摘要
随着电动汽车等柔性负荷的快速发展,园区运营商作为柔性负荷参与需求响应的引导者起着重要作用。为此,有效协调园区运营商定价策略与多柔性负荷的用电行为显得尤为重要。针对上述问题,提出一种园区运营商-柔性负荷层面的日前-日内两阶段调峰优化模型。在日前阶段基于主从博弈建立以园区运营商削峰填谷并兼顾自身利益的上层优化模型,下层建立以柔性负荷用电费用最小的下层优化模型;日内为应对预测偏差,基于模型预测控制对柔性负荷进行合理调控以平滑电网联络线跟踪日前调峰计划。最后通过算例分析,所建立两阶段优化模型可实现园区运营商与柔性负荷间的共赢,结果可为多柔性负荷参与需求响应提供重要借鉴。
With the rapid development of flexible loads such as electric vehicles,park operators play an important role as guides for flexible loads to participate in demand response.Therefore,it is particularly important to effectively coordinate the pricing strategy of park operators and the power consumption behavior of multiple flexible loads.To solve the above problems,a two-stage peak shaving optimization model of day-ahead and intraday peak regulation at the park operator flexible load level is proposed.In the day ahead stage,based on the master-slave game,the upper optimization model is established with the park operators cutting peaks and flling valleys and taking into account their own interests,and the lower optimization model with the minimum power consumption cost of flexible load is established at the lower level.In order to cope with the forecast deviation,the model predictive control is applied to adjust the flexible load reasonably in order to smooth the tie line and track the peak load regulation plan.Finally,through the example analysis,the two-stage optimization model can realize the win-win between park operators and flexible loads,and the results can provide an important reference for multi-flexible loads to participate in demand response.
作者
陈鑫
林永君
白青飞
李静
CHEN Xin;LIN Yong-jun;BAI Qing-fei;LI Jing(North China Electric Power University,Baoding Hebei 071000,China)
出处
《计算机仿真》
北大核心
2023年第5期477-485,共9页
Computer Simulation
基金
国家自然科学基金资助项目(52077078)。
关键词
主从博弈
模型预测控制
柔性负荷
削峰填谷
Master-slave game
Model predictive control
Flexible load
Peak cutting and valley flling
