Regulating PID Optimal Gains Using Particle Swarm Optimization Algorithm long with Mutation Operator and Genetic Algorithm

Hydraulic turbine regulator systems are among the most important components of any hydroelectric power plant, and play a vital role in securing the economic performance of the hydroelectric installations. Currently, normal PID controllers are employed extensively in these systems, the main disadvantage of which is, given the control rule, that it provides no information regarding how one can regulate the parameters optimally. In this paper, these parameters are regulated using Genetic Algorithm (GA) and the combined algorithm of Particle Swarm Optimization-Mutation (PSO-Mutation) algorithm in order to solve the problem of PID gains in hydraulic turbine systems. The results of the simulation of these two algorithms, compared to that of Improved Particle Swarm Optimization (IPSO) algorithm, show that the combined algorithm (PSO-Mutation) has led to the removal of the tipping point and the reduction of settlement and error squares. In fact, a more desirable response is achieved and finally, the accuracy of controlling the hydraulic turbine speed is increased and this has led to an increase in production efficiency in comparison to other two algorithms.

Keywords:

Genetic Algorithm (GA) , Hydraulic Turbine , Mutation , Optimization , Particle Swarm Optimization (PSO) Algorithm , PID Controller