摘要
针对用户独立决策的储能行为难以发挥共享储能主动性,且负荷预测误差导致共享储能电站制定的日前调度计划有效性和经济性下降的问题,提出一种主动式共享储能社区双层优化调度策略。首先,设计含主动式共享储能的产消者社区架构;其次,构建以共享储能电站为领导者、产消者集群为跟随者的主从博弈决策模型,采用遗传算法求解社区最优日前调度计划;最后,基于拉丁超立方抽样预测日内发电量及负荷,并构建基于模型预测控制的日内滚动调度模型,据此实现发挥共享储能电站主动性的产消者社区日前-日内双层优化调度。实验结果表明,所提模型能有效实现博弈各方利益均衡意义下的最大化,与现有用户决策共享储能相比,储能电站经济收益提升16.3%,充分发挥了共享储能的主动性。
To address the proactivity of shared energy storage undermined by individual user-driven energy storage behavior and the diminished effectiveness and economic efficiency of day-ahead scheduling plans formulated by shared energy storage plants caused by load prediction errors,a bi-level scheduling optimization strategy is proposed for active shared energy storage communities.First,a community structure with prosumers utilizing active shared energy storage is designed.Second,a master-slave game decision-making model is constructed,where the shared energy storage power plant acts as the leader and the prosumer cluster as the follower.A genetic algorithm is used to solve the optimal day-ahead scheduling plan for the communities.Lastly,intra-day power generation and load are predicted by using Latin hypercube sampling,and an intra-day rolling scheduling model based on model predictive control(MPC)is developed.This allows the implementation of bi-level day-ahead and intra-day scheduling optimization for communities with prosumers,which enhances the proactivity of the shared energy storage plant.Experimental results show that the proposed model effectively maximizes the balanced interests of all parties in the game.Compared to that of existing user-driven shared energy storage,the economic return of the energy storage plant increases by 16.3%,which ensures the proactivity of shared energy storage.
作者
金鑫
潘廷哲
王宗义
曹望璋
于鹤洋
JIN Xin;PAN Tingzhe;WANG Zongyi;CAO Wangzhang;YU Heyang(Electric Power Research Institute,CSG,Guangzhou 510530,China)
出处
《电力科学与技术学报》
北大核心
2025年第3期174-183,共10页
Journal of Electric Power Science And Technology
基金
南方电网公司科技项目(ZBKJXM20240185)。
关键词
共享储能
新能源产消者
主从博弈
模型预测控制
双层优化调度
shared energy storage
new energy prosumer
master-slave game
model predictive control
bi-level scheduling optimization
作者简介
通信作者:潘廷哲(1994—),男,硕士,研究员,主要从事智能用电与电力需求侧管理方面的工作,E‑mail:18900220639@163.com。
