Optimization of droop setting using Genetic Algorithm for Speedtronic Governor controlled Heavy Duty Gas Turbine Power Plants

Biomass is identified as one of the major renewable energy sources for electrical power generation. Heavy duty gas turbine engines are preferred for clean and efficient power generation. An extensive literature survey reveals that the governor droop setting of the heavy duty gas turbines varies from 2 percentage to 10 percentage. But it needs to be optimized for analyzing the dynamic response of heavy duty gas turbine plants in grid connected operation. An attempt has been made in this paper to optimize the speedtronic governor droop setting of all heavy duty gas turbine plants ranging from 18.2MW to 102.6MW using genetic algorithm. Step response of all heavy duty gas turbine plants with the genetic algorithm based droop setting are obtained using MATLAB/Simulink. On comparing the simulation results based on all time domain specifications and performance index criteria, it is witnessed that the genetic algorithm based droop setting yield optimal transient and steady state responses than the previous findings using SYSTAT software. Therefore the genetic algorithm based droop setting is identified as the optimal droop setting for all heavy duty gas turbine plants in grid connected operation. Key-Words: Biomass Power, Heavy Duty Gas turbine, Optimal droop setting, Genetic Algorithm, Simple cycle operation, Simplified Model, Single shaft turbine, Speedtronic Governor, SYSTAT