李振坤, 何苗, 苏向敬, 符杨. 基于生物体免疫机制的智能配电网故障恢复方法[J]. 中国电机工程学报, 2021, 41(23): 7924-7936. DOI: 10.13334/j.0258-8013.pcsee.201223
引用本文: 李振坤, 何苗, 苏向敬, 符杨. 基于生物体免疫机制的智能配电网故障恢复方法[J]. 中国电机工程学报, 2021, 41(23): 7924-7936. DOI: 10.13334/j.0258-8013.pcsee.201223
LI Zhenkun, HE Miao, SU Xiangjing, FU Yang. Smart Distribution Network Fault Recovery Method Based on Biology Immune Mechanism[J]. Proceedings of the CSEE, 2021, 41(23): 7924-7936. DOI: 10.13334/j.0258-8013.pcsee.201223
Citation: LI Zhenkun, HE Miao, SU Xiangjing, FU Yang. Smart Distribution Network Fault Recovery Method Based on Biology Immune Mechanism[J]. Proceedings of the CSEE, 2021, 41(23): 7924-7936. DOI: 10.13334/j.0258-8013.pcsee.201223

基于生物体免疫机制的智能配电网故障恢复方法

Smart Distribution Network Fault Recovery Method Based on Biology Immune Mechanism

  • 摘要: 随着配电网智能化的发展,配电网故障处理的要求也在提高,故障恢复如何做到快速精准有效引起了人们的重视。鉴于生物免疫系统应答迅速、准确、高效,与配电网故障恢复的要求相契合,该文将其与智能配电网相结合,建立基于生物体免疫机制的智能配电网故障恢复方法,为配电网故障后的供电恢复提供一种新思路。首先,该文建立配电网免疫识别模型,利用故障的“电子辞典”识别故障并进行免疫匹配;然后,配对成功的故障状态采用已有方案恢复供电,即二次免疫应答,否则通过初次免疫应答模型对故障进行处理,优化计算故障恢复的决策方案,并将该方案进行免疫记忆。同时,为了提高系统二次免疫应答的比例,提出通过免疫记忆模型去构建预想事故集,仿真建立高风险故障的预恢复方案,扩充免疫记忆细胞库。最后,针对一改造后的实际配电网,给出其预想事故集及决策集,对故障进行仿真匹配,给出不同时段故障后的恢复方案,并与采用传统恢复决策方法时的可靠性指标进行对比分析。

     

    Abstract: With the development of smart distribution network, the requirements of fault recovery are also improving. How to achieve rapid, accurate and effective fault recovery has attracted people's attention. In view of the rapid, accurate and efficient response of biological immune system matching the requirements of fault recovery, this paper combines it with smart distribution network to establish smart distribution network fault recovery method based on biology immune mechanism, which provides a new idea for power supply after failure. Firstly, the "electronic dictionary" is used to describe the characteristics of faults and immune matching is carried out. Then, the existing scheme is used to restore the power supply for the successfully paired fault. Otherwise, the fault is processed by the first immune response model. At the same time, in order to improve the proportion of secondary immune response, the immune memory model is proposed to construct contingency set, and the pre recovery scheme of high-risk fault is simulated to expand the immune memory cell bank. Finally, a modified actual distribution network is simulated, the contingency set and decision set are given, a real fault is simulated and matched, and the recovery schemes after failure in different periods are given. The reliability index of the traditional recovery decision method is compared and analyzed with this method.

     

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