Load Frequency Control of Two Area System Using Genetic Algorithm

Abstract

Today all generating area are interconnected through tie line. We require secure, economic and stable operation because in interconnected area one area is affected by change in other area. Improve power system stability we use no. of intelligence technique. In this research work, the Genetic algorithm controlling technique has been used for automatic generation control of interconnected power systems and application of Genetic algorithm to load frequency control in two area interconnected (Thermal-Thermal) power systems. The parameters of genetic algorithms are varied widely by a suitable choice of objective functions and parameters in the rule base. The Genetic algorithm is used to find the optimal values of the proportional-integral-derivation controller parameters based load frequency control. The chief aim of this work is to reduce all the fluctuations of the power system due to the disturbance and get again the frequency at prescribe value. This paper shows with tie line bias control, control parameters based on Ziegler-Nichols tuning rule and controller parameters based on GA algorithm this comparison shows that genetic algorithms give efficient output.

A Novel Multistage Controller for Load Frequency Control of a Multi-Area Network Integrated with Renewable Energy Sources

“…As a result of this challenge, many researchers have come up with different techniques for solving LFC problems by using classical PID controllers [9]- [12]. The control parameters tuning was achieved by using a swarm artificial intelligent technique, such as Genetic Algorithm (GA) [9], [11], particle Swarm optimization technique [10], firefly algorithm (FA) [13], and Bacteria Forging Optimization Algorithm [12] and hybrid approach combining Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) [14]. Nevertheless, the controllers that have been designed do not yield exceptional values for settling time, peak overshoot, or peak undershoot.…”