Application of Bat Algorithm to Reduce Power Loss in Electrical Power Systems

Samson Ademola Adegoke, Yanxia Sun, Zenghui Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The bat algorithm (BA) is a population-based optimization that mimics the echolocation of microbats when looking for prey and avoiding obstacles. BA is a unique algorithm that gives fast convergence and optimum solutions to a problem. Reactive power dispatch (RPD) plays a vital role in the control and operation of the power system and is part of the optimal power flow (OPF) problem. It is formulated as continuous and discrete (i.e., mixed integer nonlinear programming) model. This research involves the application of BA to RPD to reduce power loss (PL) in transmission systems and applied constraints handling (penalty function) to keep it within the operating limits. Also, the optimum control settings are voltage of the generator, reactive power sources, and transformer taps were obtained without violating the limits. The method's performance was demonstrated on standard IEEE New England 39 and 57 node systems. BA can reduce the test systems’ losses to 37.109 MW and 22.304 MW from the initial case of 43.6 MW and 28.46 MW, respectively. The percentage savings of the test systems are 14.94% and 21.63%, respectively, which shows that BA can reduce PL in electrical power systems. The simulation results of BA are compared with the other techniques, and BA outperformed them.

Original languageEnglish
Title of host publicationInternational Conference on Neural Computing for Advanced Applications - 4th International Conference, NCAA 2023, Proceedings
EditorsHaijun Zhang, Yinggen Ke, Yuanyuan Mu, Zhou Wu, Tianyong Hao, Zhao Zhang, Weizhi Meng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages206-219
Number of pages14
ISBN (Print)9789819958436
DOIs
Publication statusPublished - 2023
EventProceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023 - Hefei, China
Duration: 7 Jul 20239 Jul 2023

Publication series

NameCommunications in Computer and Information Science
Volume1869 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceProceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023
Country/TerritoryChina
CityHefei
Period7/07/239/07/23

Keywords

  • Bat algorithm
  • Reactive power dispatch
  • Transmission power loss

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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