Hydropower Fleet Modelling And Parameter Identification For Synchronous Generator Based On Improved Particle Swarm Optimization

Nowadays, the world has been focusing more and more attention on protecting the environment and saving resources, and so has the electric power industry. Water, as a kind of clean and renewable energy, has been long been valued a lot by our country. In the area with abundant hydropower resources, it has distributed a large number of small and medium-sized hydropower stations. Although the unit capacity of their hydropower fleet is small now, the switchboard capacity is sure to be large and large with the increasing scale of hydropower stations, and more importantly, these generator sets will weaken the damping effects of the power system and induce low-frequency oscillation. Thus the effects on the power system’s stability of the small and medium-sized hydropower station for grid can not ever be ignored.Moreover, digital simulation of power system is an important means of power system stability analysis and we need to build an equivalent model of hydropower unit to identify the parameters of synchronous generators. Because of a numerous number of synchronous generator parameters needing to identify, the simple random,it is impossible to realize the parameters identification of synchronous generators only by static inputting and outputting data. So to guarantee the uniqueness and identifiability of the parameters, a combination of using wide area measurement system to get the PMU data online and becomes an effective tool for online parameter identification. The study chooses the parallel improved PSO algorithm to identify the parameters of synchronous generators among the a large number of parameter identification methods.The study focuses on modelling for the Hydropower fleet and identifying the parameters of synchronous generators of this model based on analysis of various parameter identification methods. The paper analyzes the mathematical models of the main components of the Hydropower system, including four parts: synchronous generators, loads, transmission lines and excitation system,and confirms synchronous generator’s parameters identifiability by evolving mathematical equations of its third-order model. The paper models detailedly for a standard 10 machine 39-bus system based on MATLAB/PST platform, and identifies synchronous generator G2’s parameters of this model by using parallel improved PSO algorithm, which integrates linear decreasing weights, compression factor and parallel algorithm, and analyzes transient stability of the system using the parameters obtained in the identification to confirm the effectiveness of the program.