Improved Squirrel Search Algorithm Driven Cascaded 2DOF-PID-FOI Controller for Load Frequency Control of Renewable Energy Based Hybrid Power System

Abstract

Renewable energy-based hybrid power systems are being increasingly deployed across the globe to reduce carbon emissions. The system frequency and tie-line power tend to fluctuate due to system operating conditions. These fluctuations can be maintained within the desired limits using optimally designed controllers. In this article, the recently developed improved squirrel search algorithm (ISSA) is used to tune the parameters of different controllers, such as the proportional-integral-differential (PID), two degrees of freedom PID (2DOF-PID), three degrees of freedom PID (3DOF-PID), and a cascaded 2DOF-PID fractional order integral (FOI) to improve the performance of the system. The effectiveness of the best controller tuned with ISSA is compared with other optimization techniques such as Particle Swarm Optimization (PSO) and Squirrel Search Algorithm (SSA). A two-area multi-machine hybrid power system is considered to demonstrate the robustness of the proposed concept. The first area consists of a thermal, a hydro, and a wind power plant, while the second area consists of a thermal, a hydro, and a diesel power plant. Comparative performance analysis is carried out to obtain the best controller, tuned with the best optimization technique. Various case studies have been developed to check the system’s robustness, flexibility, and reliability.

Keywords

• Improved squirrel search algorithm (ISSA)
• integral time multiplied by absolute error (ITAE)
• load frequency control (LFC)
• particle swarm optimization (PSO)
• PID
• squirrel search algorithm (SSA)