Identification of Key Parameters for Fault Crossing in Photovoltaic Power Plants Based on Measured Data
Year: 2025
Type: article
Abstract: In order to better avoid the grid disconnection caused by the grid faults of new energy power plants, verify the high and low voltage ride-through capability of photovoltaic power plants, and obtain accurate model control parameters, this paper proposes a key parameter identification method for photovoltaic power plants based on high and low voltage ride-through test measurement data, considering the characteristics of the entire fault ride-through process.Based on the measured data, a BPA model of the photovoltaic power plant is established.By conducting sensitivity analysis on the model parameters, key identification parameters are determined.A photovoltaic power plant model identification method based on an improved Salp Swarm Algorithm (SSA) with multiple strategies is proposed.The method continuously optimizes and updates the parameters to be identified and performs transient stability calculations.The error between the output of the simulation model and the measured data is calculated to obtain accurate model parameters for the photovoltaic power plant.This method is applied to the grid performance testing of an actual photovoltaic power plant in Guizhou, verifying the high and low voltage ride-through capability of the power plant under different operating conditions and obtaining accurate control parameters.The results show that the proposed parameter identification method can accurately identify the key parameters of high and low voltage ride-through under different operating conditions, and the error between the simulation and measured data meets the technical requirements of relevant standards, making it suitable for practical engineering calculations.
Source: Modeling and Simulation
Author: 国强 曹
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4406130780