Special Issue "Distribution System Operation and Control"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (31 August 2018).

Special Issue Editors

Dr. Miadreza Shafie-khah
E-Mail
Guest Editor
Department of Electromechanical Engineering, University of Beira Interior, Calçada Fonte do Lameiro, 6201-001 Covilhã, Portugal
Interests: smart grid; demand response; electric vehicle; power system; electricity market
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleauges,

With high penetration of small-scale renewable energies, as well as electric vehicles in distribution electric network, suitable operation strategies are highly required to manage these new resources. Moreover, some new potentials, such as demand response programs and market players like retailers or energy providers, should be organized in modern distribution networks. For example, one way to approach distribution system problems is by rethinking our distribution system to include the integration of high levels of distributed energy resources (DERs), using microgrid concepts. Basic objectives are improving the reliability, promoting high penetration of renewable sources, dynamic islanding, and improving generation efficiencies through the use of waste heat. For distribution systems to utilize the emerging diversity of DER technology at significant levels of penetration, the basic distribution pyridine needs to be rethought. Managing such a wide and dynamic set of resources and control points can become overwhelming. This Special Issue aims at encouraging researchers to address the solutions to overcome the issue.

Prof. Pierluigi Siano
Dr. Miadreza  Shafie-khah
Guest Editors

Manuscript Submission Information

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Keywords

  • distribution system
  • operation
  • control
  • renewable energy
  • electric vehicle
  • demand response
  • distributed energy resources
  • microgrid
  • smart grid

Published Papers (12 papers)

