重庆理工大学学报2024，Vol.38Issue(1)：281-289,9.DOI:10.3969/j.issn.1674-8425(z).2024.01.031
采用改进北方苍鹰算法的微电网优化调度研究
Research on optimal scheduling of microgrid using improved Northern Goshawk algorithm
摘要
Abstract
The microgrid system normally consists of a variety of distributed power sources.To cut the operating cost of the microgrid,intelligent algorithms are often employed to dispatch the microgrid.Intelligent algorithms are prone to fall into local optimal solutions when solving microgrid scheduling models,resulting in poor accuracy.Therefore,based on the Northern Goshawk algorithm,this paper proposes a hybrid strategy improved Northern Goshawk algorithm(HNGO),which uses reverse learning,Metropolies criterion and adaptive T-distribution variation to enhance its accuracy.Meanwhile,a demand response model considering the output characteristics of renewable energy is built,so that the load curve is closer to the output curve of renewable energy.Then,a microgrid optimization scheduling model with the lowest daily operating cost is established,and HNGO is used to find the solution.Our simulation results show the proposed algorithm achieves accuracy,and our proposed demand response model significantly reduces fuel costs.关键词
北方苍鹰算法/反向学习/模拟退火算法/自适应t分布变异/需求响应Key words
Northern Goshawk algorithm/reverse learning/simulated annealing algorithm/adaptive t distribution variation/demand response分类
信息技术与安全科学引用本文复制引用
陈将宏,王羲沐,李伟亮,李雪莲,袁腾..采用改进北方苍鹰算法的微电网优化调度研究[J].重庆理工大学学报,2024,38(1):281-289,9.基金项目
国家自然科学基金项目(52107108) （52107108）
