| 引用本文: | 王守相,张齐,王瀚,舒欣.高可再生能源渗透率下的区域多微网系统优化规划方法[J].电力自动化设备,2018,(12): |
| WANG Shouxiang,ZHANG Qi,WANG Han,SHU Xin.Optimal planning method for regional multi-microgrid system with high renewable energy penetration[J].Electric Power Automation Equipment,2018,(12): |
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| 摘要: |
| 高可再生能源渗透率下区域内多个微网之间存在相互支援的可能性，故将微网互联构成区域多微网系统，并通过优化配置区域多微网系统中各微网的分布式电源和储能，将有可能提升微网的经济性。为此，提出了一种高可再生能源渗透率下的区域多微网系统优化规划方法，以区域多微网系统年化综合收益最大化为目标，同时考虑了可再生能源渗透率的要求和各微网之间的相互功率支援，采用免疫遗传算法对各微网内的分布式电源和储能进行优化配置。以IEEE 33节点系统为例，得到了在多种高可再生能源渗透率下的区域多微网系统及各微网的年化综合收益；与未组成区域多微网系统的情形相比较，证实了组成区域多微网系统能提升微网经济性；与微网内只有单一类型的分布式电源情形相比较，证实了合理配置各类分布式电源能提升微网经济性。 |
| 关键词: 高可再生能源渗透率 区域多微网系统 分布式电源 储能 免疫遗传算法 优化规划 |
| DOI：10.16081/j.issn.1006-6047.2018.12.005 |
| 分类号:TM715 |
| 基金项目:国家高技术研究发展计划(863 计划)项目(2014-AA052003)；国家电网公司科技项目(52153217000F) |
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| Optimal planning method for regional multi-microgrid system with high renewable energy penetration |
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WANG Shouxiang1, ZHANG Qi1, WANG Han1, SHU Xin2
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1.Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China;2.State Grid Hubei Electric Power Company, Wuhan 430077, China
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| Abstract: |
| Considering the fact that nearby microgrids can potentially support each other, a RMMS(Regional Multi-Microgrid System) is built, and an optimal allocation of DGs(Distributed Generators) and energy storages in RMMS is presented, which may contribute to an improved RMMS economic performance. An optimal planning method for RMMS with high renewable energy penetration is proposed, which maximizes the annual total profits and employs the immune genetic algorithm to obtain an optimal configuration of DGs and energy storages with the consideration of the requirements from RMMS renewable energy penetration and mutual power support between microgrids. The IEEE 33-node system is taken as an example to obtain the annual total profits of each microgrid and RMMS with several penetration levels of renewable energy sources. Test results verify that the establishment of RMMS provides additional economic benefits of these microgrids. Moreover, it also proves that the configuration of various types of DGs improves the economic performance of these microgrids compared with the systems with single type of DGs. |
| Key words: high renewable energy penetration regional multi-microgrid system distributed power generation energy storages immune genetic algorithm optimal planning |
