Affiliations:
Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science & Technology, Nawabshah, Sindh, Pakistan
Correspondence:
[*]
Corresponding author. Abdul Sami Memon, Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science & Technology, Nawabshah, 67480, Sindh, Pakistan. E-mail: justasmemon@gmail.com.
Abstract: In the modern power system, the use of renewable energy sources is increasing rapidly, which makes the system more sensitive. Therefore, it requires effective controllers to operate within the allowable ranges. The existing techniques based on cascaded controllers implemented so far for load frequency control have the advantage of improving the system response. However, this makes the system a more complex and time-consuming process. This makes the system more straightforward, makes it easy to optimize PID parameters, and provides results in acceptable ranges. This paper attempts to solve the load frequency control (LFC) problem in an interconnected hybrid power system with a classical PID controller employing the tunicate swarm algorithm (TSA). This algorithm is used for two areas of an interconnected hybrid power system: thermal, hydro, nuclear, and wind. The PID controller parameters are optimized by tunicate swarm algorithm using integral time absolute error (ITAE) based objective function. To show the robustness of the proposed TSA algorithm, a sensitivity analysis is performed for four case studies ranging from 20% to 30% load increments and decrements. The performance of the proposed TSA algorithm has been compared with the well-known optimization algorithms, particle swarm optimization (PSO), artificial bee colony (ABC), and arithmetic optimization algorithm (AOA) in terms of overshoot, undershoot, and settling time. The simulation results show that the proposed TSA has better optimization capability than PSO, ABC, and AOA in terms of overshoot, undershoot, and settling time.
Keywords: Tunicate Swarm based Automatic generation control, hybrid power system, TSA based Optimized PID controller, Interconnected power system, multi-area power system.
