摘要
针对多能微网的自治运行需求,基于长短周期混合储能(氢储能、电储能和热储能)提出周前-日前-实时多能微网能量-功率匹配滚动优化方法。一方面,通过长周期(周前)能量平衡模型与短周期(日前-实时)功率平衡模型滚动优化,应对可再生能源与负荷长时间尺度预测误差较大的问题。另一方面,采用基于数据驱动的两阶段分布鲁棒优化模型刻画日内源荷双侧不确定性,综合1-范数和∞-范数约束不确定性概率分布置信集合,在保障多能微网运行鲁棒性的同时避免了运行方案的保守性。同时,日前模型的第2阶段问题可以分解为多个小规模的子问题,并可通过列与约束生成算法并行处理,无须进行复杂的对偶计算。最后,算例分析结果验证了所提模型与算法的有效性。
For the autonomous operation demand of multi-energy microgrid,a rolling optimization method of energy-power matching for pre-week/day-ahead/real-time multi-energy microgrid is proposed based on long short-term hybrid energy storage(hydrogen storage,electric storage and thermal storage).On one hand,the rolling optimization of the long-term(week-ahead) energy balance model and the short-term(day-ahead and real-time) power balance model addresses the problem of large errors in the long-time-scale prediction of renewable energy and load.On the other hand,a data-driven two-stage distributionally robust optimization model is used to portray the intra-day source-load bilateral uncertainty.The 1-norm and ∞-norm are comprehensively used to constrain the uncertainty probability distribution confidence sets for ensuring the robustness of the multi-energy microgrid operation while avoiding the conservatism of the operation scheme.At the same time,the second-stage problem of the day-ahead model can be decomposed into multiple small-scale subproblems and can be processed in parallel by the column-and-constraint generation algorithm without complex pairwise computation.Finally,the arithmetic case analysis results verify the effectiveness of the proposed model and algorithm.
作者
赵波
王文博
陈哲
罗冰洋
李志浩
汪湘晋
ZHAO Bo;WANG Wenbo;CHEN Zhe;LUO Bingyang;LI Zhihao;WANG Xiangjin(Electric Power Research Institute of State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310014,China;School of Automation,Wuhan University of Technology,Wuhan 430070,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2023年第16期22-33,共12页
Automation of Electric Power Systems
基金
国家自然科学基金面上项目(51877039)。
关键词
长短周期混合储能
多能微网
能量-功率匹配
分布鲁棒优化
long short-term hybrid energy storage
multi-energy microgrid
energy-power matching
distributionally robust optimization
