Generation-based automatic generation control with multisources power system using bacterial foraging algorithm

Abstract

This article presents an application of bacterial foraging algorithm (BFA) for design and implementation of generation-based PID structured automatic generation control (AGC) in a 2-area multisources power system with hydro, thermal, and gas power plants incorporated in each area. Most of AGC studies carried out so far have considered the initial system loading to be equal to 50% of the area generation capacity. But, AGC controller parameters are uncertain due to stochastic nature of power demand of the end users. Hence, in this article, the design of AGC controller is proposed on the basis of generation schedule by incorporating changes in power system gain constant, power system time constant, frequency bias constant, and so on. The dynamic responses of power system with BFA tuned AGC controller are compared with the genetic algorithm tuned AGC controller. The parameters of the controllers are evaluated by using these techniques and investigations are carried out to find the best performance of the system. Therefore, it is desirable to find the parameters of the generation-based controller depending upon the contribution of its constituent hydro, thermal, and gas energy sources in the total power generation.