考虑分时电价和最大暂态频率偏移的储能机会约束优化配置  

Chance-constrained Optimal Configuration for Energy Storage System Considering Time-of-use Price and Maximum Transient Frequency Deviation

作　　者：曹永吉 吴秋伟 张恒旭[3] 李常刚[3] CAO Yongji;WU Qiuwei;ZHANG Hengxu;LI Changgang(Center for Electric Power and Energy,Department of Electrical Engineering,Technical University of Denmark,Lyngby 2800,Denmark;Tsinghua-Berkeley Shenzhen Institute,Tsinghua Shenzhen International Graduate School,Tsinghua University,Shenzhen 518055,China;Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University),Jinan 250061,China)

机构地区：[1]丹麦科技大学电气工程系电力与能源中心,丹麦灵比2800 [2]清华大学深圳国际研究生院清华-伯克利深圳学院,广东省深圳市518055 [3]电网智能化调度与控制教育部重点实验室(山东大学),山东省济南市250061

出　　处：《电力系统自动化》2023年第2期61-68,共8页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(52177096);山东省自然科学基金资助项目(ZR2021QE133)。

摘　　要：针对可再生能源规模化接入电网引起的频率稳定控制资源减少的问题,提出一种考虑分时电价和最大暂态频率偏移(MTFD)的储能系统(ESS)机会约束优化配置方案。首先,建立含ESS的扩展系统频率响应模型,估计预想事故下的频率动态响应特征,采用基于最大仿射函数的分段线性化方法构造MTFD约束;其次,考虑预想事故发生的不确定性,构建以投资成本最小和峰谷套利收益最大为目标的ESS容量机会约束优化模型;然后,利用线性加权方法和基于蒙特卡洛模拟的非线性递减惯性权重粒子群优化算法求解,以确定最优的ESS容量;最后,通过算例分析验证了所提方法的有效性。In order to compensate the decreasing frequency stability control resource caused by the large-scale integration of the renewable energy in the power system, a chance-constrained optimal configuration scheme considering the time-of-use price and the maximum transient frequency deviation(MTFD)is proposed for the energy storage system(ESS). Firstly, an extended system frequency response model is established to estimate the frequency dynamic response characteristics under the predefined contingency, from which the constraints of MTFD are extracted by the max-affine function based piecewise linearization method.Secondly, taking into account the uncertainty of contingencies, a chance-constrained optimization model is built to optimize the capacity of the ESS, with the objective of minimizing the investment cost and maximizing the peak-valley arbitrage income.Thirdly, the linear weighted method and the Monte Carlo-and nonlinear decreasing inertia weight-based particle swarm optimization algorithm are used to attain the optimal capacity of the ESS. Finally, a case study is carried out to validate the effectiveness of the proposed method.

关 键 词：频率稳定 调频能力 储能系统 机会约束优化 分时电价 

分 类 号：TK02[动力工程及工程热物理] TM73[电气工程—电力系统及自动化]