Optimal Frequency Control of an Autonomous Microgrid Using a Virtual Synchronous Generator Based on the Ant Colony Optimization Algorithm

International Journal of Electrical and Electronics Engineering |
© 2025 by SSRG - IJEEE Journal |
Volume 12 Issue 5 |
Year of Publication : 2025 |
Authors : Hung Nguyen-Van, Hoan Hoang-Van, Chuong Trinh-Trong |
How to Cite?
Hung Nguyen-Van, Hoan Hoang-Van, Chuong Trinh-Trong, "Optimal Frequency Control of an Autonomous Microgrid Using a Virtual Synchronous Generator Based on the Ant Colony Optimization Algorithm," SSRG International Journal of Electrical and Electronics Engineering, vol. 12, no. 5, pp. 58-68, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I5P106
Abstract:
Maintaining frequency stability in isolated microgrids is very challenging due to the unpredictable and fluctuating output of local renewable energy sources, such as wind and solar. Furthermore, given the growing use of distributed generation via power electronics interfaces, the low natural inertia in such systems makes the task more challenging. To solve this issue, the Virtual Synchronous Generator (VSG) is a promising tool for modelling the inertial response of traditional synchronous machines. By adjusting two important parameters, the damping factor D and the virtual moment of inertia J, this paper proposes an optimisation method to enhance the performance of VSG. The Ant Colony Optimisation (ACO) algorithm is used to determine the optimal values for these parameters. Simulation results using MATLAB/Simulink show that the optimised settings significantly improve the microgrid's dynamic frequency behaviour when compared to default control settings, which lowers frequency deviations and speeds up recovery.
Keywords:
Microgrid, VSG, lack of inertia, ACO, Frequency control.
References:
[1] Saad Ahmad et al., “A Review of Microgrid Energy Management and Control Strategies,” IEEE Access, vol. 11, pp. 21729-21757, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Moslem Uddin et al., “Microgrids: A Review, Outstanding Issues and Future Trends Moslem,” Energy Strategy Reviews, vol. 49, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Amirnaser Yazdani, and Reza Iravani, Voltage-Sourced Converters in Power Systems: Modeling, Control, and Applications, John Wiley & Sons, 2010.
[Google Scholar] [Publisher Link]
[4] Joan Rocabert et al., “Control of Power Converters in AC Microgrids,” IEEE Transactions on Power Electronics, vol. 27, no. 11, pp. 4734-4749, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Prabha S. Kundur, and Om P. Malik, Power System Stability and Control, 2nd ed., McGraw-Hill, 1994.
[Google Scholar]
[6] Jia Liu et al., “Enhanced Virtual Synchronous Generator Control for Parallel Inverters in Microgrids,” IEEE Transactions on Smart Grid, vol. 8, no. 5, pp. 2268-2277, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Chenyang Li et al., “Modelling and Small Signal Stability for Islanded Microgrids with Hybrid Grid-Forming Sources based on Converters and Synchronous Machines,” International Journal of Electrical Power & Energy Systems, vol. 157, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Lakshmi Satya Nagasri D., and Marimuthu R., “Review on Advanced Control Techniques for Microgrids,” Energy Reports, vol. 10, pp. 3054-3072, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Sudhir Kumar Singh et al., “Virtual Synchronous Machine Using Ant Colony Optimization in Inverter Interfaced Distributed Generation (IIDG),” Journal of Electrical Engineering & Technology, vol. 18, no. 1, pp. 167-179, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Long Phan-Van et al., “A Comparison of Different Metaheuristic Optimization Algorithms on Hydrogen Storage-Based Microgrid Sizing,” Energy Reports, vol. 9, pp. 542-549, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Yongli Zhu et al., “Optimization of Battery Energy Storage to Improve Power System Oscillation Damping,” IEEE Transactions on Sustainable Energy, vol. 10, no. 3, pp. 1015-1024, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Thongchart Kerdphol et al., “Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration,” Sustainability, vol. 9, no. 5, pp. 1-21, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Jong Ju Kim, and June Ho Park, “A Novel Structure of a Power System Stabilizer for Microgrids,” Energies, vol. 14, no. 4, pp. 1-33, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Mohamed Yaich et al., “Metaheuristic Optimization Algorithm of MPPT Controller for PV System Application,” The International Conference on Energy and Green Computing (ICEGC’2021), vol. 336, pp. 1-6, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Jingyang Fang et al., “On the Inertia of Future More-Electronics Power Systems,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 7, no. 4, pp. 2130-2146, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Paul Denholm et al., “Inertia and the Power Grid: A Guide Without the Spin,” National Renewable Energy Laboratory, Golden, CO, 2020.
[Google Scholar]
[17] Mpeli Rampokanyo et al., “Impact of High Penetration of Inverter-based Generation on System Inertia of Networks,” Electra CIGRE, 2021.
[Google Scholar] [Publisher Link]
[18] Amirnaser Yazdani, and Reza Iravani, “A Unified Dynamic Model and Control for the Voltage-Sourced Converter under Unbalanced Grid Conditions,” IEEE Transactions on Power Delivery, vol. 21, no. 3, pp. 1620-1629, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Marco Dorigo, and Thomas Stützle, Ant Colony Optimization, MIT Press, 2004. [Online]. Available:
https://mitpress.mit.edu/9780262042192/ant-colony-optimization/
[20] Marco Dorigo, and Gianni Di Caro, “Ant Colony Optimization: A New Meta-Heuristic,” Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, Washington, DC, USA, vol. 2, 1992.
[CrossRef] [Google Scholar] [Publisher Link]
[21] MarcoDorigo, Vittorio Maniezzo, and Alberto Colorni, “Ant System: Optimization by a Colony of Cooperating Agents,” IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 26, no. 1, pp. 29-41, 1999.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Dorian Gaertner, and Keith Clark, “On Optimal Parameters for Ant Colony Optimization algorithms TSP classifications,” Proceedings of the 2005 International Conference on Artificial Intelligence IC-AI, Las Vegas, Nevada, USA, pp. 83-89, 2005. [Google Scholar] [Publisher Link]
[23] Ibtissem Chiha, Noureddine Liouane, and Pierre Borne, “Tuning PID Controller Using Multiobjective Ant Colony Optimization,” Applied Computational Intelligence and Soft Computing, vol. 2012, no. 1, pp. 1-7, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Mohd Hanif Othman et al., “Genetic Algorithm-Optimized Adaptive Network Fuzzy Inference System-Based VSG Controller for Sustainable Operation of Distribution System,” Sustainability, vol. 14, no. 17, pp. 1-16, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Qian Chen et al., “Analysis of Grid-Connected Stability of VSG-Controlled PV Plant Integrated with Energy Storage System and Optimization of Control Parameters,” Electronic, vol. 13, no. 7, pp. 1-18, 2024.
[CrossRef] [Google Scholar] [Publisher Link]