Fractional order PIλDμ controller for microgrid power system using cohort intelligence optimization

Abstract

Microgrids are the future of energy management systems. Effective deployment and integration of microgrids can provide energy independence to many communities. The effectiveness of a microgrid primarily depends on its stability and reliability. Fractional regulators offer promising solutions to ensure stable microgrid performances. This article proposes a Fractional order Proportional–Integral–Derivative (FOPID) based secondary Load Frequency Control (LFC) for single area and dual-area AC microgrid systems. Cohort Intelligence (CI) based optimization was employed to tune the five major gain values of fractional PID regulators. The performance of the proposed CI tuned FOPID regulator was compared with that of the traditional PID controller tuned by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) on the same single and dual control area microgrid systems. Four different cases of AC microgrid simulations were explored for LFC performance assessments and effective comparisons among different controllers and tuning algorithms. The first case considered load changes in single area AC microgrid with and without distributed energy system. The second case considered load variations in the two area AC microgrid system. The third and fourth cases included variations in random step load and system parameters respectively. Primary results affirm the superiority of the CI tuned FOPID regulator over its GA and PSO tuned PID counterparts in terms of its better steady-state precision, expressed in terms of the Integral Time Absolute Error (ITAE) selected as the objective function.

Keywords

• Cohort Intelligence
• Genetic algorithm
• Particle Swarm Optimization
• Load Frequency Control
• Fractional order PID controller