基于自适应时段划分的含氢微能网中长期变分辨率调度  

Medium-and Long-term Variable-resolution Scheduling of Micro-energy Networks with Hydrogen Based on Adaptive Time Division

作　　者：刘洪[1] 惠之洲 张鹏[1] 李俊锴 张世达 杨白洁 LIU Hong;HUI Zhizhou;ZHANG Peng;LI Junkai;ZHANG Shida;YANG Baijie(Key Laboratory of Ministry of Education on Smart Power Grids(Tianjin University),Tianjin 300072,China)

机构地区：[1]智能电网教育部重点实验室(天津大学),天津市300072

出　　处：《电力系统自动化》2025年第4期178-187,共10页Automation of Electric Power Systems

基　　金：天津市科技计划资助项目(22JCZDJC00820)。

摘　　要：传统微网中长期调度在日能量平衡时难以计及储能的能量循环过程,不仅可能导致日能量平衡方案无法支撑日内初始时段的储能充放策略,而且无法适应电氢相互转换过程的高损耗。为此,文中提出自适应时段划分与变分辨率相结合的两阶段随机优化调度方法。首先,针对不确定性“近小远大”问题,建立基于改进鞅模型的源荷出力特性模型。其次,构建含氢微能网中长期调度的两阶段变分辨率随机优化架构,在阶段1提出基于深度神经网络的自适应时段划分方法,在阶段2以系统运行费用最低为目标,结合分时段机会约束分别建立粗、细分辨率随机优化调度模型,后者基于前者决策的储氢设备荷电状态安排各小时的设备出力计划,并提出基于采样法的求解方案。最后,通过算例仿真验证了所提模型和方法的有效性。The medium-and long-term scheduling of traditional microgrids is difficult to take into account the energy cycle process of energy storage during the daily energy balance,which may not only lead to the inability of the daily energy balancing scheme to support the charging and discharging strategy of energy storage during the initial period of the day,but also cannot adapt to the high loss of the electricity-hydrogen conversion process.Therefore,a two-stage stochastic optimal scheduling method combining adaptive period division and variable-resolution is proposed.Firstly,for the“near small and far big”problem of uncertainty,a model of source-load output characteristics based on the modified martingale model is established.Secondly,a two-stage variableresolution stochastic optimization architecture for the medium-and long-term scheduling of micro-energy networks with hydrogen is constructed.At stage one,an adaptive time division method based on deep neural network is proposed.At stage two,with the goal of minimizing the system operation costs and combining with time-segment chance constraints,the stochastic optimal scheduling models with coarse and fine resolutions are established,respectively.The latter arranges the hourly equipment output plans based on the state of charge of hydrogen storage equipment decided by the former,and a solution scheme based on sampling method is proposed.Finally,the effectiveness of the proposed model and method is verified through numerical simulations.

关 键 词：自适应时段划分 中长期调度 鞅模型 不确定性 分时段机会约束 微能网 

分 类 号：TM73[电气工程—电力系统及自动化]