Two-level Correction Method of Load Parameters Based on an Aggregation-identification Structure

In view of the shortcomings of the existing parameter identification algorithms in precision and time, a two-level correction method of load parameters based on an aggregation-identification structure is proposed. Firstly, according to the historical statistical data of the load group, an equivalent aggregation model is established by the weighted aggregation algorithm which takes into account the load rate and critical slip of induction motors. Then, based on the parameter trajectory sensitivity analysis, with the parameter values of the aggregation model as the initial values, particle swarm optimization algorithm is used to identify the dominant parameters to establish a synthesis load model and calculate the root mean square error between the measurement data and system response. Finally, the improved EPRI-36 node system is built by the power system analysis and synthesis program for system simulation, and the effectiveness and accuracy of the proposed method is verified.