Accelerating Chance-Constrained SCED via Scenario Compression

被引:0
|
作者
Zhang, Qian [1 ]
Xie, Le [1 ]
机构
[1] Harvard University, School of Engineering and Applied Sciences, Cambridge,MA,02138, United States
关键词
Constrained optimization - Risk assessment - Weather forecasting;
D O I
10.1109/TPWRS.2024.3450369
中图分类号
学科分类号
摘要
This paper studies some compression methods to accelerate the scenario-based chance-constrained security-constrained economic dispatch (SCED) problem. In particular, we show that by exclusively employing the vertices after convex hull compression, an equivalent solution can be obtained compared to utilizing the entire scenario set. For other compression methods that might relax the original solution, such as box compression, this paper presents the compression risk validation scheme to assess the risk arising from the sample space. By quantifying the risk associated with compression, decision-makers are empowered to select either solution risk or compression risk as the risk metric, depending on the complexity of specific problems. Numerical examples based on the 118-bus system and synthetic Texas grids compare these two risk metrics. The results also demonstrate the efficiency of compression methods in both problem formulation and solving processes. © 1969-2012 IEEE.
引用
收藏
页码:1880 / 1890
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