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Finding optimal solutions for an economic load dispatch problem considering thermal, solar and wind power plants by using salp swarm and northern goshawk optimization algorithms

Minh Duc Cuong Nguyen, Ta Minh Cuong, Anh Tang Nguyen

Abstract


This paper proposes a new variant of the traditional economic load dispatch (NELD) problem. Unlike traditional economic load dispatch (TELD), generating sources in NELD are diversified with different types, including thermal, wind, and solar power plants. The reduction of total fuel consumption from thermal power plants is the main objective of this study. The Salp swarm algorithm and Northern Goshawk optimization are utilized to find the optimal solution for NELD. The evaluation of the real performance of these optimization tools is tested on the power system with twenty thermal power plants, two wind power plants, and one solar power plant. In addition, the power system must satisfy load demand variation within 24 hours per day as in practice. Northern Goshawk optimization outperforms Salp swarm optimization on all comparison criteria with no violation of involving constraints and minimum total fuel consumption. Therefore, Northern goshawk optimization is highly recommended for solving the NELD problem

Keywords


New variant of traditional economic load dispatch (NELD); Salp swarm algorithm; Northern goshawk optimization; thermal generator; renewable energies; load demand variation

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References


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