With electric distribution network operators experiencing an exponential increase in distributed energy resource connections to the power grid, operational challenges arise attributable to the traditional methods of building distribution feeders. Photovoltaic (PV) solar systems are the major contributor due to recent technological advancements. Though this renewable energy resource is beneficial to human society, unfavorable electrical conditions can arise from the inherit variability of solar energy. Extreme variability of power injection can force excessive operations of voltage regulation equipment and potentially degrade customer voltage quality. If managed and controlled properly, battery energy storage systems installed on a distribution feeder have the ability to compliment solar generation and dampen the negative effects of solar generation.
Now that customers are connecting their own generation, the traditional design assumption of load flowing from substation to customer is nullified. This research aims first to capture the maximum amount of generation that can be connected to a distribution feeder. Numerous deployments of generation scenarios are applied on six unique distribution feeders to conclude that hosting capacity is dependent on interconnect location. Then, existing controllers installed on voltage regulation equipment are modeled in detail. High resolution time series analysis driven from historical measurements is conducted on two contrasting feeders with specific PV generator deployments. With the proper modeling of on-load tap changer controls, excessive operations caused by extreme PV generation swings were captured.
Several services that battery energy storage systems can provide when connected to an individual distribution feeder with significant PV generation include long term absorption of excessive PV generation, dynamic response to extreme PV generation ramping, and release of stored energy for system peak shaving. A centralized master energy coordinator is proposed with the ability to dispatch the battery system in such a fashion to implement each service throughout consecutive days of operation. This solution was built by integrating load and solar energy forecasting predictions in order to construct an optimum charging and discharging schedule that would maximize the asset’s lifespan. Multiple load and solar generation scenarios including a consecutive three day run is included to verify the robustness of this energy coordinator
