Decentralized automatic generation control of interconnected power systems incorporating asynchronous tie-lines

Abstract

This Paper presents the design of decentralized automatic generation controller for an interconnected power system using PID, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The designed controllers are tested on identical two-area interconnected power systems consisting of thermal power plants. The area interconnections between two areas are considered as (i) AC tie-line only (ii) Asynchronous tie-line. The dynamic response analysis is carried out for 1% load perturbation. The performance of the intelligent controllers based on GA and PSO has been compared with the conventional PID controller. The investigations of the system dynamic responses reveal that PSO has the better dynamic response result as compared with PID and GA controller for both type of area interconnection.Electronic supplementary materialThe online version of this article (doi:10.1186/2193-1801-3-744) contains supplementary material, which is available to authorized users.

Automatic Generation Control of Two Area Thermal Power System using Single Objective PSO and DE Optimization Techniques

“…PSO is developed by Eberhart and Kennedy,it is population based heuristic or stochastic optimization technique based on the social behavior of bird flocking or fish schooling of swarm theory [13].In this method, a swarm consists of a set of individuals which are named as particles and each of them specified by their position as well as by velocity vectors and symbolically represented by (xi(t) and vi(t)) respectively. In PSO fitness values of all of particles is evaluated and optimized by using fitness function which has velocity to direct the flying.…”

“…Ziegler-Nichols is one of the early conventional PID tuning technique [4] ,this method is practical applied for broad range application ,however, these traditional methods have their own drawback for employing in large interconnected power system, some of the reasons are, they do not perform adequately for non-linearity and uncertainty cases and results in poor transient performance and slow in action, large overshoot, more oscillation and long settling time, for this comparison the artificial intelligent methods are better as mentioned in [6]. To enhance the capabilities, PID parameters are tuned using GA and DE for two area multi-unit thermal power plant by applying single and multi-objective optimization and an attractive result was obtained for the case of DE [3,8],the artificial intelligent technique PSO has been applied to improve the PID controller [7] besides this, optimization of nonlinear and linear time-invariant function by PSO is given in [10,13]. Many research work have been done considering AGC of having two or more interconnected areas using both single and multi-objective optimization, in [9,11] single and hybrid optimization methods was applied in AGC of two area having six units in non-reheat thermal power plant to improve the controllability of PID controller.…”