10.1007/s40095-017-0233-9

Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic

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  • Bahman Taheri*1,
  • Gholamreza Aghajani2,
  • Mahsa Sedaghat2,
  1. Department of Electrical Engineering, Bilesavar Branch, Islamic Azad University, Bilesavar, IR
  2. Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, IR
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Published in Issue 2017-04-12

How to Cite

Taheri, B., Aghajani, G., & Sedaghat, M. (2017). Economic dispatch in a power system considering environmental pollution using a multi-objective particle swarm optimization algorithm based on the Pareto criterion and fuzzy logic. International Journal of Energy and Environmental Engineering, 8(2 (June 2017). https://doi.org/10.1007/s40095-017-0233-9
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Abstract

Abstract In recent years, many studies have studied economic dispatch problem in power systems. However, most of them have not considered the environmental pollution caused by fossil fuels. In this study, the use of an evolutionary search algorithm called multi-objective particle swarm optimization algorithm is proposed to solve the economic dispatch problem in power systems while considering environmental pollution. The proposed method is validated in terms of its accuracy and convergence speed based on comparisons with the results obtained using the classic nonlinear programming method. The proposed strategy is applied to a realistic power system under various conditions. Overall, six generating units are investigated along the corresponding constraints. The results obtained reveal that costs of operation and pollution with/without power loss are reduced significantly by the proposed approach. Obtained results show a good compromise can be established between two contradicting functions of exploitation cost and pollution by optimizing them simultaneously. Values of these function without considering their loss is 46,112.09 $/h and 682.32 kg/h, respectively. And if losses are considered, these values would be 48,381.09 $/h and 726.52 kg/h, respectively.

Keywords

  • Economic dispatch,
  • Multi-objective optimization,
  • Multi-objective particle swarm optimization (MOPSO) algorithm,
  • Pareto criterion,
  • Power plant environmental pollution
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