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Service restoration for distribution network with DGs based on stochastic response surface method

机译:基于随机响应面法的分布式配电网服务恢复

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摘要

In order to deal with the uncertainty of renewable distributed generators (DGs) and load under fault conditions in distribution network, a service restoration method based on stochastic response surface method (SRSM) is proposed. After the input variables are processed by correlation, chaotic second-order polynomials are introduced, and the probability distributions of each state variable are obtained by solving its coefficients. Moreover, network reconfiguration is combined with intending islanding to resolve the service restoration problem in the distribution network. For a network structure that does not satisfy the probability constraint, the load is cut until it is satisfied. In the iterative process of service restoration algorithm, the stochastic response surface method is adopted to deal with the uncertainty, which can maximize power supply recovery of outage areas under the premise of satisfying the probability constraint. The proposed method is applied to the IEEE 33-bus system and TPC 84-bus system for testing. The comparison with other algorithms validates the correctness and effectiveness of the proposed method.
机译:针对配电网故障条件下可再生分布式发电机(DGs)和负荷的不确定性,提出了一种基于随机响应面法(SRSM)的服务恢复方法。在对输入变量进行相关处理后,引入混沌二阶多项式,并通过求解其系数来获得每个状态变量的概率分布。此外,将网络重新配置与预期的孤岛相结合以解决配电网络中的服务恢复问题。对于不满足概率约束的网络结构,将减少负载直到满足。在服务恢复算法的迭代过程中,采用随机响应面法处理不确定性,在满足概率约束的前提下,可以最大限度地提高停电地区的供电恢复能力。将该方法应用于IEEE 33总线系统和TPC 84总线系统进行测试。与其他算法的比较验证了所提方法的正确性和有效性。

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