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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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This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

History of engineering & technology --- vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

History of engineering & technology --- vacuum tank degasser --- rule extraction --- extreme learning machine --- classification and regression trees --- wind power: wind speed: T–S fuzzy model: forecasting --- linearization --- machine learning --- photovoltaic output power forecasting --- hybrid interval forecasting --- relevance vector machine --- sample entropy --- ensemble empirical mode decomposition --- high permeability renewable energy --- blockchain technology --- energy router --- QoS index of energy flow --- MOPSO algorithm --- scheduling optimization --- Adaptive Neuro-Fuzzy Inference System --- insulator fault forecast --- wavelet packets --- time series forecasting --- power quality --- harmonic parameter --- harmonic responsibility --- monitoring data without phase angle --- parameter estimation --- blockchain --- energy internet --- information security --- forecasting --- clustering --- energy systems --- classification --- integrated energy system --- risk assessment --- component accident set --- vulnerability --- hybrid AC/DC power system --- stochastic optimization --- renewable energy source --- Volterra models --- wind turbine --- maintenance --- fatigue --- power control --- offshore wind farm --- Interfacial tension --- transformer oil parameters --- harmonic impedance --- traction network --- harmonic impedance identification --- linear regression model --- data evolution mechanism --- cast-resin transformers --- abnormal defects --- partial discharge --- pattern recognition --- hierarchical clustering --- decision tree --- industrial mathematics --- inverse problems --- intelligent control --- artificial intelligence --- energy management system --- smart microgrid --- optimization --- Volterra equations --- energy storage --- load leveling --- cyber-physical systems