such a setting is NP-hard and presents a distributed demand-side management algorithm, called DDSM, to solve this. Experimental results show that the proposed DDSM algorithm is effective, scalable and converges to a Nash equilibrium in finite rounds. Full article
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Open AccessArticle Broadband PLC for Clustered Advanced Metering Infrastructure (AMI) Architecture
Energies 2016, 9(7), 569; https://doi.org/10.3390/en9070569
Received: 16 April 2016 / Revised: 11 July 2016 / Accepted: 12 July 2016 / Published: 21 July 2016
Cited by 15 | PDF Full-text (791 KB) | HTML Full-text | XML Full-text
Abstract
Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed
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Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed for conventional data networks with different requirements. It is therefore necessary to investigate how much of existing communication technologies can be retrofitted into the new energy infrastructure to cost-effectively deliver acceptable level of service. This paper investigates broadband power line communications (BPLC) as a backhaul solution in AMI. By applying the disparate traffic characteristics of selected AMI applications, the network performance is evaluated. This study also examines the communication network response to changes in application configurations in terms of packet sizes. In each case, the network is stress-tested and performance is assessed against acceptable thresholds documented in the literature. Results show that, like every other communication technology, BPLC has certain limitations; however, with some modifications in the network topology, it indeed can fulfill most AMI traffic requirements for flexible and time-bounded applications. These opportunities, if tapped, can significantly improve fiscal and operational efficiencies in AMI services. Simulation results also reveal that BPLC as a backhaul can support flat and clustered AMI structures with cluster size ranging from 1 to 150 smart meters. Full article
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Open AccessArticle New Scheme for Seamless Operation for Stand-Alone Power Systems
Energies 2016, 9(6), 457; https://doi.org/10.3390/en9060457
Received: 21 April 2016 / Revised: 31 May 2016 / Accepted: 1 June 2016 / Published: 15 June 2016
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Abstract
On remote islands photovoltaic (PV) panels with battery energy storage systems (BESSs) supply electric power to customers in parallel operation with engine generators (EGs) to reduce fuel consumption and environmental burden. A BESS operates in voltage control mode when it supplies power to
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On remote islands photovoltaic (PV) panels with battery energy storage systems (BESSs) supply electric power to customers in parallel operation with engine generators (EGs) to reduce fuel consumption and environmental burden. A BESS operates in voltage control mode when it supplies power to loads alone, while it operates in current control mode when it supplies power to loads in parallel with the EG. This paper proposes a smooth mode change of the BESS from current control to voltage control by using initial value at the output of integral part in the voltage controller, and a smooth mode change from voltage control to current control by tracking the EG output voltage to the BESS output voltage using a phase-locked loop (PLL). The feasibility of the proposed scheme was verified through computer simulations and experiments with a scaled prototype. Full article
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Open AccessArticle A Wavelet-Based Unified Power Quality Conditioner to Eliminate Wind Turbine Non-Ideality Consequences on Grid-Connected Photovoltaic Systems
Energies 2016, 9(6), 390; https://doi.org/10.3390/en9060390
Received: 16 March 2016 / Revised: 26 April 2016 / Accepted: 5 May 2016 / Published: 24 May 2016
Cited by 1 | PDF Full-text (6683 KB) | HTML Full-text | XML Full-text
Abstract
The integration of renewable power sources with power grids presents many challenges, such as synchronization with the grid, power quality problems and so on. The shunt active power filter (SAPF) can be a solution to address the issue while suppressing the grid-end current
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The integration of renewable power sources with power grids presents many challenges, such as synchronization with the grid, power quality problems and so on. The shunt active power filter (SAPF) can be a solution to address the issue while suppressing the grid-end current harmonics and distortions. Nonetheless, available SAPFs work somewhat unpredictably in practice. This is attributed to the dependency of the SAPF controller on nonlinear complicated equations and two distorted variables, such as load current and voltage, to produce the current reference. This condition will worsen when the plant includes wind turbines which inherently produce 3rd, 5th, 7th and 11th voltage harmonics. Moreover, the inability of the typical phase locked loop (PLL) used to synchronize the SAPF reference with the power grid also disrupts SAPF operation. This paper proposes an improved synchronous reference frame (SRF) which is equipped with a wavelet-based PLL to control the SAPF, using one variable such as load current. Firstly the fundamental positive sequence of the source voltage, obtained using a wavelet, is used as the input signal of the PLL through an orthogonal signal generator process. Then, the generated orthogonal signals are applied through the SRF-based compensation algorithm to synchronize the SAPF’s reference with power grid. To further force the remained uncompensated grid current harmonics to pass through the SAPF, an improved series filter (SF) equipped with a current harmonic suppression loop is proposed. Concurrent operation of the improved SAPF and SF is coordinated through a unified power quality conditioner (UPQC). The DC-link capacitor of the proposed UPQC, used to interconnect a photovoltaic (PV) system to the power grid, is regulated by an adaptive controller. Matlab/Simulink results confirm that the proposed wavelet-based UPQC results in purely sinusoidal grid-end currents with total harmonic distortion (THD) = 1.29%, which leads to high electrical efficiency of a grid-connected PV system. Full article
