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Optimal Distributed Generation Placement and Size under Uncertainties and Contingencies in Active Distribution Networks

机译:在主动分配网络中不确定性和突发事件下的最佳分布生成放置和大小

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In order to describe the uncertainties, such as distributed generation (DG) output, load fluctuation and contingencies, in active distribution networks comprehensively, this paper proposes an optimal DG planning model in the presence of active management schemes. A correlated sample matrix of wind speed, illumination intensity and load is generated using quasi Monte Carlo simulation and singular value decomposition. Fuzzy C-means clustering is utilized to classify scenarios of the sample matrix to improve the computation efficiency of optimal power flow. The optimal allocation model is mathematically formulated as a bi-level programming problem, which is solved by a hybrid algorithm combining dynamic niche differential evolution and primal-dual interior point algorithms. The solution provides the trade-off between system economy and security. Case study demonstrates the effectiveness of those techniques.
机译:为了描述在主动分配网络中的分布式发电(DG)输出,负载波动和抗困境的不确定性,本文提出了在存在主动管理方案的情况下最佳的DG计划模型。使用Quasi Monte Carlo仿真和奇异值分解产生有关样品矩阵的风速,照明强度和负载。模糊C-Means群集用于对样品矩阵的场景进行分类,提高最佳功率流的计算效率。最佳分配模型在数学上配制成双级编程问题,其通过组合动态利基差分演化和原始 - 双内部点算法组合的混合算法来解决。该解决方案提供了系统经济与安全之间的权衡。案例研究表明这些技术的有效性。

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