DOI:10.35833/MPCE.2021.000734 Data-driven Convexification for Frequency Nadir Constraint of Unit Commitment Page view: 5        Net amount: 25 Author: Yukang Shen1, Wenchuan Wu1, Bin Wang1, Yue Yang1, Yi Lin2 Author Affiliation: 1. State Key Laboratory of Power Systems (Department of Electrical Engineering), Tsinghua University, Beijing 100084, China 2. Electric Power Research Institute, Fujian Electric Power Ltd. Company, Fuzhou 350003, China Foundation: This work was supported in part by the S&T Project of State Grid Corporation of China “Learning based Renewable Cluster Control and Coordinated Dispatch” (No. 5100-202199512A-0-5-ZN). Abstract: The increasing penetration of the renewable energy sources brings new challenges to the frequency security of power systems. In order to guarantee the system frequency security, frequency constraints are incorporated into unit commitment (UC) models. Due to the non-convex form of the frequency nadir constraint which makes the frequency constrained UC (FCUC) intractable, this letter proposes a revised support vector machine (SVM) based system parameter separating plane method to convexify it. Based on this data-driven convexification method, we obtain a tractable FCUC model which is formulated as a mixed-integer quadratic programming (MIQP) problem. Case studies indicate that the proposed method can obtain less conservative solution than the existing methods with higher efficiency. Keywords: Unit commitment ; frequency constraint ; support vector machine (SVM) ; data-driven convexification Received:November 02, 2021               Online Time:2023/09/20 View Full Text       Download reader