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

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.

Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications

“…Overpowering the distribution network is a problem for grid operations because cogeneration plants are inflexible, and wind energy production is unpredictable. To overcome these issues, the authors [ 106 ] developed an improved MFO algorithm with the help of three strategies: inertia weight, unified initialization, and the spiral position update strategy. The effectiveness of the newly developed algorithm has been applied in combining heat and power system operation problems and economic dispatch in light load and wind power unpredictability.…”