| 引用本文: | 谢 俊,王 璐,傅旭华,边巧燕,辛焕海,甘德强.考虑风电功率概率分布不确定性的含风电配电网无功规划方法[J].电力自动化设备,2016,36(6): |
| XIE Jun,WANG Lu,FU Xuhua,BIAN Qiaoyan,XIN Huanhai,GAN Deqiang.Reactive power planning with consideration of wind power probability distribution uncertainty for distribution network[J].Electric Power Automation Equipment,2016,36(6): |
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| 摘要: |
| 由于风电功率预测的局限性，难以准确而有效地刻画风电功率的概率分布函数，提出考虑风电功率概率分布不确定性的含风电配电网无功规划方法。该方法可有效应用于风电概率分布集合中的任意分布情况，在一定概率约束下保证配电网的安全运行要求，同时最小化配电网网损和无功设备投资成本之和。采用概率分布鲁棒机会约束模型描述含风电的配电网无功规划问题，根据潮流平衡等式分离节点电压和支路功率约束中的随机向量，根据条件风险价值（CVaR）的物理意义构建关于节点电压约束和支路功率约束的CVaR模型，利用对偶优化、Schur补和S-lemma的性质将该模型转化为确定性的双线性矩阵不等式（BMI）问题。采用基于BMI优化的免疫粒子群算法求解该问题。改进的IEEE 33节点配电系统仿真结果验证了所提无功规划方法的可行性和有效性。 |
| 关键词: 配电网 风电 无功规划 不确定性 概率分布鲁棒 条件风险价值 双线性矩阵不等式 |
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| 基金项目:国家自然科学基金资助项目（51207074）；国家电网公司重点科技项目（dz71-13-045）；国网浙江省电力公司科技项目（5211JY15001Q） |
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| Reactive power planning with consideration of wind power probability distribution uncertainty for distribution network |
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XIE Jun1, WANG Lu1, FU Xuhua2, BIAN Qiaoyan2, XIN Huanhai3, GAN Deqiang3
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1.College of Automation，Nanjing University of Posts and Telecommunications，Nanjing 210023，China;2.State Grid Zhejiang Electric Power Company，Hangzhou 310007，China;3.College of Electrical Engineering，Zhejiang University，Hangzhou 310027，China
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| Abstract: |
| Since the wind power probability distribution function could not be described accurately based on the wind power forecast，a method of reactive power planning with the consideration of wind power probability distribution uncertainty is proposed for the distribution network with wind power，which，effectively suitable for any distribution pattern in the wind power probability distribution set，minimizes the sum of power loss and reactive-power equipment investment while ensures the safe operation of distribution network with the constraints of a certain probability. The distributional robust chance constraint model is applied to describe the reactive-power planning of distribution network，the random vectors in the constraints of node voltage and branch power are separated according to the power-flow balance equation，and the CVaR （Conditional Value at Risk） model is built according to its physical significance for the constraints of node voltage and branch power. The dual optimization，Schur supplement and S-lemma are adopted to convert the distributional robust chance constraint model into a determined BMI（Bi-linear Matrix Inequality），which is solved by the immune particle swarm optimization algorithm based on BMI optimization. The simulative results for the modified IEEE 33-bus distribution network verify the feasibility and effectiveness of the proposed method. |
| Key words: distribution network wind power reactive power planning uncertainty probability distributional robust conditional value at risk bi-linear matrix inequality |
