Load frequency controller design of a two-area system composing of PV grid and thermal generator via firefly algorithm

• Published in: Neural computing & applications Vol. 30; no. 2; pp. 607 - 616
• Main Authors: Abd-Elazim, S. M., Ali, E. S.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Block diagrams; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Computer simulation; Control systems design; Controllers; Data Mining and Knowledge Discovery; Frequency control; Genetic algorithms; Heuristic methods; Hybrid systems; Image Processing and Computer Vision; Original Article; Photovoltaic cells; Probability and Statistics in Computer Science; Solar cells; LFC; Two-area system; MPPT; PI controller; Firefly algorithm; PV grid
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-016-2668-y

In this paper, firefly algorithm (FA) for optimal tuning of PI controllers for load frequency control of hybrid system composing of photovoltaic (PV) system and thermal generator is introduced. Also, maximum power point tracking of PV is considered in the design process. The block diagram of the hybrid system is performed. To robustly tune the parameters of controllers, a time-domain-based objective function is established which is solved by the FA. Simulation results are presented to show the improved performance of the suggested FA-based controllers compared with genetic algorithm (GA). These results show that the proposed controllers present better performance over GA in terms of settling times and different indices.