Development of a Reverse Power Flow Identification and Under Frequency Load Shedding Scheme Load Anticipation Algorithm

The introduction of Distributed Solar Photovoltaic (DPV) Generation onto the Australian market presents many unique boons for the Australian energy market, including increased generation and cleaner energy for the mitigation of the growing climate change crisis. But so does it pose several uniquely challenging obstacles to overcome. One such challenge is the introduction of reverse power flow (RPF) to the Network, which occurs when the distributed generation on a feeder exceeds the load. This phenomenon often occurs during midday when solar penetration is at its greatest. On certain sections of Distributed Network Service Provider (DNSP) networks, the infrastructure necessary to determine power flow directionality is limited. This is detrimental to protection schemes, most notably the Under Frequency Load Shedding (UFLS) scheme. When a large disturbance occurs on the network and/or a large portion of generation is removed, generation no longer matches the load on the network, and so the frequency of the network decreases. To maintain the frequency, load must be shed from the system. However, much of the load acts as generation during high solar penetration days and shedding of this generation during an event may exacerbate the problem. This means that gaining visibility of power flow directionality is important to ensuring successful operation of protections schemes. To explore this issue, this conference paper will work to develop a data analysis reverse power flow identification algorithm. This algorithm is able to identify 88.3% of the time when a feeder is in RPF, and 99.34% of the time when a feeder is not in RPF.