Optimization-Based Calibration of Aggregated Dynamic Models for Distributed Energy Resources

The rapid growth of solar photovoltaic systems installation capacity has changed the behavior of the power system. To handle the high penetration level of distributed energy resources (DERs), an aggregate dynamic model called "DER A" has been developed and is available for most power system simulators. Since DER A has tens of adjustable parameters, methods are required for optimizing the model by finding the best-fit parameter values that guarantee the accuracy of the power system simulation. In this paper, an optimization-based method is proposed to find the best parameter configuration of the DER A model for improving the simulation accuracy. The critical parameters are identified among a total of 48 parameters to participate in the optimization process. To verify the performance of the optimized DER A model, a commercial distribution grid simulator is used to generate the required input data by simulating the IEEE 34-node test feeder. Five PVs are integrated into the simulated distribution feeder model to test the capability of the DER A model in terms of the representation of DERs' aggregated behaviors.