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Economic Load Dispatch Incorporating Wind Power Using Hybrid Biogeography-Based Optimization: Salp Swarm Algorithm

Author

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  • Bikram Saha

    (Kalyani Government Engineering College, India)

  • Provas Kumar Roy

    (Kalyani Government Engineering College, India)

  • Barun Mandal

    (Kalyani Government Engineering College, India)

Abstract

This article represents salp swarm algorithm (SSA) for the most favourable operating solution of economic load dispatch (ELD). For making the convergence first along with SSA, another optimization algorithm (i.e., BBO [biogeography;based optimization]) is also used. For lowering the operational cost, wind power is employed with thermal units. SSA is inspired by swarming behaviour of salp, which belongs to salpiside family. Salp possess a special kind of swarm while hunting for food and navigating. The recommended algorithm is executed on two systems of SIX units and 40 units. In both of the cases, load dispatch problem is carried out with renewable sources and also without renewable sources. Individually, BBO, SSA, and hybrid BBO-SSA are applied to all the test systems to justify effectiveness of hybrid BBO-SSA. Obtained results assure the prospective and advantages of recommended algorithm in contrast to algorithms mentioned in the article. Results come out to be very satisfying and reveal that hybrid BBO-SSA is a powerful algorithm to solve ELD problems.

Suggested Citation

  • Bikram Saha & Provas Kumar Roy & Barun Mandal, 2021. "Economic Load Dispatch Incorporating Wind Power Using Hybrid Biogeography-Based Optimization: Salp Swarm Algorithm," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 12(3), pages 54-80, July.
    • Handle: RePEc:igg:jamc00:v:12:y:2021:i:3:p:54-80
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