| 引用本文: | 王涛,刘雪飞,郑重,刘芮,习朋,赵阳,张丽洁,苗世洪.基于潮流线性化的分布式发电选址定容新算法[J].电力自动化设备,2020,40(8): |
| WANG Tao,LIU Xuefei,ZHENG Zhong,LIU Rui,XI Peng,ZHAO Yang,ZHANG Lijie,MIAO Shihong.Novel locating and sizing algorithm for distributed generation based on power flow linearization[J].Electric Power Automation Equipment,2020,40(8): |
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| 摘要: |
| 针对现有分布式发电选址定容模型存在的维度高、寻优困难、求解时间长等问题，提出一种基于潮流线性化的分布式发电选址定容方法。在实际配电网运行场景的基础上，综合考虑多利益主体竞争关系，建立计及风光投资商竞争关系的分布式发电选址定容双层规划模型；计及配电网参数特性，利用二阶锥松弛法针对模型非凸潮流约束进行凸松弛，进而将二阶锥非线性形式进行线性化近似，通过卡罗需-库恩-塔克(KKT)条件将下层模型等效转化为上层约束条件，最终将原模型转化为一个多目标线性数学规划模型，极大降低原始模型的求解复杂度。基于某乡镇11节点系统进行算例仿真，结果验证了所提模型及算法的有效性。 |
| 关键词: 分布式发电 选址定容 凸松弛 二阶锥近似 KKT最优性条件 |
| DOI：10.16081/j.epae.202007035 |
| 分类号:TM715 |
| 基金项目: |
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| Novel locating and sizing algorithm for distributed generation based on power flow linearization |
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WANG Tao1, LIU Xuefei1, ZHENG Zhong2, LIU Rui1, XI Peng1, ZHAO Yang1, ZHANG Lijie1, MIAO Shihong2
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1.Economic Research Institute of State Grid Hebei Electric Power Company, Shijiazhuang 050000, China;2.Hubei Electric Power Security and High Efficiency Key Laboratory, State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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| Abstract: |
| Aiming at the problems of existing distributed generation locating and sizing model, such as high dimension, difficult optimization, long solving time, etc.,a locating and sizing method based on power flow linearization is proposed for distributed generation. On the basis of actual operation scenario of distribution network, a bi-level planning model for locating and sizing of distributed generation is built considering the competition relationship between wind and photovoltaic investors. Considering the characteristics of distribution network parameters, the second-order cone relaxation method is used for convex relaxation of non-convex power flow constraints of the model, further linear approximation is carried out for the second-order cone non-linear form. The lower level model is equivalently transformed into the upper level constraints by using KKT(Karojan-Kuhn-Tucker) condition, and the original model is finally transformed into a multi-objective linear mathematical programming model, which reduces the solving complexity of the original model greatly. The case simulation of a 11-bus system of a town is carried out, and the results verify the validity of the proposed model and algorithm. |
| Key words: distributed generation locating and sizing convex relaxation second-order cone approximation KKT optimality condition |
