Reprint

Challenges and Research Trends of Renewable Energy Power System

Edited by
June 2023
248 pages
  • ISBN978-3-0365-7528-5 (Hardback)
  • ISBN978-3-0365-7529-2 (PDF)

This book is a reprint of the Special Issue Challenges and Research Trends of Renewable Energy Power System that was published in

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

This reprint focuses on the current research trends in renewable energy sources (RESs) penetrated modern power systems (PSs). Various operational, power quality and stability issues and their solutions are discussed comprehensively in RESs integrated PSs. The topics of attraction include islanding detection and prevention, frequency regulation, pricing based multi-objective optimal scheduling, day-ahead load demand forecasting, advancing intelligent and robust optimization techniques based control strategies.

Format
  • Hardback
License
© by the authors
Keywords
distributed generation (DG); backward and forward sweep (BFS) method; passive islanding detection; islanding detection time; islanding prevention; V-F (voltage–frequency) index; non-detection zone (NDZ); Renewable Energy Systems (RES); solar PV; wind power; Double-Fed Induction Generators (DFIG); Area Control Error (ACE); Fuzzy Type-2 (FT2); Fractional Order PID (FOPID); available transfer capacity; deregulated power system; TCSC; teaching learning based optimization; congestion; ac power transfer distribution factor; LFC; ACE; fuzzy logic; PSO; FACTS; RFB; UPFC; induction generator; wind energy; inverters; stationary reference frame; synchronous reference frame; pitch angle; converters; grid; STATCOM; virtual inertia emulation; virtual synchronous generator (VSG); inverter interfaced distributed generation (IIDG); sliding mode control (SMC); super-twisting algorithm (STALG); super-twisting control (STC); virtual power plant; renewable energy resources; black widow optimization; multi-objective optimal scheduling; peak valley pricing; ANN training algorithms; cluster microgrids; load demand forecasting; machine learning methods; urban energy community; intelligent control; irrigation system; fuzzy logic; automatic irrigation control system; arithmetic optimization algorithm (AOA); conventional hysteresis band current controller (CHCC); improved arithmetic optimization algorithm (IAOA); offset hysteresis band current controller (OFHCC); particle swarm optimization (PSO); demand response strategies; demand side management; distributed energy resources; battery energy storage systems; distribution generation; operational challenges; optimization techniques