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Research

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Open AccessArticle
Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources
Energies 2018, 11(11), 3117; https://doi.org/10.3390/en11113117 - 11 Nov 2018
Cited by 3
Abstract
Electric vehicles (EVs) promote many advantages for distribution systems such as increasing efficiency and reliability, decreasing dependence on non-endogenous resources, and reducing pollutant emissions. Due to increased proliferation of EVs and their integration in power systems, management and operation of distribution systems (ODS) [...] Read more.
Electric vehicles (EVs) promote many advantages for distribution systems such as increasing efficiency and reliability, decreasing dependence on non-endogenous resources, and reducing pollutant emissions. Due to increased proliferation of EVs and their integration in power systems, management and operation of distribution systems (ODS) is becoming more important. Recent studies have shown that EV can increase power grid flexibility since EV owners do not use them for 93–96% of the daytime. Therefore, it is important to exploit parking time, during which EVs can act either as a load or distributed storage device, to maximize the benefit for the power system. Following a survey of the current state-of-the-art, this work studies the impact of EV charging on the load profile. Since renewable energy resources (RES) play a critical role in future distribution systems the current case study considered the presence of RES and their stochastic nature has been modeled. The study proceeds with analyzing EV owners’ driving habits, enabling prediction of the network load profile. The impact of: EV charging modes (i.e., controlled and uncontrolled charging), magnitude of wind and photovoltaic (PV) generation, number of EVs (penetration), and driving patterns on the ODS is analyzed. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Optimization of Solar Energy System for the Electric Vehicle at University Campus in Dhaka, Bangladesh
Energies 2018, 11(9), 2433; https://doi.org/10.3390/en11092433 - 14 Sep 2018
Cited by 6
Abstract
The incorporation of renewable energy and the transportation system can be significantly beneficial for the economy and environment of Bangladesh. The main energy source for vehicles in Bangladesh are the country’s natural gas and fuel. However, due to the rapid depletion of the [...] Read more.
The incorporation of renewable energy and the transportation system can be significantly beneficial for the economy and environment of Bangladesh. The main energy source for vehicles in Bangladesh are the country’s natural gas and fuel. However, due to the rapid depletion of the gas reserve, soaring gas prices and global warming, alongside the environmental pollution caused by burning fuel, this raises concerns about these energy sources. Renewable energy offers a plausible solution to these problems. This paper’s objective is to focus on the maximum usages of a solar photovoltaic (PV) system in electrical vehicles and to minimize the environmental impact in terms of CO2 emission. This system may be partially used to power up the electric vehicle with a charging facility and contribute excess power to the national grid. The modeling, with its optimal analysis of the green transportation system, is simulated using the Hybrid Optimization of Multiple Energy Renewables (HOMER) software. The energy produced by the PV system can provide up to 13,792 kWh/year. Approximately 21% of the total production can be used in the charging station for charging the electrical vehicles and the rest of the energy can contribute to the national grid. Moreover, using the proposed concept of green transport will ultimately reduce greenhouse gas emissions by 52,944 kg/year. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessFeature PaperArticle
Dynamic Placement Analysis of Wind Power Generation Units in Distribution Power Systems
Energies 2018, 11(9), 2326; https://doi.org/10.3390/en11092326 - 05 Sep 2018
Cited by 3
Abstract
The placement problem of distributed generators (DGs) in distribution networks becomes much more complicated in the case of using the DGs with renewable energy resources. Due to several reasons such as, their intermittent output powers, the interactions between DGs and the rest of [...] Read more.
The placement problem of distributed generators (DGs) in distribution networks becomes much more complicated in the case of using the DGs with renewable energy resources. Due to several reasons such as, their intermittent output powers, the interactions between DGs and the rest of the distribution network, and considering other involved uncertainties are very vital. This paper develops a new approach for optimal placement of wind energy based DGs (WDGs) in which all of such influences are carefully handled. The proposed method considers the time variations of dynamic nodal demands, nodal voltage magnitudes, and wind speed in the WDG placement process simultaneously. Thereby, an accurate dynamic model of the active and reactive powers injected by the WDG to the system is employed in which the interactions between the WDG and the distribution network are well regarded. Finally, simulation results are given to show the capability of the proposed approach. As it is demonstrated in the numerical analysis of the radial 33-bus distribution test network, the proposed placement algorithm can efficiently determine the optimal bus for connecting the WDG and is suitable for real applications. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Lyapunov-Based Large Signal Stability Assessment for VSG Controlled Inverter-Interfaced Distributed Generators
Energies 2018, 11(9), 2273; https://doi.org/10.3390/en11092273 - 29 Aug 2018
Cited by 7
Abstract
Inverter-interfaced distributed generators (IIDGs) have been widely applied due to their control flexibility. The stability problems of IIDGs under large signal disturbances, such as large load variations and feeder faults, will cause serious impacts on the system. The virtual synchronous generator (VSG) control [...] Read more.
Inverter-interfaced distributed generators (IIDGs) have been widely applied due to their control flexibility. The stability problems of IIDGs under large signal disturbances, such as large load variations and feeder faults, will cause serious impacts on the system. The virtual synchronous generator (VSG) control is an effective scheme for IIDGs to increase transient stability. However, the existing linearized stability models of IIDGs are limited to small disturbances. Hence, this paper proposes a Lyapunov approach based on non-linearized models to assess the large signal stability of VSG-IIDG. The electrostatic machine model is introduced to establish the equivalent nonlinear model. On the basis of Popov’s theory, a Lyapunov function is derived to calculate the transient stability domain. The stability mechanism is revealed by depicting the stability domain using the locus of the angle and the angular frequency. Large signal stability of the VSG-IIDG is quantified according to the boundary of the stability domain. Effects and sensitivity analysis of the key parameters including the cable impedance, the load power, and the virtual inertia on the stability of the VSG-IIDG are also presented. The simulations are performed in PSCAD/EMTDC and the results demonstrate the proposed large signal stability assessment method. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Resilient Multiscale Coordination Control against Adversarial Nodes
Energies 2018, 11(7), 1844; https://doi.org/10.3390/en11071844 - 13 Jul 2018
Cited by 33
Abstract
Multiscale consensus has been studied recently as a new concept in the field of multi-agent systems, which is able to accommodate many complicated coordination control tasks where values are measured in different scales due to, e.g., the constraints of physical environment. In this [...] Read more.
Multiscale consensus has been studied recently as a new concept in the field of multi-agent systems, which is able to accommodate many complicated coordination control tasks where values are measured in different scales due to, e.g., the constraints of physical environment. In this paper, we investigate the problem of resilient multiscale coordination control against a set of adversarial or non-cooperative nodes in directed networks. We design a multiscale filtering algorithm based upon local information which can withstand both faulty and Byzantine nodes. Building on the concept of network robustness, we establish necessary and sufficient conditions guaranteeing multiscale consensus with general time varying scales in the presence of globally bounded as well as locally bounded threats. In particular, for a network containing at most R faulty nodes, multiscale consensus is achieved if and only if the network is (R+1,R+1)-robust. The counterpart when having at most R Byzantine nodes instead is that the induced subnetwork of cooperative nodes is R+1-robust. Conditions guaranteeing resilient consensus for time-dependent networks are developed. Moreover, multiscale formation generation problems are introduced and solved as the generalizations. Finally, some numerical examples including applications in modular microgrids and power systems are worked out to demonstrate the availability of our theoretical results. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
