Abstract
Stand-alone solar photovoltaic (PV) systems are a convenient way to provide electricity for people far from the electric grid or for people who want electric power with a slight dependence on the utility grid, to run their usual activities either at home or at businesses. These PV systems, combined with storage components, are considered distributed energy resources (DERs). In fact, DERs connected to distribution grids are increasing, especially PV systems, which pose several challenges to fault location, isolation, and restoration service (FLIRS) integrated into distribution automation systems (DAS). While most studies paid attention to issues focused on background knowledge or impedance-based fault location, others only adopted simplified PV models that cannot ensure accurate presentation of actual PV fault behaviors. Therefore, this chapter aims to extensively investigate the impacts of increased PV integration on the existing FLIRS performance, when PV systems become more intelligent by integrating inverters with the Internet of Things (IoT) to efficiently control the system and optimize power generation through maximum power point tracking algorithms. Since Danang Power Company put a commercial advanced FLIRS function integrated with DAS in operation along with the orientation of transforming into a smart grid, considering the extremely rapid development of PV systems in medium-voltage (MV) distribution networks, it has become a typical model for studying faults occurring in MV systems when PV penetration is high. A total of 2,700 error scenarios were carried out for comprehensive investigation purposes. All the network components relevant to the study are simulated with great detail in an environment of PowerFactory/DIgSILENT software, which can communicate with DAS through communication methods. From then, can be built IoT solutions that support modern PV system monitoring and control, which can predict and evaluate outputs from available data, possibly from Big Data.
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