Parameters Identification of Equivalent Model of Permanent Magnet Synchronous Generator (PMSG) Wind Farm Based on Analysis of Trajectory Sensitivity

Abstract

As wind farms have great influences on power system stability, it is essential to develop an adaptive as well as robust equivalent model of it. In this paper, a detailed equivalent model of PMSG wind farm and initialization method is developed. The trajectory sensitivity of parameters is analyzed. Then, the key parameters are estimated using improved Genetic Learning Particle Swarm Optimization (GLPSO) hybrid algorithm with phasor measurement unit (PMU). The description and generalization capability, stability for parameter identification of the equivalent model under wake effects, and when some wind turbines are off-line or wind speed is unknown after an event are analyzed. The maximum differences between the values of estimated parameters and their real ones are less than 10% for the proportional magnification constant of DC voltage controller and grid side current controller . The convergence rate and global optimization performance of the improved GLPSO hybrid algorithm is 0.5 times higher than the classical particle swarm optimization algorithm (PSO) and genetic algorithm (GA).

Aggregation Equivalence Method for Direct-Drive Wind Farms Based on the Excitation–Response Relationship

“…To improve the accuracy of equivalence, the most commonly used method for establishing equivalence models for new energy stations is the multi-machine equivalence method [7][8][9][10][11][12][13]. This method classifies new energy stations into a number of clusters based on the principle of similar operating states and then applies single-machine equivalence to the clusters [7,8].…”

“…This method classifies new energy stations into a number of clusters based on the principle of similar operating states and then applies single-machine equivalence to the clusters [7,8]. Essentially, it is no different from the single-machine equivalent method [9]. When clustering, it is necessary to use the operating data of each PMSG as the clustering indicator.…”

A Practical GERI-Based Method for Identifying Multiple Erroneous Parameters and Measurements Simultaneously

“…Reference [29] automatically updates the weighting factors of measurement dependencies with a robust state estimation method based on the WLS SE model. Reference [30] uses the genetic learning particle swarm optimization hybrid algorithm for the robust state estimation method to estimate the key parameters. Seven robust methods for line impedance estimation using fast voltage and current variation measurement are compared in an analysis of real measured data [31].…”