Using Genetic Algorithm to Optimize Controllers of Thermal Load System in Thermal Power Plant

This chapter presents the sequence of implementing the genetic algorithms using the programming language in the Mfile application of MATLAB Simulink software to optimize the two controller parameters of the coordinated control system structure of the thermal load system in coal-fired thermal power plants: electric power controller and steam pressure controller. Optimal standards are determined to be fast-tracking and fuel-saving. Operational data at a thermal power plant in Vietnam have been used to simulate the operation of a thermal load control system with a coordinated control structure in a thermal power plant to test controller parameters found from the genetic solution. To clarify the superiority of the genetic algorithm method in control of the thermal load system of a thermal power plant, the authors give an evaluation of the original control system compared to the control system using the parameters found from the genetic algorithm method. The results show that the thermal load control system in the thermal power plant using controller parameters found from the genetic algorithm method is much more optimal in terms of fuel consumption and the ability to follow the set amount