Special Issue "Distributed Energy Resources Management 2018"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: closed (28 February 2019).

Special Issue Editors

Guest Editor
Dr. Pedro Faria Website E-Mail
GECAD–Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, Portugal
Interests: demand response; electricity markets; renewable energy integration; real-time simulation; smart grids; virtual power players
Guest Editor
Prof. Dr. Zita Vale Website E-Mail
Engineering Institute, Polytechnic of Porto, Portugal
Interests: artificial intelligence, demand response, electric vehicles, multi-agent systems, optimization, power & energy systems, smart grids

Special Issue Information

Dear Colleagues,

This Special Issue, “Distributed Energy Resources Management 2018”, is a continuation of the Special Issue “Distributed Energy Resources Management”. The success of the previous Special Issue shows the unquestionable relevance of distributed energy resources in the operation of power and energy systems at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicles charging. Demand response has a great potential to contribute to increased system efficiency while bringing additional benefits, namely to consumers. Distributed storage is also promising, especially when jointly used with photovoltaic panels. This Special Issue addresses the management of distributed energy resources with focus on methods and techniques to achieve an optimized operation, to aggregate the resources namely in the scope of virtual power players and other types of aggregators, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as an enabler for their increased and efficient use.

Dr. Pedro Faria
Dr. Zita Vale
Guest Editors

Manuscript Submission Information

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Keywords

  • demand response
  • electricity markets
  • renewable energy integration
  • real-time simulation
  • smart grids
  • virtual power players

Published Papers (13 papers)

