| 引用本文: | 颜炯,万涛,李浩松,等.计及不确定性因素的配电网网架规划方法[J].电力系统保护与控制,2017,45(18):76-81.[点击复制] |
| YAN Jiong,WAN Tao,LI Haosong,et al.Distribution network planning considering the uncertainties[J].Power System Protection and Control,2017,45(18):76-81[点击复制] |
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| 计及不确定性因素的配电网网架规划方法 |
| 颜炯,万涛,李浩松,杨明,郑旭,瞿少成,李金,康泰峰 |
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| (国网湖北省电力公司经济技术研究院，湖北 武汉 430077;北京国网信通埃森哲信息技术有限公司， 北京 100000;华中师范大学，湖北 武汉 430079) |
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| 摘要: |
| 为了在配电网网络架构规划中计及分布式电源出力与负荷不确定性的影响，提出了模糊规划法。通过三角模糊数表述分布式电源(Distributed Generation, DG)出力的不确定性，并利用可信度理论构建配电网网架规划模型；提出了一种快速生成树算法形成待规划系统的初始网络架构，再利用遗传算法对初始网架进行调整寻优，最终得到系统最优网架。通过算例仿真验证了该方法的有效性。 |
| 关键词: 配电网 网架规划 分布式电源 不确定性 模糊数 |
| DOI：10.7667/PSPC161452 |
| 投稿时间：2016-09-05修订日期：2016-11-30 |
| 基金项目:国家自然科学基金项目(61074046，F030107);国网湖北省电力公司科技项目(52153814000D) |
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| Distribution network planning considering the uncertainties |
| YAN Jiong,WAN Tao,LI Haosong,YANG Ming,ZHENG Xu,QU Shaocheng,LI Jin,KANG Taifeng |
| (State Grid HBEPC Economic &Technology Research Institute, Wuhan 430077, China;State Grid Information & Telecommunication Accenture Information Technology Co., Ltd., Beijing 100000, China;Central China Normal University, Wuhan 430079, China) |
| Abstract: |
| In order to consider the impacts of distributed generation (DG) output and load uncertainty in distribution network planning, a fuzzy programming approach is proposed. Triangular fuzzy numbers are used to describe the uncertainty of DG. Based on credibility theory, the network planning model of distribution network is established. Moreover, a rapid spanning tree algorithm is presented to form the initial network configuration of under-planning system. Genetic algorithm (GA) is then used to adjust and optimize the initial network configuration and finally get the optimal one. The effectiveness of the proposed approach is proved through case simulation. This work is supported by National Natural Science Foundation of China (No. 61074046 and No. F030107) and Science and Technology Project of Hubei Electric Power Company (No. 52153814000D). |
| Key words: distribution system network planning distributed generation (DG) uncertainty fuzzy |
