Fast Solution Method for the Large-scale Unit Commitment Problem with Long-term Storage

作     者：Bo Li Chunjie Qin Ruotao Yu Wei Dai Mengjun Shen Ziming Ma Jianxiao Wang 

作者机构：School of Electrical EngineeringGuangxi UniversityNanning 530004China State Grid Sichuan Electric Power CompanyChengdu 610041China National Power Dispatching and Control CenterState Grid Corporation of ChinaBeijing 100031China National Engineering Laboratory for Big Data Analysis and Applications(Peking University)Beijing 100871China 

出 版 物：《Chinese Journal of Electrical Engineering》 (中国电气工程学报（英文）)

年 卷 期：2023年第9卷第3期

页      面：39-49页

核心收录：

学科分类：08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 

基　　金：Supported by the Specific Research Project of Guangxi for Research Bases and Talents (2022AC21257)。 

主　　题：Constraint splitting long-term storage mix-integer programming unit commitment 

摘      要：Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational burden.Herein,an iterative-based fast solution method is proposed to solve the long-term UC with LTS.First,the UC with coupling constraints is split into several sub problems that can be solved in parallel.Second,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling constraints.Third,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the LTS.The price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub problem.Finally,the sub problem with the SOC boundary of the LTS is iteratively solved independently.The proposed method was verified using a modified IEEE 24-bus system.The results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.