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FAST SUBSTATION SERVICE RESTORATION USING INTELLIGENT PETRI-NETS MODELS

机译:使用智能Petri网模型的快速变电站服务恢复

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This paper proposes a new Petri Nets (PNs)knowledge representation scheme to on-line fast achieve the service restoration plan of a substation. In accordance with the practical guidelines and the heuristic rules obtained by interacting with the dispatchers of distribution systems, a PNs model is first built to represent the related knowledge about the task of substation restoration. The PNs model built is then transformed into matrix forms, which are relied on to infer a restoration plan through simple matrix operations. Due to its graphic representation of the heuristic rules and parallel rule-firing manner via matrix operations, the human expertise on restoration can be advantageously expressed and exploited by means of the PNs knowledge-representing approach. The developed system is illustrated on a sample substation and tested on a practical Taiwan Power (Taipower) substation in Tainan City. Flexibility and effectiveness of the PNs model have been verified as a decision support for restoration scheduling.
机译:提出了一种新的Petri网知识表示方案,以在线快速实现变电站的服务恢复计划。根据实践准则和与配电系统的调度员交互获得的启发式规则,首先建立PNs模型来表示有关变电站恢复任务的相关知识。然后,将构建的PNs模型转换为矩阵形式,然后通过简单的矩阵运算来依靠它们来推断恢复计划。由于其启发式规则的图形表示以及通过矩阵运算的并行规则触发方式,因此可以借助PNs知识表示方法来方便地表达和利用人类在恢复方面的专业知识。所开发的系统在一个示例变电站中进行了说明,并在台南市的实际台湾电力(Taipower)变电站中进行了测试。 PNs模型的灵活性和有效性已得到验证,可以作为恢复计划的决策支持。

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