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Research

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Open AccessArticle
Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House
Energies 2019, 12(9), 1645; https://doi.org/10.3390/en12091645 - 30 Apr 2019
Abstract
Demand response as a distributed resource has proved its significant potential for power systems. It is capable of providing flexibility that, in some cases, can be an advantage to suppress the unpredictability of distributed generation. The ability for participating in demand response programs [...] Read more.
Demand response as a distributed resource has proved its significant potential for power systems. It is capable of providing flexibility that, in some cases, can be an advantage to suppress the unpredictability of distributed generation. The ability for participating in demand response programs for small or medium facilities has been limited; with the new policy regulations this limitation might be overstated. The prosumers are a new entity that is considered both as producers and consumers of electricity, which can provide excess production to the grid. Moreover, the decision-making in facilities with different generation resources, energy storage systems, and demand flexibility becomes more complex according to the number of considered variables. This paper proposes a demand response optimization methodology for application in a generic residential house. In this model, the users are able to perform actions of demand response in their facilities without any contracts with demand response service providers. The model considers the facilities that have the required devices to carry out the demand response actions. The photovoltaic generation, the available storage capacity, and the flexibility of the loads are used as the resources to find the optimal scheduling of minimal operating costs. The presented results are obtained using a particle swarm optimization and compared with a deterministic resolution in order to prove the performance of the model. The results show that the use of demand response can reduce the operational daily cost. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Virtual Organization Structure for Agent-Based Local Electricity Trading
Energies 2019, 12(8), 1521; https://doi.org/10.3390/en12081521 - 22 Apr 2019
Abstract
End-users are more active because of demand response programs and the penetration of distributed energy resources in the bottom-layer of the power systems. This paper presents a virtual organization of agents of the power distribution grid for local energy trade. An iterative algorithm [...] Read more.
End-users are more active because of demand response programs and the penetration of distributed energy resources in the bottom-layer of the power systems. This paper presents a virtual organization of agents of the power distribution grid for local energy trade. An iterative algorithm is proposed; it enables interaction between end-users and the Distribution Company (DisCo). Then, the performance of the proposed algorithm is evaluated in a 33-bus distribution network; its effectiveness is measured in terms of its impact on the energy trading scenarios and, thus, of its contribution to the energy management problem. According to the simulation results, although aggregators do not play the role of decision makers in the proposed model, our iterative algorithm is profitable for them. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks
Energies 2019, 12(6), 1182; https://doi.org/10.3390/en12061182 - 26 Mar 2019
Abstract
In recent years, the installation of residential Distributed Energy Resources (DER) that produce (mainly rooftop photovoltaics usually bundled with battery system) or consume (electric heat pumps, controllable loads, electric vehicles) electric power is continuously increasing in Low Voltage (LV) distribution networks. Several technical [...] Read more.
In recent years, the installation of residential Distributed Energy Resources (DER) that produce (mainly rooftop photovoltaics usually bundled with battery system) or consume (electric heat pumps, controllable loads, electric vehicles) electric power is continuously increasing in Low Voltage (LV) distribution networks. Several technical challenges may arise through the massive integration of DER, which have to be addressed by the distribution grid operator. However, DER can provide certain degree of flexibility to the operation of distribution grids, which is generally performed with temporal shifting of energy to be consumed or injected. This work advances a horizon optimization control framework which aims to efficiently schedule the LV network’s operation in day-ahead scale coordinating multiple DER. The main objectives of the proposed control is to ensure secure LV grid operation in the sense of admissible voltage bounds and rated loading conditions for the secondary transformer. The proposed methodology leans on a multi-period three-phase Optimal Power Flow (OPF) addressed as a nonlinear optimization problem. The resulting horizon control scheme is validated within an LV distribution network through multiple case scenarios with high microgeneration and electric vehicle integration providing admissible voltage limits and avoiding unnecessary active power curtailments. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method
Energies 2019, 12(4), 579; https://doi.org/10.3390/en12040579 - 13 Feb 2019
Abstract
This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main [...] Read more.
This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main grid bill, which includes an energy cost and a power peak cost. The method predicts the loads and generation power of each day, and then searches for an optimal storage behavior plan for the energy storage system according to these predictions. However, this plan is not followed in an open-loop control structure as in previous publications, but provided to a real-time decision algorithm, which also considers real power measures. This algorithm considers a series of device priorities in addition to the storage plan, which makes it robust enough to comply with unpredicted situations. The whole proposed method is implemented on a real-hardware test bench, with its different steps being distributed between a personal computer and a programmable logic controller according to their time scale. When compared to a different state-of-the-art method, the proposed method is concluded to better adjust the energy storage system usage to the photovoltaic generation and general consumption. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Decentralised Active Power Control Strategy for Real-Time Power Balance in an Isolated Microgrid with an Energy Storage System and Diesel Generators
Energies 2019, 12(3), 511; https://doi.org/10.3390/en12030511 - 06 Feb 2019
Cited by 2
Abstract
Remote microgrids with battery energy storage systems (BESSs), diesel generators, and renewable energy sources (RESs) have recently received significant attention because of their improved power quality and remarkable capability of continuous power supply to loads. In this paper, a new proportional control method [...] Read more.
Remote microgrids with battery energy storage systems (BESSs), diesel generators, and renewable energy sources (RESs) have recently received significant attention because of their improved power quality and remarkable capability of continuous power supply to loads. In this paper, a new proportional control method is proposed using frequency-bus-signaling to achieve real-time power balance continuously under an abnormal condition of short-term power shortage in a remote microgrid. Specifically, in the proposed method, the frequency generated by the grid-forming BESS is used as a global signal and, based on the signal, a diesel generator is then controlled indirectly. The frequency is controlled to be proportional to the AC voltage deviation of the grid-forming BESS to detect sudden power shortages and share active power with other generators. Unlike a conventional constant-voltage constant-frequency (CVCF) control method, the proposed method can be widely applied to optimise the use of distributed energy resources (DERs), while maintaining microgrid voltages within an allowable range, particularly when active power balance cannot be achieved only using CVCF control. For case studies, a comprehensive model of an isolated microgrid is developed using real data. Simulation results are obtained using MATLAB/Simulink to verify the effectiveness of the proposed method in improving primary active power control in the microgrid. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization
Energies 2019, 12(3), 370; https://doi.org/10.3390/en12030370 - 24 Jan 2019
Cited by 1
Abstract
This paper proposes Object-Oriented Usability Indices (OOUI) for multi-objective Demand Side Management (DSM). These indices quantify the achievements of multi-objective DSM in a power network. DSM can be considered as a method adopted by utilities to shed some load during peak load hours. [...] Read more.
