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Multiobjective Load Dispatch for Coal-Fired Power Plants under Renewable-Energy Accommodation Based on a Nondominated-Sorting Grey Wolf Optimizer Algorithm

Author

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  • Yue Cao

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Tao Li

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Tianyu He

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Yuwei Wei

    (Guangxi Special Equipment Inspection and Research Institute, Nanning 530219, China)

  • Ming Li

    (Changyuan Hanchuan Power Generation Company Limited, China Energy Investment Corporation, Xiaogan 431600, China)

  • Fengqi Si

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

Coal-fired power plants are widely used to achieve a power balance in grids with renewable energy, which leads to new requirements for speediness in load dispatch. This paper presents a nondominated-sorting grey wolf optimizer algorithm (NSGWO) for the multiobjective load dispatch of coal-fired power plants that employed efficient nondominated sorting, a reference-point selection strategy, and a simulated binary crossover operator. The optimization results of the benchmark functions indicated that the NSGWO algorithm had a better accuracy and a better distribution than the traditional multiobjective grey wolf optimizer algorithm. Regarding the load dispatch of economy, environmental protection, and speediness strategies, the NSGWO had the best performance of all the simulated algorithms. The optimal-compromise solutions of the economy and speediness strategies of the NSGWO algorithm had a good distribution, which elucidated that this novel algorithm was favorable to allowing coal-fired power plants to accommodate renewable energy.

Suggested Citation

  • Yue Cao & Tao Li & Tianyu He & Yuwei Wei & Ming Li & Fengqi Si, 2022. "Multiobjective Load Dispatch for Coal-Fired Power Plants under Renewable-Energy Accommodation Based on a Nondominated-Sorting Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 15(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2915-:d:794817
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    References listed on IDEAS

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