Efficient Scenario Generation for Chance-Constrained Economic Dispatch Considering Ambient Wind Conditions

作     者：Zhang, Qian Shukla, Apurv Xie, Le 

作者机构：Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA 

出 版 物：《IEEE TRANSACTIONS ON POWER SYSTEMS》 (IEEE Trans Power Syst)

年 卷 期：2024年第39卷第4期

页      面：5969-5980页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：NSF 

主　　题：Scenario generation chance-constrained programming economic dispatch wind power forecasting error scenario approach 

摘      要：Scenario approach is an effective data-driven method for solving chance-constrained optimization while ensuring desired risk guarantees with a finite number of samples. Crucial challenges in deploying this technique in the real world arise due to non-stationarity environments and the absence of appropriate risk-tuning models tailored for the desired application. In this article, we focus on designing efficient scenario generation schemes for economic dispatch in power systems. We propose a novel scenario generation method based on filtering scenarios using ambient wind conditions. These filtered scenarios are deployed incrementally in order to meet desired risk levels while using minimum resources. In order to study the performance of the proposed scheme, we illustrate the procedure on case studies performed for both 24-bus and 118-bus systems with real-world wind power forecasting data. Numerical results suggest that the proposed filter-and-increment scenario generation model leads to a precise and efficient solution for the chance-constrained economic dispatch problem.