Online correction of multi-scene load model parameters based on measured data

In identifying high-voltage load parameters, the identification method based on measurement data has limited application scenarios and poor identification timeliness. To solve this problem, this paper takes the composite load model with distributed photovoltaic power as the research object. A dual objective function is constructed based on the load bus’s fitting degree of active and reactive power. The multi-objective particle swarm optimization algorithm is used to identify the proportional parameters of the model in the small disturbance scenario where the voltage fluctuation caused by the power change of different components of the load model is less than 5%. Combined with the identification of load parameters in large disturbance scenarios, an online load parameter correction system based on load bus measurement data is proposed, which can automatically adapt to the scene. Through the validation of the EPRI-36 node system, the proposed method can realize the high-precision identification of load parameters in various scenarios and greatly improve the timeliness of load parameter correction.