Improving Frequency Control of Multi-Area Interconnected Hydro-Thermal Power System Using PSO Algorithm
Source abstract
Abstract
In modern power systems, fluctuations in load present ongoing challenges, making Load frequency control (LFC) an essential part of maintaining system stability and efficiency. This paper explores a method that combines traditional PID control with the Particle Swarm Optimization (PSO) algorithm to improve frequency regulation in interconnected hydropower systems. By using PSO, the method fine-tunes the PID controller parameters, enhancing frequency regulation, accelerating stabilization, and ensuring steady power flow across interconnecting lines. The simulation results show that this optimized method outperforms the conventional techniques, offering improved dynamic responses and a more robust performance, even in challenging and variable conditions. This makes it a promising solution for modern power systems, particularly in managing load fluctuations and maintaining frequency stability in interconnected hydropower systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Frequency Control in Power Systems · Microgrid Control and Optimization · Wind Turbine Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
References (34)
Show source-provided references
1. An overview of load frequency control strategies: A literature survey
2. Rasolomampionona, D.D., Połecki, M., Zagrajek, K., Wróblewski, W., and Januszewski, M. (2024). A Comprehensive Review of Load Frequency Control Technologies. Energies, 17.10.3390/en17122915 ↗
3. Robust decentralized turbine/governor control using linear matrix inequalities10.1109/TPWRS.2002.800959 ↗
4. Load-and renewable-following control of linearization-free differential algebraic equation power system models10.1109/TCST.2023.3244492 ↗
5. Sparsity-promoting optimal wide-area control of power networks10.1109/TPWRS.2014.2304465 ↗
6. Sundararaju, N., Vinayagam, A., Veerasamy, V., and Subramaniam, G. (2022). A chaotic search-based hybrid optimization technique for automatic load frequency control of a renewable energy integrated power system. Sustainability, 14.10.3390/su14095668 ↗
7. Gulzar, M.M., Iqbal, M., Shahzad, S., Muqeet, H.A., Shahzad, M., and Hussain, M.M. (2022). Load frequency control (LFC) strategies in renewable energy-based hybrid power systems: A review. Energies, 15.10.3390/en15103488 ↗
8. Mokhtar, M., Marei, M.I., Sameh, M.A., and Attia, M.A. (2022). An adaptive load frequency control for power systems with renewable energy sources. Energies, 15.10.3390/en15020573 ↗
9. Advanced sliding mode observer design for load frequency control of multiarea multisource power systems10.1155/2022/6587194 ↗
10. An optimized hybrid fractional order controller for frequency regulation in multi-area power systems10.1109/ACCESS.2020.3040620 ↗
11. An improved ACO algorithm optimized fuzzy PID controller for load frequency control in multi area interconnected power systems10.1109/ACCESS.2019.2960380 ↗
12. Izci, D., Ekinci, S., Çelik, E., Bajaj, M., Blazek, V., and Prokop, L. (2024). Dynamic load frequency control in power systems using a hybrid simulated annealing based quadratic interpolation optimizer. Sci. Rep., 14.10.1038/s41598-024-77247-3 ↗
13. Adaptive differential evolution and pattern search tuned fractional order fuzzy PID for frequency control of power systems10.1080/02286203.2021.1875287 ↗
14. Efficient load frequency control in multi-source interconnected power systems using an innovative intelligent control framework10.1016/j.egyr.2024.02.037 ↗
15. Dhanasekaran, B., Kaliannan, J., Baskaran, A., Dey, N., and Tavares, J.M.R. (2023). Load frequency control assessment of a PSO-PID controller for a standalone multi-source power system. Technologies, 11.10.3390/technologies11010022 ↗
16. Wang, J., and Sun, Y. (2024). Load Frequency Active Disturbance Rejection Control Based on Improved Particle Swarm Optimization. Electronics, 13.10.3390/electronics13071268 ↗
17. Ogar, V.N., Hussain, S., and Gamage, K.A. (2023). Load frequency control using the particle swarm optimisation algorithm and Pid controller for effective monitoring of transmission line. Energies, 16.10.3390/en16155748 ↗
18. Optimized PID Controller for load frequency control in multi-source and Dual-Area Power Systems Using PSO and GA algorithms10.1109/ACCESS.2024.3445165 ↗
19. Bano, F., Ayaz, M., Baig, D.E.Z., and Rizvi, S.M.H. (2024). Intelligent Control Algorithms for Enhanced Frequency Stability in Single and Interconnected Power Systems. Electronics, 13.10.3390/electronics13214219 ↗
20. Veerasamy, V., Abdul Wahab, N.I., Ramachandran, R., Vinayagam, A., Othman, M.L., Hizam, H., and Satheeshkumar, J. (2019). Automatic load frequency control of a multi-area dynamic interconnected power system using a hybrid PSO-GSA-tuned PID controller. Sustainability, 11.10.3390/su11246908 ↗
21. Whale optimization algorithm optimized fuzzy-PID plus PID hybrid controller for frequency regulation in hybrid power system10.1007/s40031-021-00656-9 ↗
22. Whale optimization algorithm applied to load frequency control of a mixed power system considering nonlinearities and PLL dynamics10.1007/s12667-019-00326-2 ↗
23. Sahu, P.R., Simhadri, K., Mohanty, B., Hota, P.K., Abdelaziz, A.Y., Albalawi, F., and Elsisi, M. (2023). Effective load frequency control of power system with two-degree freedom tilt-integral-derivative based on whale optimization algorithm. Sustainability, 15.10.3390/su15021515 ↗
24. Application of grey wolf optimization algorithm for load frequency control in multi-source single area power system10.1007/s12065-020-00530-5 ↗
25. A novel grey wolf optimizer based load frequency controller for renewable energy sources integrated thermal power systems10.1080/15325008.2022.2050450 ↗
26. Gupta, D.K., Soni, A.K., Jha, A.V., Mishra, S.K., Appasani, B., Srinivasulu, A., and Thounthong, P. (2021). Hybrid gravitational–firefly algorithm-based load frequency control for hydrothermal two-area system. Mathematics, 9.10.3390/math9070712 ↗
27. Kumar, N.K., Gopi, R.S., Kuppusamy, R., Nikolovski, S., Teekaraman, Y., Vairavasundaram, I., and Venkateswarulu, S. (2022). Fuzzy logic-based load frequency control in an island hybrid power system model using artificial bee colony optimization. Energies, 15.10.3390/en15062199 ↗
28. Load Frequency Control Strategy for the Nigerian Power System Using artificial Bee Colony optimized PI Controller
29. A hybrid metaheuristic optimisation technique for load frequency control10.1007/s42452-021-04482-y ↗
30. Harris hawks optimization algorithm for load frequency control of isolated multi-source power generating systems
31. A multi-agent deep reinforcement learning method for cooperative load frequency control of a multi-area power system10.1109/TPWRS.2020.2999890 ↗
32. Wu, M., Ma, D., Xiong, K., and Yuan, L. (2024). Deep Reinforcement Learning for Load Frequency Control in Isolated Microgrids: A Knowledge Aggregation Approach with Emphasis on Power Symmetry and Balance. Symmetry, 16.10.3390/sym16030322 ↗
33. Saadat, H. (1999). Power System Analysis, McGraw-Hill. Available online: https://www.amazon.com/Power-System-Analysis-Third-Saadat/dp/0984543864.
34. Huynh, V.V., Minh, B.L.N., Amaefule, E.N., Tran, A.T., and Tran, P.T. (2021). Highly robust observer sliding mode-based frequency control for multi-area power systems with renewable power plants. Electronics, 10.10.3390/electronics10030274 ↗