分布式能源2025，Vol.10Issue(6)：75-85,11.DOI:10.16513/j.2096-2185.DE.25100113
基于TimeGAN数据驱动的智能楼宇共享储能调度
TimeGAN-Based Data-Driven Scheduling for Shared Energy Storage Systems in Smart Buildings
摘要
Abstract
Shared energy storage can effectively address the issues of low utilization and high costs caused by individual energy storage configurations by regulating resources across multiple regions.To further exploit the potential of shared energy storage in demand-side resources,this paper introduces electric vehicles and ice storage air conditioning,both with flexible energy storage characteristics,to construct a generalized shared energy storage model for the coordinated optimization of energy usage in smart building clusters.In response to the uncertainty of photovoltaic(PV)output on the energy input side,a time generative adversarial networks(TimeGAN)is employed to simulate a large number of PV output scenarios.By combining daily irradiance data,the static and dynamic features of these scenarios are mined,and typical scenarios are identified using K-medoids clustering.Additionally,a tiered carbon trading mechanism is introduced to limit the carbon emissions of the energy system.An optimization scheduling model for smart buildings is established,considering operational costs,carbon emissions,and user comfort,and is solved using CPLEX.Case studies demonstrate that the proposed method can generate high-quality PV output scenarios,improve regional PV consumption rates,and effectively balance user comfort and costs.关键词
时间生成对抗网络(TimeGAN)/场景生成/广义共享储能/智能楼宇/优化调度Key words
time generative adversarial networks(TimeGAN)/scene generation/generalized shared energy storage/smart buildings/optimization scheduling分类
能源科技引用本文复制引用
LI Ruojin,JI Guangjun,YANG Kang,LIU Zehua,WANG Yuyang,WANG Bolun,ZHOU Xia,ZHAO Jie..基于TimeGAN数据驱动的智能楼宇共享储能调度[J].分布式能源,2025,10(6):75-85,11.基金项目
国家自然科学基金项目(5237070785)This work is supported by National Natural Science Foundation of China(5237070785) （5237070785）
