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Energy storage systems have been recognized as viable solutions for implementing the smart grid paradigm, but have created challenges in terms of load levelling, integrating renewable and intermittent sources, voltage and frequency regulation, grid resiliency, improving power quality and reliability, reducing energy import during peak demand periods, and so on. In particular, distributed energy storage addresses a wide range of the above potential issues, and it is gaining attention from customers, utilities, and regulators. Distributed energy storage has considerable potential for reducing costs and improving the quality of electric services. However, installation costs and lifespan are the main drawbacks to the wide diffusion of this technology. In this context, a serious challenge is the adoption of new techniques and strategies for the optimal planning, control, and management of grids that include distributed energy storage devices. Regulatory guidance and proactive policies are urgently needed to ensure a smooth rollout of this technology. This book collects recent contributions of methodologies applied to the integration of distributed energy storage devices in smart power systems. Several areas of research (optimal siting and sizing of energy storage systems, adaption of energy storage systems to load leveling and harmonic compensation, integration for electric vehicles, and optimal control systems) are investigated in the contributions collected in this book.

decision theory --- voltage dips --- robust optimization --- Multiport Converter (MPC) --- storage --- uncertainty --- harmonics --- battery energy storage systems (BESS) --- second life batteries --- optimization --- stationary storage --- charging station --- scheduling --- Energy Storage Device (ESD) --- Grid Connected Photovoltaic Systems (GCPVS) --- plug-in --- electricity market --- economic analysis --- batteries --- distribution system --- distribution network planning --- Electric Vehicle (EV) --- active harmonic filter --- Intelligent Energy Management System (iEMS) --- battery electric vehicle --- fast charge --- microgrid planning --- EV --- planning --- BEV --- energy storage system --- decision-making --- power quality --- electrical energy storage systems --- load leveling

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Electric power systems around the world are changing in terms of structure, operation, management and ownership due to technical, financial, and ideological reasons. Power systems keep on expanding in terms of geographical areas, asset additions, and the penetration of new technologies in generation, transmission, and distribution. The conventional methods for solving the power system design, planning, operation, and control problems have been extensively used for different applications, but these methods suffer from several difficulties, thus providing suboptimal solutions. Computationally intelligent methods can offer better solutions for several conditions and are being widely applied in electrical engineering applications. This Special Issue represents a thorough treatment of computational intelligence from an electrical power system engineer’s perspective. Thorough, well-organised, and up-to-date, it examines in detail some of the important aspects of this very exciting and rapidly emerging technology, including machine learning, particle swarm optimization, genetic algorithms, and deep learning systems. Written in a concise and flowing manner by experts in the area of electrical power systems who have experience in the application of computational intelligence for solving many complex and difficult power system problems, this Special Issue is ideal for professional engineers and postgraduate students entering this exciting field.

localization --- reactive power optimization --- model predictive control --- CNN --- long short term memory (LSTM) --- meter allocation --- particle update mode --- combined economic emission/environmental dispatch --- glass insulator --- emission dispatch --- genetic algorithm --- grid observability --- defect detection --- feature extraction --- parameter estimation --- incipient cable failure --- active distribution system --- boiler load constraints --- multivariate time series --- particle swarm optimization --- inertia weight --- VMD --- NOx emissions constraints --- spatial features --- penalty factor approach --- self-shattering --- differential evolution algorithm --- short term load forecasting (STLF) --- genetic algorithm (GA) --- economic load dispatch --- least square support vector machine --- Combustion efficiency --- electricity load forecasting

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The deployment of distributed renewable energy resources (DRERs) has accelerated globally due to environmental concerns and an increasing demand for electricity. DRERs are considered to be solutions to some of the current challenges related to power grids, such as reliability, resilience, efficiency, and flexibility. However, there are still several technical and non-technical challenges regarding the deployment of distributed renewable energy resources. Technical concerns associated with the integration and control of DRERs include, but are not limited, to optimal sizing and placement, optimal operation in grid-connected and islanded modes, as well as the impact of these resources on power quality, power system security, stability, and protection systems. On the other hand, non-technical challenges can be classified into three categories—regulatory issues, social issues, and economic issues. This Special Issue will address all aspects related to the integration and control of distributed renewable energy resources. It aims to understand the existing challenges and explore new solutions and practices for use in overcoming technical challenges.

