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Economic Load Dispatch: A Holistic Review on Modern Bio-inspired Optimization Techniques

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Proceedings of the International Conference on Computational Intelligence and Sustainable Technologies

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

In power system analysis, economic load dispatch (ELD) is a basic optimization challenge. Over the years, the ELD problems have been resolved with a large range of optimization strategies. Many researchers have reviewed AI techniques in their past literatures. However, newly discovered bio-inspired techniques are yet to be explored particularly in power system. This paper discusses some of the recently developed bio-inspired algorithms and their application in solving combined economic emission dispatch problem. From the comparative analysis provided in this paper, it can be inferred that these bio-inspired optimization techniques prove to be most competitive and successful in solving CEED problems.

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Authors and Affiliations

  1. Department of Electrical Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, 462003, India

    Akriti Agrawal, Priyanka Paliwal & Tripta Thakur

Authors
  1. Akriti Agrawal
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  2. Priyanka Paliwal
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  3. Tripta Thakur
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Editor information

Editors and Affiliations

  1. Department of Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

  2. Department of Civil Engineering, JIS College of Engineering, Nadia, West Bengal, India

    Debasish Das

  3. Department of Electrical and Electronics Engineering, National Institute of Technology Sikkim, Ravangla, Sikkim, India

    Anjan Kumar Ray

  4. School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

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Agrawal, A., Paliwal, P., Thakur, T. (2022). Economic Load Dispatch: A Holistic Review on Modern Bio-inspired Optimization Techniques. In: Das, K.N., Das, D., Ray, A.K., Suganthan, P.N. (eds) Proceedings of the International Conference on Computational Intelligence and Sustainable Technologies. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6893-7_45

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