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配电网分布式电源最大并网容量的机会约束评估模型及其转化方法 被引量:18

Chance Constrained DG Capacity Assessment Model and Transforming Method for Distribution Networks
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摘要 分布式可再生能源的广泛接入对配电网的规划与运行产生重大影响,如何准确评估配电网的最大并网能力是一个配电网规划中的重要问题。该问题的最大挑战是在评估模型中如何刻画分布式电源出力的不确定性,并进行有效求解。为此,提出了一种基于机会约束的配电网分布式电源容量评估方法。该方法考虑了分布式电源出力及负荷预测的不确定性,将约束构建为线性机会约束形式。通过假设预测误差服从各个变量的边际分布相互独立、均值为0的概率分布,进一步将该机会约束模型转化为可被有效求解的混合二阶锥规划模型。最后,基于IEEE 33节点配电网络的算例给出了所提出方法的评估结果。基于文中提出的分布式电源容量评估方法在给定约束越限概率下可得到较大容量的接入方案。 Increasing penetration of renewable energy brings a great impact on planning and operation of distribution networks. Accurate evaluation of maximum allowable distributed generation(DG) capacity is an important issue in distribution network planning. The most challenging part of this problem is how to describe DG output uncertainty in evaluation model and solve it effectively. This paper proposes a distribution network DG capacity assessment method based on chance constraints. The method describes the uncertainties of DG and load as stochastic variables, and the assessment model is formulated as a linear chance constrained optimization model. Furthermore, assuming the probabilistic distribution of forecast errors satisfy that its marginal distributions are independent and take zero mean, the chance constrained optimization model is transformed into a second-order cone programming model which can be effectively solved. Finally, numerical tests on IEEE 33-bus distribution network verify its effectiveness. Results show that the method can reach larger DG capacity under given risk rate of chance constraints.
作者 吴素农 于金镒 杨为群 李迎军 朱文广 熊宁 彭莉萍 WU Sunong;YU Jinyi;YANG Weiqun;LI Yingjun;ZHU Wenguang;XIONG Ning;PENG Liping(State Grid Jiangxi Electric Power Company,Nanchang 330077,Jiangxi Province,China;State Grid Institute of Economics and Technology of Jiangxi Electric Power Company,Nanchang 330043,Jiangxi Province,China)
出处 《电网技术》 EI CSCD 北大核心 2018年第11期3691-3697,共7页 Power System Technology
关键词 主动配电网 分布式电源 容量评估 机会约束 active distribution network distributed generation capacity assessment chance constraint
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