Optimization of Controller Parameters for Load Frequency Control Problem of Two-Area Deregulated Power System Using Soft Computing Techniques

It is very difficult to obtain the optimal parameter of controllers for load frequency control (LFC) problem of a multiarea power system in deregulated environment. Deregulated power system contains multisources and multistakeholders; therefore, conventional LFC methods are not effective and competent. The primary goal of LFC in a deregulated system is to restore the frequency to its original value as soon as feasible while also minimizing uncontracted power flow in tie line between neighboring control regions and tracking load balancing contracts. Gains of PID controller are required to be optimized in order to fulfill the objectives of LFC. Here genetic algorithm as well as particle swarm optimization techniques are presented in this paper for optimization of controller parameters in order to achieve the purposes of LFC of two-area deregulated system taking suitable objective function that are to minimize the frequency deviations of both the areas and to maintain tie line power flow according to contractual conditions. System has been simulated under MATLAB/Simulink, and dynamic responses have been obtained for many contractual conditions between GENCOS and DISCOS. It is confirmed by the results that the soft computing–based PID controllers are capable of maintaining the frequency in the pre-specified range and keep the tie line power flow as per the contractual conditions. An analysis has been done by comparing the dynamic responses of the system with PSO-based controller and GA-based controller.