交直流混合配电网多阶段随机优化调度模型  

Multi-stage stochastic optimization dispatch model for AC-DC hybrid distribution power networks

作　　者：裴蕾 卫志农[1] 陈胜[1] 赵景涛[2] 傅强[2] PEI Lei;WEI Zhinong;CHEN Sheng;ZHAO Jingtao;FU Qiang(College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China;NARI Technology Company Limited,Nanjing 211100,China)

机构地区：[1]河海大学能源与电气学院,江苏南京211100 [2]国电南瑞科技股份有限公司,江苏南京211100

出　　处：《电力系统保护与控制》2022年第14期23-32,共10页Power System Protection and Control

基　　金：国家自然科学基金项目资助(U1966205)。

摘　　要：高比例间歇性分布式光伏的接入给交直流混合配电网的运行带来了挑战。当前所提两阶段随机优化调度模型对不确定变量的观测较为粗略,导致配电网实时决策与日前决策偏差较大。鉴于此,提出了基于场景树的交直流混合配电网多阶段随机优化模型。所提模型以日前购电成本、日内调节成本和实时平衡成本之和最小为目标,通过储能装置的充放电功率调节、换流站输出功率调节和需求响应等灵活调节措施,实现了间歇性光伏的就地消纳和系统的削峰填谷。多阶段随机优化模型的日前离散决策变量可随日内和实时阶段的不确定信息改变而自适应调整,更符合实际高比例光伏渗透下交直流混合配电网的运行需求,为其经济灵活运行提供技术支撑。The high proportion of intermittent distributed photovoltaic access brings challenges to the operation of an AC-DC hybrid distribution network.The current two-stage stochastic optimization dispatch model leads to a large deviation between real-time and day-ahead decision-making.This paper presents a multi-stage stochastic optimization model based on a scenario tree.The proposed model aims at minimizing the sum of day-ahead purchase cost,day-ahead adjustment cost and real-time balance cost.The model also realizes photovoltaic absorption and peak load filling through flexible adjustment measures such as energy storage device adjustment,converter station output power adjustment and demand response.The discrete decision variables of the multi-stage stochastic optimization model can be adjusted adaptively with the change of uncertain information in the intra-day and real-time stage.This can meet the operational requirements of an AC-DC hybrid distribution network with a high proportion of PV penetration and provide technical support for its economical and flexible operation.

关 键 词：交直流混合配电网 多阶段决策 随机优化 场景树 分布式光伏 

分 类 号：TM721.3[电气工程—电力系统及自动化] TM73