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Optimal Scheduling of Regional Combined Heat and Power System Based on Improved MFO Algorithm

Author

Listed:
  • Fan Wang

    (Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, School of Electrical & Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Xiang Liao

    (Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, School of Electrical & Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Na Fang

    (Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, School of Electrical & Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Zhiqiang Jiang

    (School of Civil & Hydraulic Engineering, Huazhong University of Science & Technology, Wuhan 430068, China)

Abstract

Due to the inflexibility of cogeneration power plants and the uncertainty of wind power production, the excess power of the distribution network brings challenges to the power grid operation. This paper introduced an improved moth-flame optimization algorithm to meet the challenge of energy complementary dispatching. The proposed algorithm adopts three effective strategies, namely inertia weight, unified initialization, and the spiral position update strategy, which maintains a strong global search ability and a potent compromise between global and local search. The effectiveness of the proposed method was evaluated by benchmark functions. Furthermore, the proposed method was applied to combine heat and power system operation problems and economic dispatch in light load and wind power unpredictability. In order to verify the robustness of the algorithm and solve the complex constraints of power systems under extreme conditions, three different cases had been discussed. The experimental findings indicate that the proposed algorithm shows better performances in terms of convergence speed, ability to escape from a local optimum solution, and population diversity maintenance under different complexity conditions of engineering problems.

Suggested Citation

  • Fan Wang & Xiang Liao & Na Fang & Zhiqiang Jiang, 2022. "Optimal Scheduling of Regional Combined Heat and Power System Based on Improved MFO Algorithm," Energies, MDPI, vol. 15(9), pages 1-30, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3410-:d:810169
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    References listed on IDEAS

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    1. Yanhong Luo & Zhenxing Yin & Dongsheng Yang & Bowen Zhou, 2019. "A New Wind Power Accommodation Strategy for Combined Heat and Power System Based on Bi-Directional Conversion," Energies, MDPI, vol. 12(13), pages 1-16, June.
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    3. Jiang, Zhiqiang & Li, Rongbo & Li, Anqiang & Ji, Changming, 2018. "Runoff forecast uncertainty considered load adjustment model of cascade hydropower stations and its application," Energy, Elsevier, vol. 158(C), pages 693-708.
    4. Elaziz, Mohamed Abd & Ewees, Ahmed A. & Ibrahim, Rehab Ali & Lu, Songfeng, 2020. "Opposition-based moth-flame optimization improved by differential evolution for feature selection," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 168(C), pages 48-75.
    5. Zhiqiang Jiang & Peibing Song & Xiang Liao, 2020. "Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference," Energies, MDPI, vol. 13(20), pages 1-20, October.
    6. Motevasel, Mehdi & Seifi, Ali Reza & Niknam, Taher, 2013. "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, Elsevier, vol. 51(C), pages 123-136.
    7. Huawen Sheng & Chunquan Li & Hanming Wang & Zeyuan Yan & Yin Xiong & Zhenting Cao & Qianying Kuang, 2019. "Parameters Extraction of Photovoltaic Models Using an Improved Moth-Flame Optimization," Energies, MDPI, vol. 12(18), pages 1-23, September.
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    Cited by:

    1. Mohammad H. Nadimi-Shahraki & Hoda Zamani & Ali Fatahi & Seyedali Mirjalili, 2023. "MFO-SFR: An Enhanced Moth-Flame Optimization Algorithm Using an Effective Stagnation Finding and Replacing Strategy," Mathematics, MDPI, vol. 11(4), pages 1-28, February.

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