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2022 | OriginalPaper | Chapter

17. QUasi-Affine TRansformation Evolution Algorithm for Optimal Power Flow of Integrated Electrical Network Combining Thermal Power with Wind Power

Authors : Jianpo Li, Min Gao, Shu-Chuan Chu, Geng-Chen Li, Jeng-Shyang Pan

Published in: Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Publisher: Springer Singapore

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Abstract

With the development of electric power industry, it is of great technical and economic significance to introduce the optimal power flow (OPF) calculation into the economic analysis of electric power market, which can not be realized by the traditional power flow calculation. At present, many researchers have applied evolutionary algorithms to the calculation of optimal power flow. QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm is a new evolutionary algorithm, combined with the OPF model of power market, which has high efficiency and significance for the economic analysis of power market. In this paper, the minimization of generation cost and active power loss is taken as the objective function, and QUATRE is selected as the optimization tool to study the OPF. In this paper, the simulation experiment of this problem is carried out, and compared with Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Moth Swarm Algorithm (MSA). Through the analysis of the experimental results, it can be seen that QUATRE is superior to other algorithms in terms of power generation cost, active power loss and CPU time.

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previous chapter An QUasi-Affine TRansformation Evolution (QUATRE) Algorithm for Job-Shop Scheduling Problem by Mixing Different Strategies
next chapter Hybrid Optimization Algorithm Based on QUATRE and ABC Algorithms
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Metadata
Title
QUasi-Affine TRansformation Evolution Algorithm for Optimal Power Flow of Integrated Electrical Network Combining Thermal Power with Wind Power
Authors
Jianpo Li
Min Gao
Shu-Chuan Chu
Geng-Chen Li
Jeng-Shyang Pan
Copyright Year
2022
Publisher
Springer Singapore
Book
Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Print ISBN: 978-981-16-4038-4

Electronic ISBN: 978-981-16-4039-1

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-4039-1_17

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