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Open AccessArticle Developing a New HSR Switching Node (SwitchBox) for Improving Traffic Performance in HSR Networks
Energies 2016, 9(1), 36; https://doi.org/10.3390/en9010036
Received: 8 December 2015 / Revised: 5 January 2016 / Accepted: 5 January 2016 / Published: 8 January 2016
Cited by 3 | PDF Full-text (4621 KB) | HTML Full-text | XML Full-text
Abstract
High availability is crucial for industrial Ethernet networks as well as Ethernet-based control systems such as automation networks and substation automation systems (SAS). Since standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using
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High availability is crucial for industrial Ethernet networks as well as Ethernet-based control systems such as automation networks and substation automation systems (SAS). Since standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using redundancy protocols. Various redundancy protocols for Ethernet networks have been developed and standardized, such as rapid spanning tree protocol (RSTP), media redundancy protocol (MRP), parallel redundancy protocol (PRP), high-availability seamless redundancy (HSR) and others. RSTP and MRP have switchover delay drawbacks. PRP provides zero recovery time, but requires a duplicate network infrastructure. HSR operation is similar to PRP, but HSR uses a single network. However, the standard HSR protocol is mainly applied to ring-based topologies and generates excessively unnecessary redundant traffic in the network. In this paper, we develop a new switching node for the HSR protocol, called SwitchBox, which is used in HSR networks in order to support any network topology and significantly reduce redundant network traffic, including unicast, multicast and broadcast traffic, compared with standard HSR. By using the SwitchBox, HSR not only provides seamless communications with zero switchover time in case of failure, but it is also easily applied to any network topology and significantly reduces unnecessary redundant traffic in HSR networks. Full article
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2015

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Open AccessArticle Electricity Customer Clustering Following Experts’ Principle for Demand Response Applications
Energies 2015, 8(10), 12242-12265; https://doi.org/10.3390/en81012242
Received: 15 September 2015 / Revised: 15 October 2015 / Accepted: 20 October 2015 / Published: 27 October 2015
Cited by 8 | PDF Full-text (2241 KB) | HTML Full-text | XML Full-text
Abstract
The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is
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The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is no guarantee that the clustering results are applicable to real domains. In other words, the results might not coincide with those of domain experts. In this paper, we focus on formulating clusters that are applicable to real applications based on domain expert knowledge. More specifically, we try to define a distance between customers that generates clusters that are applicable to demand response applications. First, the k-sliding distance, which is a new distance between two electricity customers, is proposed for customer clustering. The effect of k-sliding distance is verified by expert knowledge. Second, a genetic programming framework is proposed to automatically determine a more improved distance measure. The distance measure generated by our framework can be considered as a reflection of the clustering principles of domain experts. The results of the genetic programming demonstrate the possibility of deriving clustering principles. Full article
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Open AccessArticle A Comparison of Techniques for Reducing Unicast Traffic in HSR Networks
Energies 2015, 8(10), 12029-12060; https://doi.org/10.3390/en81012029
Received: 7 August 2015 / Revised: 14 September 2015 / Accepted: 20 October 2015 / Published: 23 October 2015
Cited by 2 | PDF Full-text (2269 KB) | HTML Full-text | XML Full-text
Abstract
This paper investigates several existing techniques for reducing high-availability seamless redundancy (HSR) unicast traffic in HSR networks for substation automation systems (SAS). HSR is a redundancy protocol for Ethernet networks that provides duplicate frames for separate physical paths with zero recovery time. This
