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A comprehensive review of soft computing algorithms for optimal generation scheduling
Author(s) -
Lolla Phani Raghav,
Rangu Seshu Kumar,
Dhenuvakonda Koteswara Raju,
Singh Arvind R.
Publication year - 2021
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.5759
Subject(s) - computer science , economic dispatch , network topology , electric power system , heuristic , scheduling (production processes) , optimization problem , operations research , distributed computing , mathematical optimization , management science , engineering , power (physics) , algorithm , artificial intelligence , mathematics , physics , quantum mechanics , operating system
Summary Strategic planning for optimal operation of modern power systems has always been a significant task to satisfy the techno‐social aspects in the sustainable energy scenario. In the light of restructured power systems and decentralized generation, the economic dispatch (ED) problem has remained the utmost important economic assignment for the network operators. The conventional techniques have failed to address the nonlinear characteristics of generators for solving the practical ED problem. The complications identified in the literature are valve point loading, prohibited operating zones, multiple fuels, ramp rate limits, and spinning reserve. Therefore, a diverse range of traditional and modern optimization techniques have been adopted to tackle those complexities and nonlinearities. With the recent advancements in centralized optimization techniques, several research works were reported in the past decade to accomplish better results. This review paper endeavors to cover the pioneering research on centralized approaches as well as present‐day research trends on decentralized and distributed approaches by focusing on the economic aspects. First, a detailed survey of several deterministic, stochastic, nature‐inspired, and meta‐heuristic based centralized approaches for solving the ED problem is reviewed. A brief analysis based on the performance evaluation of centralized algorithms on six standard test systems is presented. Then, the recent literature on decentralized and distributed optimization approach and the consensus protocols with respect to various network topologies is briefly reviewed. The prime objective of this review is to summarize the centralized, decentralized, and distributed approaches to solve the classic dispatch, dynamic dispatch, economic emission dispatch, and multi‐area ED problems.