This paper proposes Object-Oriented Usability Indices (OOUI) for multi-objective Demand Side Management (DSM). These indices quantify the achievements of multi-objective DSM in a power network. DSM can be considered as a method adopted by utilities to shed some load during peak load hours. Usually, there are service contracts, and the curtailments or dimming of load are automatically done by service providers based on contract provisions. This paper formulates three indices, namely peak power shaving, renewable energy integration, and an overall usability index. The first two indices indicate the amount of peak load shaving and integration of renewable energy, while the third one combines the impact of both indices and quantifies the overall benefit achieved through DSM. The application of the proposed indices is presented through simulation performed in a grid-tied microgrid environment for a multi-objective DSM formulation. The adopted microgrid structure consists of three units of diesel generators and two renewable energy sources. Simulation has been done using MATLAB software. Teaching-Learning-Based Optimization (TLBO) is adopted as the optimization tool due to its simplicity and independency of algorithm-specific control parameters. Five different cases of renewable energy availability with results validate the efficiency of the proposed approach. The results indicate the usefulness in determining the suitable condition regarding DSM application. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Fault-Tolerant Temperature Control Algorithm for IoT Networks in Smart Buildings
Energies 2018, 11(12), 3430; https://doi.org/10.3390/en11123430 - 07 Dec 2018
Cited by 5
Abstract
The monitoring of the Internet of things networks depends to a great extent on the availability and correct functioning of all the network nodes that collect data. This network nodes all of which must correctly satisfy their purpose to ensure the efficiency and [...] Read more.
The monitoring of the Internet of things networks depends to a great extent on the availability and correct functioning of all the network nodes that collect data. This network nodes all of which must correctly satisfy their purpose to ensure the efficiency and high quality of monitoring and control of the internet of things networks. This paper focuses on the problem of fault-tolerant maintenance of a networked environment in the domain of the internet of things. Based on continuous-time Markov chains, together with a cooperative control algorithm, a novel feedback model-based predictive hybrid control algorithm is proposed to improve the maintenance and reliability of the internet of things network. Virtual sensors are substituted for the sensors that the algorithm predicts will not function properly in future time intervals; this allows for maintaining reliable monitoring and control of the internet of things network. In this way, the internet of things network improves its robustness since our fault tolerant control algorithm finds the malfunction nodes that are collecting incorrect data and self-correct this issue replacing malfunctioning sensors with new ones. In addition, the proposed model is capable of optimising sensor positioning. As a result, data collection from the environment can be kept stable. The developed continuous-time control model is applied to guarantee reliable monitoring and control of temperature in a smart supermarket. Finally, the efficiency of the presented approach is verified with the results obtained in the conducted case study. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
A Study on the Multi-Agent Based Comprehensive Benefits Simulation Analysis and Synergistic Optimization Strategy of Distributed Energy in China
Energies 2018, 11(12), 3260; https://doi.org/10.3390/en11123260 - 23 Nov 2018
Cited by 1
Abstract
With the economic and social development of China, the continuous growth of the energy demand is the trend for now and the future. As a consequence, distributed energy, especially distributed electricity power generation, has received more and more attention. Thus, the scale and [...] Read more.
With the economic and social development of China, the continuous growth of the energy demand is the trend for now and the future. As a consequence, distributed energy, especially distributed electricity power generation, has received more and more attention. Thus, the scale and utilization level of distributed energy has been continuously improved. However, due to the limitations of current technologies, resources, policies and other issues, the comprehensive benefits and synergy levels of energy sources need to be greatly enhanced. Based on the system dynamics model, this paper examines the factors affecting the comprehensive benefits of distributed energy in China, screens the key subjects, and using the literature review method, combined with the existing literature analysis, constructs a comprehensive benefit evaluation index system and evaluates the comprehensive benefits through case analysis. This paper also sorts out the distributed energy-related Chinese government policies from 2001 to 2017, and considers the scale of distributed energy development, then divides it into two development stages. The synergetic entropy is used to analyze the synergetic development degree of the two-stage distributed energy entities. The synergistic optimization strategy is proposed from the Chinese government side, power supply side, power grid side and user side, which provides theoretical methods and optimization suggestions for improving the comprehensive benefits of distributed energy and promoting sustainable development of energy. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Double Layer Dynamic Game Bidding Mechanism Based on Multi-Agent Technology for Virtual Power Plant and Internal Distributed Energy Resource
Energies 2018, 11(11), 3072; https://doi.org/10.3390/en11113072 - 07 Nov 2018
Cited by 1
Abstract
As renewable energies become the main direction of global energy development in the future, Virtual Power Plant (VPP) becomes a regional multi-energy aggregation model for large-scale integration of distributed generation into the power grid. It also provides an important way for distributed energy [...] Read more.
As renewable energies become the main direction of global energy development in the future, Virtual Power Plant (VPP) becomes a regional multi-energy aggregation model for large-scale integration of distributed generation into the power grid. It also provides an important way for distributed energy resources (DER) to participate in electricity market transactions. Firstly, the basic concept of VPP is outlined, and various uncertainties within VPP are modeled. Secondly, using multi-agent technology and Stackelberg dynamic game theory, a double-layer nested dynamic game bidding model including VPP and its internal DERs is designed. The lower layer is a bidding game for VPP internal market including DER. VPP is the leader and each DER is a subagent that acts as a follower to maximize its profit. Each subagent uses the particle swarm algorithm (PSA) to determine the optimal offer coefficient, and VPP carries out internal market clearing with the minimum variance of unit profit according to the quoting results. Then, the subagents renew the game to update the bidding strategy based on the outcomes of the external and internal markets. The upper layer is the external market bidding game. The trading center (TC) is the leader and VPP is the agent and the follower. The game is played with the goal of maximum self-interest. The agent uses genetic algorithms to determine the optimal bid strategy, and the TC carries out market clearance with the goal of maximizing social benefits according to the quotation results. Each agent renews the game to update the bidding strategy based on the clearing result and the reporting of the subagents. The dynamic game is repeated until the optimal equilibrium solution is obtained. Finally, the effectiveness of the model is verified by taking the IEEE30-bus system as an example. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination
Energies 2018, 11(9), 2476; https://doi.org/10.3390/en11092476 - 18 Sep 2018
Abstract
This paper focuses on a multi-agent coordination for demand-side management in electrical grids with high penetration rates of distributed generation, in particular photovoltaic generation. This coordination is done by the use of swarm intelligence and coupled oscillators, proposing a novel methodology, which is [...] Read more.
This paper focuses on a multi-agent coordination for demand-side management in electrical grids with high penetration rates of distributed generation, in particular photovoltaic generation. This coordination is done by the use of swarm intelligence and coupled oscillators, proposing a novel methodology, which is implemented by the so-call SwarmGrid algorithm. SwarmGrid seeks to smooth the aggregated consumption by considering distributed and local generation by the development of a self-organized algorithm based on multifrequency agent coordination. The objective of this algorithm is to increase stability and reduce stress of the electrical grid by the aggregated consumption smoothing based on a frequency domain approach. The algorithm allows not only improvements in the electrical grid, but also increases the penetration of distributed and renewable sources. Contrary to other approaches, this objective is achieved anonymously without the need for information exchange between the users; it only takes into account the aggregated consumption of the whole grid. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessArticle
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
Energies 2018, 11(8), 1987; https://doi.org/10.3390/en11081987 - 31 Jul 2018
Cited by 5
Abstract
Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player [...] Read more.
Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Review

