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Harris hawks optimization algorithm for load frequency control of isolated multi-source power generating systems.
- Source :
-
International Journal of Emerging Electric Power Systems . Aug2024, Vol. 25 Issue 4, p555-571. 17p. - Publication Year :
- 2024
-
Abstract
- This paper presents a recent bio-inspired optimization algorithm for the critical topic of load frequency control (LFC) in an isolated multi-source power generating system. A specific model that emerges from the scientific literature and consists of reheated thermal, hydro and gas-turbine power sources is examined. The main goal is to tune the controller of each generating source i.e. find their optimal gains through bio-inspired optimization algorithms. Namely, the algorithms applied are the Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), and the newly proposed Harris Hawks Optimization (HHO). It was observed that all optimization algorithms succeeded in obtaining controllers' gain values which ensure stable system operation. Also, the simulation results indicated the superiority of the proposed HHO algorithm over the other algorithms for all the considered scenarios. In this article, for the first time to the authors' knowledge extend an attempt has been made to optimize an isolated multi-source system using the bio-inspired HHO algorithm. The present study considered the LFC problem with a variety of different scenarios, taking into account both sub-cases of nonlinearities (e.g., generation rate constraint, boiler dynamics, etc.) and their combinations, as well as combinations of different controllers and load disturbances, which are not found in the literature. Last but not least, the robustness of the selected controller was further evaluated. The obtained results clearly demonstrated that the controller's gains established in normal conditions do not require retuning when critical system parameters undergo a significant variation. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1553779X
- Volume :
- 25
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- International Journal of Emerging Electric Power Systems
- Publication Type :
- Academic Journal
- Accession number :
- 179047087
- Full Text :
- https://doi.org/10.1515/ijeeps-2023-0035