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Coordinated Control of Active and Reactive Power of Distribution Network with Distributed Photovoltaic Based On Scene Analysis

机译:基于场景分析的分布式光伏配电网有功无功协调控制

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Variables such as distributed generation (DG) output and load demand have randomness and volatility, brings large challenges to operation and control of distribution network. In order to solve this problem, this paper generates multiple scene samples through Latin hypercube sampling (LHS) based on mathematical distribution model of variables, then reduces the scene samples by K-means clustering, typical scenes and the probability of each typical scene are obtained. Considering the adjustable capabilities of distributed photovoltaic (PV) and energy storage system (ESS), a multi-objective optimization model based on scene analysis for coordinated control of active and reactive power in distribution network is established, and the mixed integer nonlinear programming model is solved by second-order cone relaxation (SOCR) technique. Finally, the improved IEEE 33-node system is taken as an example for simulation with results confirming accuracy and rationality of the proposed algorithm.
机译:分布式发电(DG)输出和负载需求等变量具有随机性和波动性,给配电网络的运行和控制带来了巨大挑战。为了解决这个问题,本文基于变量的数学分布模型,通过拉丁超立方体采样(LHS)生成多个场景样本,然后通过K均值聚类对场景样本进行归约,得到典型场景以及每个典型场景的概率。 。考虑分布式光伏(PV)和储能系统(ESS)的可调节能力,建立了基于场景分析的配电网有功和无功协调控制的多目标优化模型,并建立了混合整数非线性规划模型。通过二阶锥松弛(SOCR)技术解决。最后,以改进的IEEE 33节点系统为例进行仿真,结果证实了所提算法的准确性和合理性。

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