Multi-Objective Reactive Power Optimization Based on Improved Particle Swarm Optimization With ε-Greedy Strategy and Pareto Archive Algorithm

This paper proposes combining an improved particle swarm optimization and Pareto archive algorithm to solve the multi-objective reactive power optimization problem. The idea of <inline-formula> <tex-math notation="LaTeX">\varepsilon </tex-math></inline-formula> -gre...

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Veröffentlicht in:	IEEE access Jg. 9; S. 65650 - 65659
Hauptverfasser:	Liu, Xiaofei, Zhang, Pei, Fang, Hui, Zhou, Yinglu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Archives & records Genetic algorithms Heuristic algorithms Iterative methods Linear programming Multi-objective reactive power optimization Multiple objective analysis Optimization Pareto archive algorithm Pareto optimization Pareto optimum Particle swarm optimization Power system stability Reactive power Sorting algorithms voltage control ε-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">greedy strategy
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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