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FAST SUBSTATION SERVICE RESTORATION USING INTELLIGENT PETRI-NETS MODELS

机译:使用智能Petri-Nets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:本文提出了一种新的Petri网(PNS)知识代表表演方案,在线快速实现变电站的服务恢复计划。根据通过与分发系统的调度仪进行交互获得的实际指导和启发式规则,首先构建PNS模型以表示关于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,依赖于通过简单的矩阵操作推断恢复计划。由于其通过矩阵操作的启发式规则和并行规则射击方式的图形表示,可以通过PNS知识代表方法有利地表达和利用恢复的人类专业知识。开发系统在样品变电站上示出并在台南市的实用台湾电力(台电)变电站上进行了测试。 PNS模型的灵活性和有效性已被验证为恢复调度的决策支持。

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