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

Fan Wang, Xiang Liao, Na Fang and Zhiqiang Jiang
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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

Energies, 2022, vol. 15, issue 9, 1-30

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.

Keywords: combined heat and power plant; moth-flame optimization; intelligent optimization algorithm; inertial weight; integrated energy system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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