基于场景概率的日前-日内两阶段限流措施优化

章谋成; 林湘宁; 魏繁荣; 黄梓欣; 孙佳航; 曹豪

章谋成,林湘宁,魏繁荣,黄梓欣,孙佳航,曹豪.基于场景概率的日前-日内两阶段限流措施优化[J].电测与仪表,2025,62(12):71-80.
zhangmoucheng,linxiangling,weifanrong,huangzixin,sunjiahang,caohao.Optimization of two-stage day-ahead and intra-day short-circuit current limiting measures based on scenario probability[J].Electrical Measurement & Instrumentation,2025,62(12):71-80.

基于场景概率的日前-日内两阶段限流措施优化

Optimization of two-stage day-ahead and intra-day short-circuit current limiting measures based on scenario probability

DOI：

中文关键词: 新能源短路电流数据-物理联合驱动

英文关键词:renewable energy sources, short-circuit current (SCC), joint data-driven and model-driven methods

基金项目:新型电力系统灰启动基础理论与方法（U22B20106）；电动汽车充电网络广泛接入下的电网跨域攻击监测及防御策略（52107095）

作者中文名	作者英文名	单位
章谋成	zhangmoucheng	三峡大学
林湘宁	linxiangling	华中科技大学
魏繁荣	weifanrong	华中科技大学
黄梓欣	huangzixin	华中科技大学
孙佳航	sunjiahang	三峡大学
曹豪	caohao	三峡大学

摘要点击次数: 7

中文摘要:

短路电流超标现象严重困扰电力系统运行方式制定。当前依据日前预测的最恶劣场景来进行限流决策，以经济性为代价保证安全性。但随着新能源大规模接入，其不确定性导致最恶劣场景可能是一个与正常场景相去甚远的极小概率场景，以之为依据进行限流决策将严重影响经济性。若日前处理较大概率场景，在日内无遗漏地紧急处理极小概率场景则能制定出更具经济性的限流策略。为此，文中提出基于场景概率的日前-日内两阶段限流措施优化框架。以日前-日内综合成本期望最低为原则划分日前和日内处理场景并制定日前限流措施；针对日内紧急限流，提出基于数据-物理联合驱动的短路电流实时预测方法，在日内实时预测并进行紧急限流，以发现并处理极小概率超标场景。仿真结果表明，所提两阶段优化框架具有较好的可行性、安全性和更优的经济性。

英文摘要:

Short-circuit current (SCC) over-limit is becoming increasingly common, seriously troubling the development of power system operation methods. Currently, limiting the SCC is based on the predicted day-ahead worst-case scenario, ensuring safety at the cost of the economy. The decision is reasonable when the start-up mode is more certain. However, with the large-scale connection of renewable energy sources, the uncertainty of their output leads to the worst-case scenario may be a very small probability scenario far from the normal one, and the decision to SCC limiting measures based on this will seriously affect the economics. With the rise of artificial intelligence technology, it has become possible to predict and limit SCC urgently in real-time. Therefore, it is possible to develop more economical and safe flow limiting strategies by handling high probability scenarios in advance and urgently handling low probability scenarios without any omissions within the day. To sum up, this paper proposes a day-ahead and intra-day two-stage SCC limiting measures optimization framework based on scenario probability. Based on the principle of the lowest combined cost expectation of day-ahead and intra-day, we divide day-ahead and intra-day treatment scenarios and formulate day-ahead current limiting measures. For day-ahead emergency current limiting, we propose a real-time prediction method of SCC based on the combined data-driven and model-driven methods to discover and treat very small probability over-limit SCC scenarios. The results show that the proposed two-stage optimization framework has better feasibility, security, and economy.

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