基于改进北方苍鹰算法的冷热电联供型微电网优化调度  

Optimization scheduling of combined cooling,heat and powermicrogrids using the improved northern goshawk optimization algorithm

作　　者：陈广 刘佩 徐达 刘炬 刘闯 CHEN Guang;LIU Pei;XU Da;LIU Ju;LIU Chuang(Jingmen Power Supply Company,State Grid Hubei Electric Power Co.,Ltd.,Jingmen Hubei 448000,China;China University of Geosciences,Wuhan Hubei 430074,China)

机构地区：[1]国网湖北省电力有限公司荆门供电公司,湖北荆门448000 [2]中国地质大学,湖北武汉430074

出　　处：《宁夏电力》2025年第1期15-22,共8页Ningxia Electric Power

基　　金：中国博士后科学基金会资助项目(2021M692992)。

摘　　要：为了实现冷热电联供(combined cooling,heat and power,CCHP)型微电网的经济运行,以综合成本最小为目标函数构建了CCHP型微电网优化调度模型。利用佳点集初始化和柯西高斯变异两种方法对北方苍鹰优化算法(northern goshawk optimization,NGO)进行改进,得到了寻优性能更强的改进北方苍鹰优化算法(improved northern goshawk optimization,INGO)。采用INGO算法对CCHP型微电网优化调度模型进行求解,算例分析结果表明,INGO算法求解的最小综合成本为10835.94元,计算时间为7.75 s,在求解精度和计算时间方面优于其他对比算法。根据INGO算法获得的调度方案,系统内各设备出力合理,既保证了清洁能源的充分利用,也提高了CCHP型微电网运行经济性。An optimization scheduling model is designed to minimize overall costs for the efficient operation of combined cooling,heat and power(CCHP)microgrids.The northern goshawk optimization(NGO)algorithm is enhanced using two techniques:optimal point set initialization and Cauchy-Gaussian mutation.These adjustments augment the method′s effectiveness,yielding the improved northern goshawk optimization(INGO)algorithm with stronger optimization performance.The INGO method is used to address the optimal scheduling model for the CCHP microgrid.The case study findings indicate that the INGO algorithm achieves a minimum comprehensive cost of 10,835.94 yuan,with a computation duration of 7.75 s.This performance surpasses that of other comparative algorithms regarding solution correctness and computational efficiency.The scheduling plan generated by the INGO algorithm produces satisfactory outputs from all system devices,guaranteeing optimal utilization of clean energy and improving the economic efficiency of the CCHP microgrid.

关 键 词：微电网 冷热电联供 优化调度 改进北方苍鹰算法 综合成本 

分 类 号：TM73[电气工程—电力系统及自动化]