distribution system --- microgrids --- power quality --- power system management --- power system reliability --- smart grids --- distribution networks --- Monte Carlo simulations --- PV hosting capacity --- photovoltaics --- green communities --- energy independence --- HOMER --- wind turbines --- power losses --- power system optimization --- PV curves --- DG --- TSA/SCA --- solar-powered electric vehicle parking lots --- different PV technologies --- PLO’s profit --- uncertainties --- smart grid paradigm --- distributed generation --- model-based predictive control --- robustness --- worst-case scenario --- min–max optimisation --- intraday forecasting --- Gaussian process regression --- machine learning --- off-grid system --- composite control strategy --- solar photovoltaic panel --- wind turbine --- diesel generator --- energy storage system (ESS) --- synchronous machine (SM) --- permanent magnet brushless DC machine (PMBLDCM) --- power quality improvement --- n/a --- PLO's profit --- min-max optimisation

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The Special Issue Distributed Energy Resources Management 2018 includes 13 papers, and is a continuation of the Special Issue Distributed Energy Resources Management. The success of the previous edition shows the unquestionable relevance of distributed energy resources in the operation of power and energy systems at both the distribution level and at the wider power system level. Improving the management of distributed energy resources makes it possible to accommodate the higher penetration of intermittent distributed generation and electric vehicle charging. Demand response programs, namely the ones with a distributed nature, allow the consumers to contribute to the increased system efficiency while receiving benefits. This book addresses the management of distributed energy resources, with a focus on methods and techniques to achieve an optimized operation, in order 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.

n/a --- virtual power plant --- bidding strategy --- local flexibility market --- multi-period optimal power flow --- flexibility service --- occupant comfort --- unbalanced networks --- decentralized energy management system --- autonomous control --- optimization --- energy storage --- microgrids --- energy efficiency --- distributed energy --- control system --- DSM --- optimal scheduling --- adaptability --- synergistic optimization strategy --- teaching-learning --- distributed generation --- energy storage system --- stackelberg dynamic game --- IoT (Internet of Things) --- supply and demand --- comprehensive benefits --- distributed generator --- frequency bus-signaling --- active distribution networks --- swarm intelligence --- wind --- multi-agent technology --- solar --- power system management --- fault-tolerant control --- indoor environment quality --- multi-temporal optimal power flow --- multi-agent synergetic estimation --- smart grids --- local energy trading --- active power control --- prosumer --- microgrid --- trade agreements --- healthy building --- smart grid --- nonlinear control --- algorithm design and analysis --- batteries --- droop control --- distributed energy resources --- aggregator --- multi-agent system --- frequency control --- particle swarm optimization --- distribution system operator --- building climate control --- low voltage networks --- demand Response --- clustering --- distributed coordination --- demand-side management --- demand response

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Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue.

Benders’ decomposition --- distributed generation planning (DGP) --- two-stage stochastic mixed-integer linear programming (MILP) --- renewable energy sources (RES) --- micro-grid --- energy management system --- IEC 61850 --- 5G --- LoRa --- multi-agent system --- isolated AC/DC hybrid microgrid --- two-layer consensus method --- dynamic economic dispatch --- distributed hierarchical strategy --- MILP optimization --- allocation --- renewable energy sources --- system modeling --- energy storages --- energy curtailment --- mathematical programming --- small scale distributed generation --- distribution networks --- active power management --- battery degradation --- electric vehicles --- electric vehicles aggregator --- electricity markets --- stochastic programming --- combined economic emission dispatch --- environment-based demand response --- emission constraints --- penalty factor --- weighting update artificial bee colony --- distribution network planning --- energy storage system --- multi-objective optimization --- optimal location --- risk assessment --- flexibility --- distributed energy resources --- distribution system operators --- local services --- system services --- arbitrage --- frequency control