基于黑猩猩算法的风光蓄火联合发电系统优化调度

Optimal Scheduling of Wind Solar Thermal Storage Combined PowerGeneration System Based on Chimp Algorithm

为了提高风光蓄火联合发电系统的经济效益,降低弃风弃光量,以联合发电系统的收益最大为优化目标,全面考虑系统约束条件,建立了风光蓄火联合发电系统优化调度模型,采用黑猩猩优化算法(Chimp Optimization Algorithm,COA)对调度模型进行求解。将该模型用于我国西南地区某联合发电系统的优化调度,结果表明,通过COA算法对联合发电系统的优化,增加了风电、光伏的出力,这样既提高了联合发电系统的经济效益,同时又减少了对环境的影响。将COA算法与GWO算法、PSO算法和GA算法进行比对,其收敛代数、计算时间、最大发电收益均优于其他对比算法,验证了COA算法在对联合发电系统优化调度时的优势。

In order to improve the economic benefit of wind solar thermal storage combined power generation system,reduce the amount of wind and solar energy abandoned,to yield maximum revenue of the combined power generation system,based on fully considering the system constraints,it established the model of wind solar thermal storage combined power generation system,and used the COA(Chimp Optimization Algorithm)to solve the scheduling model.The model was applied to the optimal scheduling of a combined power generation system in southwest China.The results showed that the COA could increase the output of wind and light,improve the economic benefit of the combined power generation system,and reduce the impact on the environment.By comparing COA with GWO,PSO and GA,its convergence algebra,calculation time and maximum generation income were superior to other comparison algorithms,which verified the advantages of COA in the optimal scheduling of combined power generation system.