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Open AccessReview
A Healthy, Energy-Efficient and Comfortable Indoor Environment, a Review
Energies 2019, 12(8), 1414; https://doi.org/10.3390/en12081414 - 12 Apr 2019
Cited by 1
Abstract
Design strategies for sustainable buildings, that improve building performance and avoid extensive resource utilization, should also promote healthy indoor environments. The following paper contains a review of the couplings between (1) building design, (2) indoor environmental quality and (3) occupant behavior. The paper [...] Read more.
Design strategies for sustainable buildings, that improve building performance and avoid extensive resource utilization, should also promote healthy indoor environments. The following paper contains a review of the couplings between (1) building design, (2) indoor environmental quality and (3) occupant behavior. The paper focuses on defining the limits of adaptation on the three aforementioned levels to ensure the energy efficiency of the whole system and healthy environments. The adaptation limits are described for measurable physical parameters and the relevant responsible human sensory systems, evaluating thermal comfort, visual comfort, indoor air quality and acoustical quality. The goal is to describe the interactions between the three levels where none is a passive participant, but rather an active agent of a wider human-built environment system. The conclusions are drawn in regard to the comfort of the occupant. The study reviews more than 300 sources, ranging from journals, books, conference proceedings, and reports complemented by a review of standards and directives. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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Open AccessReview
Local Markets for Flexibility Trading: Key Stages and Enablers
Energies 2018, 11(11), 3074; https://doi.org/10.3390/en11113074 - 08 Nov 2018
Cited by 2
Abstract
The European energy transition is leading to a transformed electricity system, where Distributed Energy Resources (DERs) will play a substantial role. Renewable Energy Sources (RES) will challenge the key operational obligation of real-time balancing and the need for flexibility will consequently increase. The [...] Read more.
The European energy transition is leading to a transformed electricity system, where Distributed Energy Resources (DERs) will play a substantial role. Renewable Energy Sources (RES) will challenge the key operational obligation of real-time balancing and the need for flexibility will consequently increase. The introduction of a local flexibility market (LFM) would allow the trading of flexibility supplied by both producing and consuming units at the distribution level, providing market access to DERs, a support tool for Distribution System Operators (DSOs) and a value stream for energy suppliers. Aggregators and DSOs for different reasons can enhance the valuation of flexible DERs. Several research papers have assumed aggregators fully interacting with the electricity markets and DSOs contracting services with power system actors. These interactions are still not allowed in many European countries. This article aims to analyze the European regulation to identify the most important enablers and pave the way towards the full exploitation of DER flexibility, culminating in the establishment of an LFM. Therefore, three main stages, emerging from the progressive withdrawal of the current regulatory and market barriers, are identified: (1) enabling the aggregator’s trading, (2) evolution of the DSO’s role, and (3) key-design challenges of an LFM. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management 2018)
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