A Distributed PV System Capacity Estimation Approach Based on Support Vector Machine with Customer Net Load Curve Features
Energies 2018, 11(7), 1750; https://doi.org/10.3390/en11071750 - 04 Jul 2018
Cited by 13
Abstract
Most distributed photovoltaic systems (DPVSs) are normally located behind the meter and are thus invisible to utilities and retailers. The accurate information of the DPVS capacity is very helpful in many aspects. Unfortunately, the capacity information obtained by the existing methods is usually [...] Read more.
Most distributed photovoltaic systems (DPVSs) are normally located behind the meter and are thus invisible to utilities and retailers. The accurate information of the DPVS capacity is very helpful in many aspects. Unfortunately, the capacity information obtained by the existing methods is usually inaccurate due to various reasons, e.g., the existence of unauthorized installations. A two-stage DPVS capacity estimation approach based on support vector machine with customer net load curve features is proposed in this paper. First, several features describing the discrepancy of net load curves between customers with DPVSs and those without are extracted based on the weather status driven characteristic of DPVS output power. A one-class support vector classification (SVC) based DPVS detection (DPVSD) model with the input features extracted above is then established to determine whether a customer has a DPVS or not. Second, a bootstrap-support vector regression (SVR) based DPVS capacity estimation (DPVSCE) model with the input features describing the difference of daily total PV power generation between DPVSs with different capacities is proposed to further estimate the specific capacity of the detected DPVS. A case study using a realistic dataset consisting of 183 residential customers in Austin (TX, U.S.A.) verifies the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Game Theoretic Spectrum Allocation in Femtocell Networks for Smart Electric Distribution Grids
Energies 2018, 11(7), 1635; https://doi.org/10.3390/en11071635 - 22 Jun 2018
Cited by 15
Abstract
Ever growing penetration of the behind-the-meter technologies is changing the electricity consumption profiles of end-users. Intelligent coordination of these emerging technologies through a robust communication infrastructure enables their seamless integration with electric utilities’ operation. In this context, an efficient and reliable communication infrastructure [...] Read more.
Ever growing penetration of the behind-the-meter technologies is changing the electricity consumption profiles of end-users. Intelligent coordination of these emerging technologies through a robust communication infrastructure enables their seamless integration with electric utilities’ operation. In this context, an efficient and reliable communication infrastructure plays a pivotal role in enabling optimal integration of emerging resources. In this paper, we propose a game-theory based method to enhance efficiency of the underlying communication network. Specifically, we focus on Femtocell communication technology which is one the promising options for improving poor indoor communication coverage. The major drawback for using femtocell communication technology is cross-layer interference of femto users (FUs) and macro users (MUs) which adversely impact network performance. In this paper, we propose a novel approach for sharing spectrum in a cognitive radio system with FUs and MUs as primary and secondary users, respectively. The underlying problem is formulated as Stackelberg game that is joined with a convex optimization problem. In this study, MUs and FUs are assumed to be selfish, rational and motivated to achieve maximum utility function, while MUs are competing to obtain maximum bandwidth. Finally, we present a closed form solution for the proposed approach which obtains a unique Nash Equilibrium and prioritizes the access of MUs to femto-base stations. Simulation results provide proof of concept and verify the effectiveness of our mathematical modeling. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Microgrids Real-Time Pricing Based on Clustering Techniques
Energies 2018, 11(6), 1388; https://doi.org/10.3390/en11061388 - 30 May 2018
Cited by 5
Abstract
Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level [...] Read more.
Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessEditor’s ChoiceArticle
Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks
Energies 2018, 11(1), 196; https://doi.org/10.3390/en11010196 - 14 Jan 2018
Cited by 26
Abstract
Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with [...] Read more.
Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with competing charging stations, to exchange data such as electricity price, energy demand, and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs’ charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices were communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e., optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Improving Transient Response of Power Converter in a Stand-Alone Microgrid Using Virtual Synchronous Generator
Energies 2018, 11(1), 27; https://doi.org/10.3390/en11010027 - 23 Dec 2017
Cited by 6
Abstract
Multiple power converters based on the droop controllers have been used widely in the microgrid (MG) system. However, owing to the different response time among several types of power converters such as grid-feeding and grid-forming converters, low frequency oscillation occurs with high overshoot [...] Read more.
Multiple power converters based on the droop controllers have been used widely in the microgrid (MG) system. However, owing to the different response time among several types of power converters such as grid-feeding and grid-forming converters, low frequency oscillation occurs with high overshoot in the transient state. This paper proposes a novel control strategy based on the virtual synchronous generator (VSG) for improving transient response of parallel power converters during large disturbance in the stand-alone microgrid. The proposed VSG control, which inherits the transient state characteristic of the synchronous generator, can provide inertia virtually to the system. The transient response of voltage and frequency is improved, while the total system inertia response is compensated. Thus, the system stability can be enhanced by using the proposed VSG control. Additionally, the small signal analysis of the conventional VSG controller and the proposed VSG controller are carried out to show the effectiveness of the proposed VSG controller. The derivation of frequency, which is used to evaluate the inertia support of the VSG controller to the MG system, is discussed. The simulation result demonstrates that the overshoot of the transient response can be reduced, and the system stability is improved when the proposed VSG controller is applied. The MG system based on the real-time simulator OP5600 (OPAL-RT Technologies, Montreal, QC, Canada) is carried out to verify the feasibility of the proposed VSG controller. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Open AccessArticle
Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimization Model for Stand-Alone Microgrid Operation
Energies 2017, 10(12), 1936; https://doi.org/10.3390/en10121936 - 23 Nov 2017
Cited by 16
Abstract
The optimal dispatching model for a stand-alone microgrid (MG) is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, [...] Read more.
The optimal dispatching model for a stand-alone microgrid (MG) is of great importance to its operation reliability and economy. This paper aims at addressing the difficulties in improving the operational economy and maintaining the power balance under uncertain load demand and renewable generation, which could be even worse in such abnormal conditions as storms or abnormally low or high temperatures. A new two-time scale multi-objective optimization model, including day-ahead cursory scheduling and real-time scheduling for finer adjustments, is proposed to optimize the operational cost, load shedding compensation and environmental benefit of stand-alone MG through controllable load (CL) and multi-distributed generations (DGs). The main novelty of the proposed model is that the synergetic response of CL and energy storage system (ESS) in real-time scheduling offset the operation uncertainty quickly. And the improved dispatch strategy for combined cooling-heating-power (CCHP) enhanced the system economy while the comfort is guaranteed. An improved algorithm, Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy (SIP-CO-PSO-ERS) algorithm with strong searching capability and fast convergence speed, was presented to deal with the problem brought by the increased errors between actual renewable generation and load and prior predictions. Four typical scenarios are designed according to the combinations of day types (work day or weekend) and weather categories (sunny or rainy) to verify the performance of the presented dispatch strategy. The simulation results show that the proposed two-time scale model and SIP-CO-PSO-ERS algorithm exhibit better performance in adaptability, convergence speed and search ability than conventional methods for the stand-alone MG’s operation. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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Review

