分布式能源2025，Vol.10Issue(5)：30-40,11.DOI:10.16513/j.2096-2185.DE.25100030
考虑源荷不确定性的智能楼宇共享储能混合博弈优化配置
Hybrid Game Optimization Allocation of Shared Energy Storage in Smart Buildings Considering Source-Load Uncertainty
摘要
Abstract
In response to the supply-demand imbalance faced by intelligent buildings under the dual uncertainties of photovoltaic output on the source side and electricity demand on the load side,this study aims to reduce energy storage investment and electricity costs while enhancing the economic viability and robustness of shared energy storage systems.To achieve this goal,we develop a bi-level optimization model for shared energy storage based on hybrid game theory.In this model,energy storage operators and building users form a leader-follower game relationship;operators act as leaders setting internal transaction prices while users respond as followers through demand response strategies.Additionally,cooperative game theory is employed among buildings to fairly allocate costs using bilateral Shapley value methods.The uncertainty in source-load dynamics is characterized by constructing fuzzy sets for photovoltaic output using Wasserstein distance and incorporating conditional value at risk(CVaR)to depict investment risks arising from load fluctuations.The Karush-Kuhn-Tucker(KKT)conditions are utilized to transform the bi-level model into a single-layer mixed-integer linear programming problem for solution.Simulation results based on an intelligent building cluster in Jiangsu demonstrate that the proposed strategy effectively reduces redundant energy storage capacity by 12.3％and lowers average electricity costs across buildings by 8.7％,while simultaneously increasing operator profits and shortening payback periods for investments.Compared with traditional robust optimization methods and deterministic approaches,our method significantly enhances economic performance without compromising system robustness.The proposed hybrid game optimization strategy can collaboratively address dual uncertainties in sources and loads,facilitating efficient utilization of shared energy storage resources while achieving mutual benefits for all parties involved.This approach provides an effective pathway toward low-carbon operational efficiency for clusters of intelligent buildings.关键词
智能楼宇/混合博弈/共享储能/需求响应/双边ShapleyKey words
intelligent buildings/hybrid game/shared energy storage/demand response/bilateral Shapley分类
能源与动力引用本文复制引用
张宸,吴栋良,王开圣,雷霞,杨宁,孙枭柯..考虑源荷不确定性的智能楼宇共享储能混合博弈优化配置[J].分布式能源,2025,10(5):30-40,11.基金项目
国网江苏省电力有限公司科技项目(J2023174)This work is supported by Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.(J2023174) （J2023174）
