Abstract Hybrid microgrids (HMGs) typically combine renewable-based and conventional generation with energy storage and controllable loads, offering a number of benefits besides simple reduction of CO2 emissions. If properly sized and controlled, such HMGs could be operated as fully dispatchable parts of a wider distribution network and could significantly improve overall system reliability and reduce impact of outages on the connected customers. Designing and operating HMGs, however, is a complex task and this paper presents an approach based on improved binary genetic algorithm (IBGA) method for optimal dispatching and control of all HMG resources: renewable and conventional generators, energy storage system and demand-manageable loads. Following an outage and based on available HMG resources, the IBGA aims to find a solution for network reconfiguration in which radial structure of the network is maintained and loads are supplied in accordance to a specified priority list, while also satisfying operational constraints: bus voltage and branch loading limits. The presented methodology is illustrated and validated on a commonly used IEEE 33-bus test network, where obtained results demonstrate that HMGs can improve overall system reliability and reduce negative impact of outages on the connected customers.

中文翻译：

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具有混合微电网的配电网络的优化重构和供应恢复

摘要 混合微电网 (HMG) 通常将可再生能源和传统发电与储能和可控负载相结合，除了简单地减少二氧化碳排放外，还提供许多好处。如果大小和控制得当，此类 HMG 可以作为更广泛的配电网络的完全可调度部分运行，并可以显着提高整体系统可靠性并减少停电对连接客户的影响。然而，设计和运行 HMG 是一项复杂的任务，本文提出了一种基于改进二元遗传算法 (IBGA) 方法的方法，用于优化调度和控制所有 HMG 资源：可再生和常规发电机、储能系统和需求可管理负载. 发生中断后，根据可用的 HMG 资源，IBGA 旨在为网络重新配置找到一种解决方案，在该解决方案中，网络的径向结构得以维持，并根据指定的优先级列表提供负载，同时还满足操作约束：母线电压和分支负载限制。所提出的方法在常用的 IEEE 33 总线测试网络上进行了说明和验证，其中获得的结果表明 HMG 可以提高整体系统可靠性并减少中断对连接客户的负面影响。