The Mechanism-Data Dual-Driven Parameter Identification Method for Multi-Condition Control of Photovoltaic Inverters

This paper addresses the parameter identification problem of photovoltaic (PV) inverters and proposes a multi-condition control parameter identification method for grid-connected PV inverters based on a mechanism-data dual-driven approach. Firstly, the control principles of PV inverters are analyzed to clarify their underlying mechanisms. Then, hardware-in-the-loop (HIL) tests are conducted to collect test data from grid-connected PV inverters. Subsequently, an improved whale optimization algorithm is employed to identify the control parameters of the PV inverter. Finally, a comparison between the identified curves and the measured curves demonstrates that the proposed method can accurately and efficiently identify the control parameters of PV inverters.