Wind turbine generator (WTG) and solar thermal power system (STPS) are growing field of renewable energy. These technologies are considered as the feasible options for the generation of electricity in future. However, the inclusion of these technologies affects the output power which intern affects the power frequency. Successful operation of a power system frequency requires frequency in operational limit, therefore, in this study a PID controller is designed for frequency control of a hybrid power system. Big bang big crunch (BBBC) optimization technique is used for determining the parameters of PID controller. The performance of controller has been checked with random variation of load demands. The obtained results demonstrate the effectiveness of the controller. Further, a comparative analysis of results obtained with BBBC has also been performed with genetic algorithm (GA) based controller.

A fractional order PID (FOPID) control technique for automatic generation control (AGC) in a multi-area power system is presented in this study. To create a reliable controller, a variety of control strategies were used. The load frequency control (LFC) problem in a power system implementing different power transactions, such as bilateral and Poolco transactions, are investigated here. Because any control scheme’s performance is only as good as its parameters, the parameters of the designed control scheme were determined using the big bang big crunch (BBBC) algorithm. Furthermore, in this work, the effect of a superconductive magnetic energy storage (SMES) unit is addressed in the given test (two and four area) systems. When confronted with a fluctuation in immediate load, the SMES unit is thought to follow the initial drop in frequency and tie-line power in order to increase LFC. It is evident that the performance of an FOPID control scheme is improved in the presence of an SMES unit and it provides frequency, tie-line power, change in generation with reduced oscillations and settling time.

This paper is focused on design and application of proportional integral derivative (PID) controller for deregulated multiarea automatic generation control (AGC) scheme utilizing the imperialist competitive algorithm (ICA) under various electricity market transactions. A multiarea hydro thermal 75-bus real power system is considered as a test system for deregulated AGC scheme. Simulation study results demonstrate the effective performance of controller on various load disturbance scenarios. The performance of ICA-tuned PID controller is also compared with genetic algorithm (GA)-tuned PID controller. The comparative results show that ICA–PID controller has higher convergence rate, smaller settling time, reduced oscillations than GA-tuned PID controller, i.e. reaching to better solution. Robustness of ICA–PID controller is also checked to determine its response towards system parameters uncertainties through sensitivity analysis. It is seen that the performance of PID controller tuned by ICA algorithm is robust for the system parameter uncertainties while GA–PID controller performance degrades.