STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Thermal Engineering and Applications

Reduction Of Total Electricity Generation Cost For Complicated Power Systems Considering Renewable Energy Sources By Using A Sea Horse Optimizer

  1. Tran Trung Hieu
  2. Nguyen Van Yen

Abstract

This paper focuses on solving the economic load dispatch (ELD) problem by incorporating the presence of wind and solar power plants alongside conventional thermal power plants (THs). Particle swarm optimization (PSO) and Sea horse optimizer (SHO) are applied to solve the problem with the main objective function of minimizing the total electricity generation cost (TEGC). SHO is a novel meta-heuristic method recently proposed, while PSO is one of the classical meta-heuristic methods proposed approximately three decades ago. The two applied methods are tested on the power system with twenty thermal power plants, one wind and one solar power plant. The results obtained by the two applied methods indicate that SHO is completely superior to PSO in all comparison criteria. Specifically, in terms of minimum, average, and maximum cost values, SHO obtains better values than those of PSO. Moreover, SHO also shows itself to be much more reliable than PSO by reporting a lower standard deviation than PSO. By evaluating this evidence, SHO is acknowledged as the powerful computing method to deal with ELD problems, which considers the presence of both wind and solar energy.

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