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This paper investigates several existing techniques for reducing high-availability seamless redundancy (HSR) unicast traffic in HSR networks for substation automation systems (SAS). HSR is a redundancy protocol for Ethernet networks that provides duplicate frames for separate physical paths with zero recovery time. This feature of HSR makes it very suited for real-time and mission-critical applications such as SAS systems. HSR is one of the redundancy protocols selected for SAS systems. However, the standard HSR protocol generates too much unnecessary redundant unicast traffic in connected-ring networks. This drawback degrades network performance and may cause congestion and delay. Several techniques have been proposed to reduce the redundant unicast traffic, resulting in the improvement of network performance in HSR networks. These HSR traffic reduction techniques are broadly classified into two categories based on their traffic reduction manner, including traffic filtering-based techniques and predefined path-based techniques. In this paper, we provide an overview and comparison of these HSR traffic reduction techniques found in the literature. The concepts, operational principles, network performance, advantages, and disadvantages of these techniques are investigated, summarized. We also provide a comparison of the traffic performance of these HSR traffic reduction techniques. Full article
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Open AccessReview State of the Art Authentication, Access Control, and Secure Integration in Smart Grid
Energies 2015, 8(10), 11883-11915; https://doi.org/10.3390/en81011883
Received: 16 July 2015 / Revised: 10 October 2015 / Accepted: 12 October 2015 / Published: 21 October 2015
Cited by 13 | PDF Full-text (306 KB) | HTML Full-text | XML Full-text
Abstract
The smart grid (SG) is a promising platform for providing more reliable, efficient, and cost effective electricity to the consumers in a secure manner. Numerous initiatives across the globe are taken by both industry and academia in order to compile various security issues
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The smart grid (SG) is a promising platform for providing more reliable, efficient, and cost effective electricity to the consumers in a secure manner. Numerous initiatives across the globe are taken by both industry and academia in order to compile various security issues in the smart grid network. Unfortunately, there is no impactful survey paper available in the literature on authentications in the smart grid network. Therefore, this paper addresses the required objectives of an authentication protocol in the smart grid network along with the focus on mutual authentication, access control, and secure integration among different SG components. We review the existing authentication protocols, and analyze mutual authentication, privacy, trust, integrity, and confidentiality of communicating information in the smart grid network. We review authentications between the communicated entities in the smart grid, such as smart appliance, smart meter, energy provider, control center (CC), and home/building/neighborhood area network gateways (GW). We also review the existing authentication schemes for the vehicle-to-grid (V2G) communication network along with various available secure integration and access control schemes. We also discuss the importance of the mutual authentication among SG entities while providing confidentiality and privacy preservation, seamless integration, and required access control with lower overhead, cost, and delay. This paper will help to provide a better understanding of current authentication, authorization, and secure integration issues in the smart grid network and directions to create interest among researchers to further explore these promising areas. Full article
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Open AccessArticle An Energy Management Service for the Smart Office
Energies 2015, 8(10), 11667-11684; https://doi.org/10.3390/en81011667
Received: 28 July 2015 / Accepted: 14 October 2015 / Published: 16 October 2015
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Abstract
The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart
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The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum. Full article
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Open AccessArticle Formulation and Analysis of an Approximate Expression for Voltage Sensitivity in Radial DC Distribution Systems
Energies 2015, 8(9), 9296-9319; https://doi.org/10.3390/en8099296
Received: 15 July 2015 / Revised: 23 August 2015 / Accepted: 24 August 2015 / Published: 28 August 2015
Cited by 3 | PDF Full-text (8297 KB) | HTML Full-text | XML Full-text
Abstract
Voltage is an important variable that reflects system conditions in DC distribution systems and affects many characteristics of a system. In a DC distribution system, there is a close relationship between the real power and the voltage magnitude, and this is one of
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Voltage is an important variable that reflects system conditions in DC distribution systems and affects many characteristics of a system. In a DC distribution system, there is a close relationship between the real power and the voltage magnitude, and this is one of major differences from the characteristics of AC distribution systems. One such relationship is expressed as the voltage sensitivity, and an understanding of voltage sensitivity is very useful to describe DC distribution systems. In this paper, a formulation for a novel approximate expression for the voltage sensitivity in a radial DC distribution system is presented. The approximate expression is derived from the power flow equation with some additional assumptions. The results of approximate expression is compared with an exact calculation, and relations between the voltage sensitivity and electrical quantities are analyzed analytically using both the exact form and the approximate voltage sensitivity equation. Full article
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