电力系统自动化2018，Vol.42Issue(11)：86-93,8.DOI:10.7500/AEPS20171118002
有源配电网分布式电源与智能软开关三层协调规划模型
Tri-level Coordinated Planning Model of Distributed Generator and Intelligent Soft Open Pointfor Active Distribution Network
摘要
Abstract
High-proportion renewable distributed generator (DG) connecting into grid is blocked by the regulating ability deficiency of existing distribution networks.Under the trend of power electronic devices represented by the intelligent soft point (SOP),a tri-level planning model for DG and SOP of active distribution network is proposed to coordinate the benefits for DG operators and distribution companies while considering the combination of system planning and operation optimization in active distribution network.The upper level aims at maximizing the DG operator revenues of unit capacity for DG planning.The middle level is devised to minimize the annual comprehensive cost of distribution companies for SOP planning.The lower level aims at minimizing the operation cost in each scenario to optimize the system operation condition and deciding the DG accommodation capacity back to the upper and middle level.Scenario analysis technique is utilized to deal with the randomness of DG and load and a hybrid algorithm combining genetic algorithm and conic planning is designed to solve the model.Finally, compared with two cases on IEEE 33-node system,which are merely planning DG and successively planning DG and SOP,the result shows that the proposed model has the advantages in coordinating benefits for different stakeholders and improving the feasibility of planning schemes.关键词
有源配电网/分布式电源/智能软开关/多层协调规划/运行优化/分布式电源消纳Key words
active distribution network/distributed generator/intelligent soft open point/multi-level coordinated planning/operation optimization/distributed generator accommodation引用本文复制引用
马丽,薛飞,石季英,秦子健,凌乐陶,杨挺..有源配电网分布式电源与智能软开关三层协调规划模型[J].电力系统自动化,2018,42(11):86-93,8.基金项目
国家重点研发计划资助项目(2017YFB0903000) （2017YFB0903000）
国家自然科学基金资助项目(61571324) （61571324）
天津市自然科学基金重点项目(16JCZDJC30900).This work is supported by National Key R&D Program of China (No.2017YFB0903000),National Natural Science Foundation of China(No.61571324) and Natural Science Foundation of Tianjin(No.16JCZDJC30900). （16JCZDJC30900）
