电力建设2024，Vol.45Issue(11)：1-13,13.DOI:10.12204/j.issn.1000-7229.2024.11.001
基于机会约束规划的含多微网主动配电网分布式优化管理
Distributed Optimization Management for Active Distribution Networks with Multiple Microgrids Based on Chance-Constrained Programming
摘要
Abstract
To achieve global stability and the optimal economic cost of a system after integrating multiple microgrids(MG)into a distribution network,this paper proposes a distributed optimization management model for an active distribution network(ADN)with multiple microgrids based on chance-constrained programming.On the microgrid side,the objective is to minimize the operating cost of each microgrid,whereas on the distribution network side,the network loss and new energy consumption of the system are optimized and adjusted.Considering the uncertainty of wind power and photovoltaic power,the modeling of the distribution network with multiple microgrids is solved through analytical target cascading(ATC).Subsequently,the distributed model is equivalently replaced through interactive power,thus decoupling the operation between distribution networks with multiple microgrids and distributed solutions for different entities.While the privacy of each entity is protected,the conservatism of conventional constraints is overcome,and energy is allocated reasonably.The optimization results for different operating conditions of the system were analyzed using chance-constrained programming with various exceedance probabilities.An improved IEEE 33-node system was used for simulation verification.Numerical analysis shows that the distributed optimization model is feasible,and the active distribution network system with multiple microgrids under this model has good economic and operational reliability.关键词
主动配电网/分布式优化模型/机会约束规划/多微网/目标级联法Key words
active distribution network/distributed optimization model/chance-constrained programming/multiple microgrids/analytical target cascading分类
信息技术与安全科学引用本文复制引用
徐文韬,米阳,蔡鹏程,李晓航,贾子昊,李肖可..基于机会约束规划的含多微网主动配电网分布式优化管理[J].电力建设,2024,45(11):1-13,13.基金项目
This work is supported by the National Natural Science Foundation of China(No.52477107),Shanghai Natural Science Foundation(No.22ZR1425500)and State Key Laboratory of Power System Operation and Control(No.SKLD22KM19).国家自然科学基金项目(52477107) （No.52477107）
上海市自然科学基金项目(22ZR1425500) （22ZR1425500）
新型电力系统运行与控制全国重点实验室资助项目(SKLD22KM19) （SKLD22KM19）
