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Multi-Objective Bilevel Coordinated Planning of Distributed Generation and Distribution Network Frame Based on Multiscenario Technique Considering Timing Characteristics

机译:基于时序特征的多情景技术的分布式发电与配电网框架多目标双层协调规划

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摘要

This paper presents a novel approach to planning distributed generation (DG) and distribution network frames based on a multiscenario technique. In view of the uncertainties of the load and intermittence of the DG output, the annual timing characteristics are analyzed, and the daily load and output of DG are divided into several typical situations according to respective influence factors. In the target planning year, the uncertain units are simulated using the typical daily forecast values, then the probability models are established considering the forecast errors; finally, multiple scenarios are achieved through Latin hypercube sampling and sample reduction. In view of the interaction of DG and distribution network frames, a bilevel coordinated planning model is proposed, in which the upper level planning is aimed to achieve the integrated optimal decision and the goal of the lower level planning is to comprehensively consider the benefits of DG. Finally, hybrid chaos binary particle swarm optimization based on Pareto set theory and niche sharing is applied to make a nested solving of the model, and the superiority and effectiveness of the proposed model are verified in the IEEE 33-node and 69-node distribution systems as the test cases.
机译:本文提出了一种基于多场景技术来规划分布式发电(DG)和配电网络框架的新颖方法。鉴于负荷的不确定性和分布式发电的间歇性,分析了年度定时特性,并根据各自的影响因素将分布式发电的日负荷和输出分为几种典型情况。在目标计划年度,使用典型的每日预测值模拟不确定的单位,然后考虑预测误差建立概率模型;最后,通过拉丁超立方体采样和样本减少实现了多种方案。针对DG与配电网框架之间的相互作用,提出了一种双层协调规划模型,其中上级规划旨在实现综合的最优决策,下级规划的目标是综合考虑DG的利益。 。最后,应用基于帕累托集理论和小生境共享的混合混沌二进制粒子群算法对该模型进行嵌套求解,并在IEEE 33节点和69节点分配系统中验证了所提模型的优越性和有效性。作为测试用例。

著录项

  • 来源
    《Sustainable Energy, IEEE Transactions on》 |2017年第4期|1415-1429|共15页
  • 作者单位

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Department of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China;

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Department of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China;

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Department of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China;

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Department of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China;

    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, Department of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Power generation planning; Load modeling; Uncertainty; Timing; Distributed power generation;

    机译:发电计划;负荷建模;不确定性;时间安排;分布式发电;

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