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Integrating Protection Constraints to a MEAN-Based Method for Service Restoration in Radial Distribution Systems

机译：将保护约束集成到径向分布系统中的平均服务恢复方法

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The distribution system service restoration (SR) process implies to change the network topology configuration via a real-time maneuver plan, which in turn results in increased load current and changed short-circuit levels in some adjacent feeders. As a consequence, some protective devices (PD) can operate undesirably. In addition, some network branches may itself become totally unprotected. Therefore, it is essential to consider phase and neutral overcurrent protection in the SR problem, in order to maintain service continuity during emergency situations. A very efficiently approach, named MEAN (Multi-Objective Evolutionary Algorithm with NDE), for solving the SR problem is based on Multi-objective Evolutionary Algorithm (MOEA) that combines sub population tables with the Node-Depth Encoding (NDE) technique. This paper proposes to incorporate the phase and neutral overcurrent protection constraints into the MEAN approach for service restoration in radial distribution systems. The approach proposed in this paper, named MEAN-PC (MEAN with Protection Constraints), uses additional subpopulation tables to store the solutions that consider protection constraints. The objective is to show that the overcurrent protection constraints on service restoration problems can be considered in an effective way, correctly indicating feasible solutions of maneuver plan. The proposed overcurrent protection constraints in service restoration are tested and verified on the 135-bus test distribution system.
机译：分发系统服务恢复（SR）流程意味着通过实时操作计划改变网络拓扑配置，从而导致负载电流增加并改变了一些相邻馈线中的短路电平。结果，一些保护装置（PD）可以不合需要地操作。此外，某些网络分支本身可能完全不受保护。因此，必须在SR问题中考虑相位和中性过电流保护，以便在紧急情况下维护服务连续性。一种非常有效的方法，命名为均值（具有NDE的多目标进化算法），用于解决SR问题是基于与节点深度编码（NDE）技术相结合的多目标进化算法（MOEA）。本文提出将相中性和中性过电流保护约束纳入径向分布系统中的服务恢复的平均方法。本文提出的方法，命名为平均PC（平均保护约束）使用额外的子迁移表来存储考虑保护约束的解决方案。目的是表明，可以以有效的方式考虑对服务恢复问题的过电流保护约束，正确地指示机动计划的可行解决方案。在135总线测试分配系统上测试并验证了在服务恢复中提出的过电流保护约束。

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