胡鹏, 艾欣, 吴界辰, 陈逸飞, 郭良松, 李庆彪, 张润恩. 基于节点电价的主动配电网日前-实时阻塞管理[J]. 现代电力, 2020, 37(3): 230-237. DOI: 10.19725/j.cnki.1007-2322.2019.0374
引用本文: 胡鹏, 艾欣, 吴界辰, 陈逸飞, 郭良松, 李庆彪, 张润恩. 基于节点电价的主动配电网日前-实时阻塞管理[J]. 现代电力, 2020, 37(3): 230-237. DOI: 10.19725/j.cnki.1007-2322.2019.0374
HU Peng, AI Xin, WU Jiechen, CHEN Yifei, GUO Liangsong, LI Qingbiao, ZHANG Runen. Day-ahead and Real-time Congestion Management of Active Distribution Network Based on Distribution Location Marginal Price[J]. Modern Electric Power, 2020, 37(3): 230-237. DOI: 10.19725/j.cnki.1007-2322.2019.0374
Citation: HU Peng, AI Xin, WU Jiechen, CHEN Yifei, GUO Liangsong, LI Qingbiao, ZHANG Runen. Day-ahead and Real-time Congestion Management of Active Distribution Network Based on Distribution Location Marginal Price[J]. Modern Electric Power, 2020, 37(3): 230-237. DOI: 10.19725/j.cnki.1007-2322.2019.0374

基于节点电价的主动配电网日前-实时阻塞管理

Day-ahead and Real-time Congestion Management of Active Distribution Network Based on Distribution Location Marginal Price

  • 摘要: 在主动配电网中分布式资源(distributed energy resources,DERs)渗透率不断上升及电力市场改革不断推进的背景下,高比例DERs引起的线路过载和节点电压越限等网络阻塞现象不容忽视。针对主动配电网的阻塞问题,该文提出基于配电网节点电价(distribution location marginal price,DLMP)的日前-实时阻塞管理模型。在日前阶段,各负荷聚合商(aggregator,Agg)首先预测日前市场电价并收集相关DERs信息,然后配电网管理员在保证用户用电需求的同时使其用电支出最小,并兼顾网络约束制定DLMP发布给Agg,Agg得到日前交易计划;在实时阶段,各Agg更新DERs信息,并根据配电网管理员更新的DLMP重新调整日前交易产生的偏差。最后,通过IEEE33节点算例进行仿真验证,结果表明提出的阻塞管理模型可以有效解决主动配电网在日前和实时两阶段的阻塞问题,保证线路容量及节点电压在允许的安全范围内。

     

    Abstract: Under the background of increasing distributed energy resources raising in the active distribution network and the advancing power market reform, the network congestion caused by high proportion of DERs cannot be ignored. To deal with this problem, this paper proposed a day-ahead and real-time congestion management model based on the distribution location marginal price (DLMP). In the day-ahead stage, the aggregators firstly predict the day-ahead market price and collect relative DERs information. Secondly, the distribution system operator (DSO) receives data from aggregators and distributes DLMPs to all aggregators with the goal of minimizing the consumed energy expenditure while meeting the network constraints. Finally aggregators make the day-ahead transaction scheme based on DLMP. In the real-time stage, the aggregators regulate the deviation of the day-ahead transaction with the more accurate prediction of the DERs based on the updating DLMP from DSO. Finally, the simulations were implemented by using the IEEE 33 bus system, and the results show that the proposed congestion management model can effectively solve the network congestion of the active distribution network both in the day-ahead and real-time stages, which avoids line overloading and node voltage beyond the limitations.ons.

     

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