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Optimization of Power Generation Costs Through Soft Computing Techniques

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Advances in Electrical and Computer Technologies (ICAECT 2021)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 881))

Abstract

This chapter attempts to use a new evolutionary algorithm called hybrid multi-agent particle swarm optimization (HMAPSO) to solve extremely complex economic load dispatch (ELD) problems with transmission loss and heterogeneous cost curves. The efficiency of this method has been tested successfully on IEEE 14 bus, New England 39 bus and IEEE 118 bus systems. In this proposed method, observation indicates the point which is HMAPSO method and can find more cost-effective load dispatch solutions than the lambda-iteration method (LIM), evolutionary program (EP), genetic algorithm (GA), particle swarm optimization (PSO), bacteria foraging (BF), multi-agent system (MAS), multi-agent particle swarm optimization (MAPSO), particle swirl algorithm (PSA) and hybrid particle swarm optimization (HPSO). In addition, compared with other methods, the calculation time is relatively uniform and shorter.

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Author information

Authors and Affiliations

  1. Department of EEE, Saranathan College of Engineering, Trichy, India

    M. V. Suganyadevi

  2. Department of EEE, Loyola-ICAM College of Engineering & Technology, Chennai, India

    A. R. Danila Shirly

Authors
  1. M. V. Suganyadevi
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  2. A. R. Danila Shirly
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Corresponding author

Correspondence to M. V. Suganyadevi .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, SVS College of Engineering, Coimbatore, India

    Thangaprakash Sengodan

  2. Department of Electronics and Communication Engineering, Kuwait College of Science and Technology, Safat, Kuwait

    M. Murugappan

  3. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Sanjay Misra

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Suganyadevi, M.V., Danila Shirly, A.R. (2022). Optimization of Power Generation Costs Through Soft Computing Techniques. In: Sengodan, T., Murugappan, M., Misra, S. (eds) Advances in Electrical and Computer Technologies. ICAECT 2021. Lecture Notes in Electrical Engineering, vol 881. Springer, Singapore. https://doi.org/10.1007/978-981-19-1111-8_71

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  • DOI: https://doi.org/10.1007/978-981-19-1111-8_71

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1110-1

  • Online ISBN: 978-981-19-1111-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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