Reprint

Emerging and Advanced Green Energy Technologies for Sustainable and Resilient Future Grid

Edited by
November 2022
416 pages
  • ISBN978-3-0365-5769-4 (Hardback)
  • ISBN978-3-0365-5770-0 (PDF)

This book is a reprint of the Special Issue Emerging and Advanced Green Energy Technologies for Sustainable and Resilient Future Grid that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

This reprint presents various aspects of the future grid, which is the next generation of the electrical grid and will enable the smart integration of conventional, renewable, and distributed power generation, energy storage, transmission and distribution, and demand management. Renewable energy is crucial in transitioning to a less carbon-intensive economy and a more sustainable energy system. The high penetration and uncertain power outputs of renewable energy pose great challenges to the stable operation of energy systems. The deployment of the smart grid is revolutionary, and also imperative around the world. It involves and deals with multidisciplinary fields such as energy sources, control systems, communications, computational generation, transmission, distribution, customer operations, markets, and service providers. Smart grids are emerging in both developed and developing countries, with the aim of achieving a reliable and secure electricity supply. Smart grids will eventually require standards, policy, and a regulatory framework for successful implementation. This reprint addresses the emerging and advanced green energy technologies for a sustainable and resilient future grid, and  provides a platform to enhance interdisciplinary research and share the most recent ideas.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
islanded mode; microgrid; decentralized control; robust tracking; invariant set; thermal energy storage; parabolic dish; latent heat; phase change material; heat transfer fluid; microgrid; bio-inspired algorithms; wireless sensor network; genetic algorithm; particle swarm optimization; advanced metering infrastructure; blockchain; Ethereum; isolated DC–DC converter; photovoltaics; LLC resonant converter; dual-bridge; wide voltage range; power optimizer; coordinated control; vehicle-to-grid; primary frequency control; secondary frequency control; state of charge; decentralized; Simulink model; microgrid; dimensionality reduction; simple linear regression; multiple linear regression; polynomial regression; load forecasting; VSC (voltage source converter); PLL (Phase-Locked Loop); weak grid; small signal stability; eigenvalues; demand-side management; low-power consumer electronic appliances; low-voltage distribution system; non-intrusive identification of appliance usage patterns; power quality; smart home; true power factor; total harmonic distortion; renewable energy sources; microgrid; energy management system; communication technologies; microgrid standards; third-order sliding mode control; asynchronous generators; variable speed dual-rotor wind turbine; direct field-oriented control; integral-proportional; transformer; internal fault currents; magnetic inrush currents; extended Kalman filter (EKF) algorithm; harmonic estimation; DC microgrid; fault; cluster; DC/DC converter; fault current limiter (FCL); multi-objective; renewable energy; profit-based scheduling; Equilibrium Optimizer; smart grid; campus microgrid; batteries; prosumer market; energy management system; distributed generation; renewable energy resources; energy storage system; distributed energy resources; demand response; microgrid; load clustering techniques; sizing methodologies; communication technologies; digital signal processing; green buildings; total harmonic distortion; spectral analysis; spectral kurtosis; energy storage system; life-cycle cost; optimal scheduling; reinforcement learning; enabling technologies; energy community; smart meter; nanogrid; platform; power cloud; n/a