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A Two-stage Stochastic Optimization Approach for Distribution Network with Load Control

机译:负荷控制的配电网两阶段随机优化方法

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With the extensive access of distributed energy resources (DER) and the development of load control technology, the distribution network is gradually becoming more and more initiative, and the economy of power grid can be effectively improved through reasonable scheduling. For this purpose, a two-stage stochastic optimization approach for distribution network with load control is established. The scenario analysis is used to characterize the uncertainty of DER. The first stage of optimization generates a day-ahead power purchase curve and load adjustment curves and calculates the corresponding costs; In the second stage, the mathematic expectation of the difference between the actual purchased electricity in each scenario and the day-ahead purchased electricity is calculated to obtain the reserve costs. The mathematical nature of the model is a large-scale nonlinear mixed integer programming problem, which is difficult to solve. By using the second-order cone (SOC) relaxation technique, the above model can be transformed into a mixed integer second-order cone programming (MISOCP) form, which can be solved effectively. Finally, the simulation analysis of the custom IEEE 14-bus system is carried out to verify the effectiveness of the proposed model.
机译:随着分布式能源的广泛使用和负荷控制技术的发展,配电网络正变得越来越主动,通过合理的调度可以有效地提高电网的经济性。为此,建立了带有负荷控制的配电网络的两阶段随机优化方法。情景分析用于表征DER的不确定性。优化的第一阶段将生成日前购电曲线和负载调整曲线,并计算相应的成本;在第二阶段,计算每种情况下的实际购电与日间购电之间的差异的数学期望,以获得储备成本。该模型的数学性质是一个大型非线性混合整数规划问题,难以解决。通过使用二阶锥(SOC)松弛技术,可以将上述模型转换为混合整数二阶锥规划(MISOCP)形式,可以有效地解决该问题。最后,对定制的IEEE 14总线系统进行了仿真分析,以验证所提出模型的有效性。

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