Enhancing Load Frequency Control in Interconnected Power Systems with Zone-Specific Fuzzy Controllers: Principles and Methods

Jahangiri, S and Jones, KO ORCID: 0000-0001-6689-3225 (2025) Enhancing Load Frequency Control in Interconnected Power Systems with Zone-Specific Fuzzy Controllers: Principles and Methods. In: Journal of Advances in Engineering and Technology , 3 (2). pp. 1-13. (SLIIT International Conference on Engineering and Technology, 25th Jul 2024, Malabe, Sri Lanka).

Preview

Text Enhancing Load Frequency Control in Interconnected Power Systems with Zone Specific Fuzzy Controllers.pdf - Accepted Version Download (867kB) | Preview

Abstract

This work focuses on load frequency control in interconnected power systems, a critical aspect of modern power grid operations. However, sudden load disturbances and generator outages can lead to transient oscillations between control areas, posing challenges to frequency control. The aim of the work was to investigate and enhance load frequency control behaviour, considering dynamic load changes and uncertainties. Fuzzy Logic Controllers optimized with Particle Swarm Optimization were applied to improve control robustness. The Particle Swarm Optimisation algorithm was used to tune the scaling factors and parameters of the fuzzy controllers to optimize their performance. The methods were tested on a standard four-area interconnected power system model equipped with load frequency control blocks, reheaters, governors, rate constraints, and thermal components. Different disturbance scenarios including parameter fluctuations and load changes were evaluated. The Fuzzy Logic Controllers demonstrate resilient response across scenarios without needing extensive tuning. Particle Swarm Optimization improves robustness through systematic exploration for constraint-based nonlinear optimization. Tuning fuzzy controllers with bio-inspired algorithms enhances efficiency in addressing complex grid conditions. The results provide insights into designing more secure and resilient grid controls, contributing to power system stability research.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	40 Engineering; 46 Information and Computing Sciences; 4007 Control Engineering, Mechatronics and Robotics; 4602 Artificial Intelligence; 4010 Engineering Practice and Education; 7 Affordable and Clean Energy
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions:	Engineering
Publisher:	Sri Lanka Institute of Information Technology
Date of acceptance:	9 December 2024
Date of first compliant Open Access:	28 October 2025
Date Deposited:	28 Oct 2025 10:25
Last Modified:	28 Oct 2025 11:00
DOI or ID number:	10.54389/wvzk7306
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27345

View Item