Parameters Tuning Of Hydro Turbine Governor Based On Enhanced Particle Swarm Optimization

The electric power industry gets highly developed, which causes environmental pollution at the same time. It follows that hydropower resource, as a kind of recycled, pollution-free and abundant resource can be applied and developed in electrical system. Water resource is transformed into power energy by generator unit of hydraulic turbine. Hydraulic turbine regulating system(HTRS), which is a key part of generator unit, can regulate output frequency and determine the power quality of the grid. How to select and optimize the parameters of hydraulic turbine governor to maintain the frequency of unit under a rated frequency range has been interesting researchers in this field.Firstly, this thesis presents the mathematical models of the typical HTRS and the HTRS with water hammer effect by studying their structure and the electricity generating principle of generator unit. By the comparisons with other common optimization algorithms, particle swarm optimization(PSO) algorithm is selected to solve the parameters optimization problem of turbine governor. Then because of the premature convergence and the loss of particle diversity in standard PSO, two kinds of improved algorithms are put forward. On the one hand, an improved chaos particle swarm optimization(CIPSO) algorithm is proposed, in which chaotic disturbance and the crossover operation in differential evolution(DE) algorithm are added for respectively improving local and global search capabilities of particles. On the other hand, in order to further study for optimization algorithms, combined fuzzy control theory with crossover progress in genetic algorithm(GA), an improved fuzzy particle swarm optimization(IFPSO) is presented to balance global and local searching performance and enhance the diversity of particles.CIPSO algorithm is applied to optimize the parameters of turbine governor for typical HTRS. The experimental results prove that the proposed CIPSO algorithm has a better performance on convergence precision and efficiency than several other common optimization algorithms. Besides, IFPSO algorithm is used in the simulation experiments for parameters optimization problem for the HTRS with water hammer effect. The results confirm the enhancement of IFPSO algorithm in terms of parameter optimization accuracy, convergence efficiency and the algorithm stability. It reveals that the proposed IFPSO algorithm, as a superior parameter optimization method, can improve the dynamic performance of system.Lastly, the simulations studies on HTRS with MATLAB/Simulink software are conducted. The simulation experiments include varying parameters of turbine governor and controlled system, respectively, under frequency disturbance and load disturbance conditions. Through the simulation experiments, HTRS can get a comprehensive analysis and the results are shown to support the decisions on seeking a better set of parameters of turbine governor.