基于极限场景的两阶段含分布式电源的配网无功优化

doi:10.19595/j.cnki.1000-6753.tces.L70664

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摘要在能源危机大背景和相关政策的引导下,以风电、光伏为代表的分布式可再生能源并网近年来发展迅速。然而风电、光伏等电源出力的随机性,使得传统的无功优化方法难以适应含有较高比例分布式可再生能源的配电网。针对这一问题,提出一种基于极限场景的两阶段配网无功优化方法,该方法通过极限场景约束形式对随机变量进行处理,在第一阶段决策配电网中不能灵活调节的慢变量取值,保证了在第二阶段中灵活性调节变量能够应对分布式电源的随机性,最终达到系统运行网损最小且最大化消纳清洁能源的目的,兼顾了系统的经济性与鲁棒性。首先建立基于支路潮流的混合整数无功优化模型,然后利用大M法和二阶锥松弛对原有模型进行凸化,最后采用极限场景法对分布式电源进行抽样并决策。最后结合理论分析和仿真分析说明所提方法的有效性与可行性。

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	张艺镨
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关键词 ：分布式新能源, 配网无功优化, 凸优化, 极限场景, 两阶段优化

Abstract：Public awareness of fossil-fuel depletion and policy incentives has emulated the development and deployment of distributed renewable energy sources, such as wind power and solar energy. However, the uncertainties of fluctuating wind power and solar power challenge the traditional methods. In this paper, a two-stage optimization method based on extreme scenarios is proposed for optimal reactive power dispatch in the distribution system. The proposed approach deals with random variables by the extreme scenarios, and determines slow variables associating with the inflexible devices in the system in coordination with those flexible sources. It guarantees the security of system operation, and at the same time it achieves the goal of minimizing the loss and maximizing the renewable integration. The proposed method can be divided into 3 steps. First, the optimal reactive optimization problem is formulated as a mixed integer non-convex nonlinear optimization based on the relaxed branch flow model. Then the big M-approach and conic relaxation are used to convert the original problem into a quadratic programming. Third, the slow variables in the distribution network are decided by sampling the output power of the distributed generation using an extreme scenario method. Theoretical proof and simulation results demonstrate the effectiveness of the proposed method.

Key words： Distributed renewable generation reactive power optimization in distribution network convex optimization extreme scenario two-stage optimization

收稿日期: 2017-04-20 出版日期: 2018-01-31

PACS:

TM71

作者简介: 张艺镨, 男,1994年生,硕士,研究方向为含新能源的电力系统优化运行调度。E-mail: yip_zhang@qq.com;艾小猛, 男,1986年生,博士,研究方向为鲁棒优化理论在电力系统中的应用、可再生能源并网优化运行等方面。E-mail: xiaomengai1986@foxmail.com（通信作者）

引用本文:

张艺镨, 艾小猛, 方家琨, 姚伟, 文劲宇. 基于极限场景的两阶段含分布式电源的配网无功优化[J]. 电工技术学报, 2018, 33(2): 380-389. Zhang Yipu, Ai Xiaomeng, Fang Jiakun, Yao Wei, Wen Jinyu. Two-Stage Reactive Power Optimization for Distribution Network with Distributed Generation Based on Extreme Scenarios. Transactions of China Electrotechnical Society, 2018, 33(2): 380-389.

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