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Open AccessReview
A Multidisciplinary Approach for the Development of Smart Distribution Networks
Energies 2018, 11(10), 2530; https://doi.org/10.3390/en11102530 - 21 Sep 2018
Cited by 7
Abstract
Electric power systems are experiencing relevant changes involving the growing penetration of distributed generation and energy storage systems, the introduction of electric vehicles, the management of responsive loads, the proposals for new energy markets and so on. Such an evolution is pushing a [...] Read more.
Electric power systems are experiencing relevant changes involving the growing penetration of distributed generation and energy storage systems, the introduction of electric vehicles, the management of responsive loads, the proposals for new energy markets and so on. Such an evolution is pushing a paradigm shift that is one of the most important challenges in power network design: the management must move from traditional planning and manual intervention to full “smartization” of medium and low voltage networks. Peculiarities and criticalities of future power distribution networks originate from the complexity of the system which includes both the physical aspects of electric networks and the cyber aspects, like data elaboration, feature extraction, communication, supervision and control; only fully integrated advanced monitoring systems can foster this transition towards network automation. The design and development of such future networks require distinct kinds of expertise in the industrial and information engineering fields. In this context, this paper provides a comprehensive review of current challenges and multidisciplinary interactions in the development of smart distribution networks. The aim of this paper is to discuss, in an integrated and organized manner, the state of the art while focusing on the need for interaction between different disciplines and highlighting how innovative and future-proof outcomes of both research and practice can only emerge from a coordinated design of all the layers in the smart distribution network architecture. Full article
(This article belongs to the Special Issue Distribution System Operation and Control)
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