孙俊杰,胡姝博,袁鹏,张庭齐,贾祺,刘宛菘
SUN Junjie,HU Shubo,YUAN Peng,ZHANG Tingqi,JIA Qi,LIU Wansong

• 1:国网辽宁省电力有限公司电力科学研究院

摘要(Abstract)：

针对现有优化调度方法无法满足非预期全场景可行性的问题，提出考虑极端非预期时序场景的日前优化调度方法，构建包含调度计划和调度预案的优化调度模型。首先，通过置信区间将考虑时空相关性的时序多场景分为正常场景集和极端场景集，按照源荷预测误差的相关系数对极端时序场景集进行分类，并根据源荷偏差以及系统备用风险筛选出各类中的高风险场景。然后，以不同时段系统正、负备用之和最大为目标得到典型正常场景的日前最优调度计划，在此基础上，对典型极端场景进行优化求解得到调度预案，通过修正调度计划解决部分极端场景无可行解的问题。实际电网的应用案例表明，所提的日前调度优化方法不仅可以兼顾调度决策的鲁棒性和经济性，还可以充分挖掘极端场景下柔性负荷的削峰填谷作用。
Existing optimal scheduling methods cannot cover all unanticipated scenarios. To overcome this limitation, this paper proposes an optimal day-ahead scheduling method that considers extreme, unanticipated and dynamic-temporal scenarios. An optimal scheduling model incorporating both a scheduling plan and a contingency plan is developed. First, the dynamic-temporal scenarios that account for spatiotemporal correlation is divided into a normal scenario set and an extreme scenario set using confidence intervals. The dynamic-temporal scenario set is classified according to the correlation coefficients of source-load forecast errors, and the high-risk scenarios within each category are identified based on source-load deviations and reserve risks of power system. Next, the total system reserves, including both positive and negative reserves, across different time periods are maximized to derive an optimal day-ahead scheduling plan for typical normal scenarios. Furthermore, the typical extreme scenarios are optimized to generate a contingency plan, with adjustments to the scheduling plan applied to resolve cases where some extreme scenarios have no feasible solution. An application case in an actual power grid demonstrates that the proposed method not only preserves the robustness and economic efficiency of scheduling decisions but also fully exploits the peak shaving and valley filling potential of flexible loads under extreme scenarios.

关键词(KeyWords)： 源荷不确定性;时空相关性;时序场景;最优调度计划;调度预案
source-load uncertainty;spatiotemporal correlation;dynamic-temporal scenario;optimal scheduling plan;contingency plan

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(U23B20118)

作者(Author): 孙俊杰,胡姝博,袁鹏,张庭齐,贾祺,刘宛菘
SUN Junjie,HU Shubo,YUAN Peng,ZHANG Tingqi,JIA Qi,LIU Wansong

DOI: 10.19585/j.zjdl.202507001

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