基于改进量子遗传算法的虚拟电厂在多时间尺度下参与AGC优化调度  

Optimal Scheduling of Virtual Power Plant Participating in AGC Based on Improved Quantum Genetic Algorithm on Multi-Time Scale

作　　者：闫鹏 曾四鸣 李铁成 卢俊达 杨少波 胡雪凯 张波[2] YAN Peng;ZENG Siming;LI Tiecheng;LU Junda;YANG Shaobo;HU Xuekai;ZHANG Bo(State Grid Hebei Electric Power Research Institute,Shijiazhuang 050021,Hebei,China;Hebei Key Laboratory of Distributed Energy Storage and Micro-Grid(North China Electric Power University),Baoding 071003,Hebei,China)

机构地区：[1]国网河北省电力有限公司电力科学研究院,河北石家庄050021 [2]河北省分布式储能与微网重点实验室(华北电力大学),河北保定071003

出　　处：《电网与清洁能源》2023年第3期23-32,共10页Power System and Clean Energy

基　　金：河北省自然科学基金项目(E2019502119);国网河北电力科技成本项目(kjcb2021-017)。

摘　　要：介绍虚拟电厂参与AGC调频控制过程,建模分析新能源机组及柔性负荷出力特性;提出一种计及传统发电机组、新能源发电机组、储能系统和柔性负荷的虚拟电厂参与AGC调频多时间尺度优化调度方法,使得虚拟电厂整体在多时间尺度下参与AGC调频收益最大、综合调频效果最佳。研究一种引入量子交叉和量子变异的改进量子遗传算法,并与传统AGC分配方法及自适应遗传算法进行仿真对比,结果表明所提算法具有收敛速度快、全局寻优能力强的优点。In this paper,the virtual power plant′s participation in the AGC frequency regulation control process is introduced,and the output characteristics of new energy units and flexible loads are modeled and analyzed.A multi-time scale optimal scheduling method is proposed for virtual power plants to participate in AGC frequency regulation,taking traditional generating units,new energy generating units,energy storage system and flexible load into account,so that the virtual power plants as a whole can participate in AGC frequency regulation on multiple time scales with the greatest benefits and the best comprehensive frequency regulation effect.An improved quantum genetic algorithm incorporating quantum crossover and quantum mutation is studied and compared with the traditional AGC allocation method and adaptive genetic algorithm.The results show that the proposed algorithm has the advantages of fast convergence speed and strong global optimization ability.

关 键 词：虚拟电厂 改进量子遗传算法 多时间尺度 AGC 优化调度 

分 类 号：TM73[电气工程—电力系统及自动化]