A hybrid shuffled frog-leaping and pattern search algorithm for load frequency controller design of a two-area system composing of PV grid and thermal generator

摘要

The shuffled frog-leaping algorithm (SFLA) is a nature-inspired metaheuristic swarm-based optimization algorithm, which mimics the social behavior of memetics. The SFLA comprises an arrangement of communicating virtual population of frogs divided into various memeplexes. Many attempts have been made to find the variant of the SFLA that performs better on a variety of optimization tasks by making the original SFLA more complex. This paper proposes the hybrid approach by combining the SFLA algorithm with a pattern search algorithm, which improves the original technique named as the hybrid shuffled frog-leaping and pattern search algorithm (hSFLA-PS). The superiority of the proposed hybrid algorithm over the original SFLA in terms of implementation time and solution quality is compared by taking several benchmark test functions. In the next step, the real application of the proposed hybrid approach in the engineering field is done by designing a proportional-integral-derivative (PID) controller for frequency regulation of a two-area power system that is composed of a photovoltaic (PV) grid and a thermal generator. It is observed that the hSFLA-PS-based PID controller is more effective for the load frequency control compared with conventional controllers tuned with genetic algorithm (GA) and firefly algorithm (FA).