分时电价响应下园区微电网日前优化调度策略  

Day-ahead Optimal Scheduling Strategy of Park Microgrid Under the Time-of-use Response

作　　者：皮琳雯 虞莉娟[1] 苏义鑫[1] PI Linwen;YU Lijuan;SU Yixin(School of Automation,Wuhan University of Technology,Wuhan 430070,China)

机构地区：[1]武汉理工大学自动化学院,湖北武汉430070

出　　处：《数字制造科学》2023年第4期302-308,共7页

基　　金：湖北省重点研发计划资助项目(2020BAB128)

摘　　要：以园区微电网PMG为研究背景,从日前这一时间尺度出发,建立以PMG日运行成本最小为目标的优化调度模型。根据PMG内可中断负荷预测曲线划分时段,对分时电价TOU进行调整,得出优化后的TOU曲线。通过电价激励用户侧调整部分负荷的用电时段,降低负荷峰谷差,降低购电成本;在调度过程中,PMG与主网通过联络线互联,进行电力交易,使PMG获得收益,进一步提高PMG运行的经济性。将所建立的PMG单目标优化调度模型用灰狼算法求解。仿真结果表明,该日前优化调度模型可有效降低PMG负荷峰谷差,同时提高微电网运行的经济性,验证了该日前优化调度策略的合理性。Based on the park microgrid(PMG)context,this study establishes an optimal scheduling model aimed at minimizing the daily operation cost of PMG from a day-ahead perspective.Segments are divided according to the interruptible load forecast curve within the PMG,leading to an adjustment in the time of use(TOU)price policy,and the optimized TOU curve is derived.Through this policy,the customer side is incentivized to adjust the time of use of some loads to reduce the peak-to-valley load difference and lower the cost of power purchase;during the dispatching process,the PMG is interconnected with the main network through the contact line for power trading,thus enabling the PMG to gain revenue and further improving the economic efficiency of PMG operation.The established PMG single-objective optimal dispatching model is solved by the gray wolf algorithm.The simulation results show that this day-ahead optimal dispatching model can reduce the PMG load peak-to-valley difference while improving the economic performance of PMG operation,validating the rationality of this day-ahead optimal dispatching strategy.

关 键 词：分时电价 园区微电网 日前优化调度 联络线交易 单目标优化 

分 类 号：TM73[电气工程—电力系统及自动化]