Global Optimal Automatic Generation Control of a Multimachine Power System Using Hybrid NLMPC and Data-Driven Methods
Source abstract
Abstract
Real-world power systems face challenges from demand fluctuations, system constraints, communication delays, and unmeasurable disturbances. This paper presents a real-time hybrid approach integrating Nonlinear Model Predictive Control (NLMPC) and data-driven methods for automatic generation control (AGC) of synchronous generators, particularly under cyber-physical attacks. Unlike previous studies, this work considers both technical and economic aspects of power system management. A key innovation is the incorporation of a detailed thermo-mechanical model of turbine and governor dynamics, enabling optimized control and effective management of power oscillations. The proposed NLMPC-based AGC strategy addresses governor saturation and generation rate constraints, ensuring stability. Extensive simulations in MATLAB/Simulink, including IEEE 11-bus and 9-bus test systems, validate the controller’s effectiveness in enhancing power system performance under various challenging conditions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Frequency Control in Power Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical and Electronics Engineering, Karabuk University, Karabuk 78050, Türkiye
References (41)
Show source-provided references
1. Maghami, M.R., Mutambara, A.G.O., and Gomes, C. (2025). Assessing cyber attack vulnerabilities of distributed generation in grid-connected systems. Environ. Dev. Sustain., 1–27.10.1007/s10668-024-05929-z ↗
2. Khademi, M.M., and Jahromi, M.Z. (2024, January 23–25). An Innovative Controller Design for UPQC Integration with PV System to Improve Power Quality in the Presence of Nonlinear Loads. Proceedings of the 2024 28th International Electrical Power Distribution Conference (EPDC), Zanjan, Iran.10.1109/EPDC62178.2024.10571725 ↗
3. Yusupov, Z., Almagrahi, N., Yaghoubi, E., Yaghoubi, E., Habbal, A., and Kodirov, D. (2022, January 25–26). Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station. Proceedings of the World Conference Intelligent System for Industrial Automation, Tashkent, Uzbekistan.
4. Brahmachari, S., and Chanana, S. (2022). Load Frequency Control of Two Area Deregulated Power System Using Hybrid PSOGSA-TVAC Algorithm. Control and Measurement Applications for Smart Grid: Select Proceedings of SGESC 2021, Springer.10.1007/978-981-16-7664-2_29 ↗
5. Khamees, A., and Altınkaya, H. (2024). Real-Time Control of Thermal Synchronous Generators for Cyber-Physical Security: Addressing Oscillations with ANFIS. Processes, 12.10.3390/pr12112345 ↗
6. Yaghoubi, E., Yaghoubi, E., Yusupov, Z., and Maghami, M.R. (2024). A Real-Time and Online Dynamic Reconfiguration against Cyber-Attacks to Enhance Security and Cost-Efficiency in Smart Power Microgrids Using Deep Learning. Technologies, 12.10.3390/technologies12100197 ↗
7. Smart grid architecture model for control, optimization and data analytics of future power networks with more renewable energy10.1016/j.jclepro.2021.126877 ↗
8. Advances in Model Predictive Control for Large-Scale Wind Power Integration in Power Systems: A Comprehensive Review10.1016/j.adapen.2024.100177 ↗
9. Real-time techno-economical operation of preserving microgrids via optimal NLMPC considering uncertainties
10. Ullah, K., Basit, A., Ullah, Z., Aslam, S., and Herodotou, H. (2021). Automatic generation control strategies in conventional and modern power systems: A comprehensive overview. Energies, 14.10.3390/en14092376 ↗
11. Load frequency control of a two-area power system with a stand-alone microgrid based on adaptive model predictive control10.1109/JESTPE.2020.3012659 ↗
12. Hierarchical model predictive control for performance enhancement of autonomous microgrids10.1016/j.asej.2020.12.007 ↗
13. An efficient design of adaptive model predictive controller for load frequency control in hybrid power system10.1155/2022/7894264 ↗
14. A multi-agent deep reinforcement learning method for cooperative load frequency control of a multi-area power system10.1109/TPWRS.2020.2999890 ↗
15. Distributed Model Predictive Frequency Control of Inverter-Based Power Systems10.1109/ACCESS.2024.3387369 ↗
16. Finite-time economic model predictive control for optimal load dispatch and frequency regulation in interconnected power systems10.1016/j.gloei.2023.06.009 ↗
17. Ajiborisha, A.S. (2021). Model Predictive Load Frequency Control Methods with Battery Energy Storage in Future Power Systems. [Ph.D. Thesis, University of Sheffield].
18. Hierarchical predictive control for electric vehicles with hybrid energy storage system under vehicle-following scenarios10.1016/j.energy.2022.123774 ↗
19. Patel, M.R., and Beik, O. (2021). Wind and Solar Power Systems: Design, Analysis, and Operation, CRC Press.10.1201/9781003042952 ↗
20. A novel model predictive controller for distributed generation in isolated microgrids—Part II: Model predictive controller implementation10.1109/TIA.2022.3181218 ↗
21. Optimal control for speed governing system of on-grid adjustable-speed pumped storage unit aimed at transient performance improvement10.1109/ACCESS.2021.3063434 ↗
22. Distributed economic MPC for LFC of multi-area power system with wind power plants in power market environment10.1016/j.ijepes.2020.106548 ↗
23. Nurkanović, A., Mešanović, A., Zanelli, A., Frison, G., Frey, J., Albrecht, S., and Diehl, M. (2020, January 1–3). Real-time nonlinear model predictive control for microgrid operation. Proceedings of the 2020 American Control Conference (ACC), Denver, CO, USA.10.23919/ACC45564.2020.9147816 ↗
24. Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques10.1016/j.rser.2021.110969 ↗
25. A fuzzy logic and artificial neural network-based intelligent controller for a vehicle-to-grid system10.1109/JSYST.2020.3006338 ↗
26. Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions10.1016/j.apenergy.2020.115733 ↗
27. Altinkaya, H., Khamees, A., Yaghoubi, E., and Yaghoubi, E. (2024, January 25–27). Control of Heat Exchanger Liquid Temperature Using PID Control and first Order Sliding Mode Control System. Proceedings of the 2024 International Conference on Electrical, Computer and Energy Technologies (ICECET), Sydney, Australia.10.1109/ICECET61485.2024.10698052 ↗
28. A literature survey on load frequency control considering renewable energy integration in power system: Recent trends and future prospects10.1016/j.est.2021.103717 ↗
29. Decentralized networked load frequency control in interconnected power systems based on stochastic jump system theory10.1109/TSG.2020.2978029 ↗
30. Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi-microgrids systems10.1002/2050-7038.12732 ↗
31. Coordinated design of PSS and multiple FACTS devices based on the PSO-GA algorithm to improve the stability of wind–PV–thermal-bundled power system10.1007/s00202-023-02055-3 ↗
32. Coordinated design of PSS and STATCOM-POD based on the GA-PSO algorithm to improve the stability of wind-PV-thermal-bundled power system10.1016/j.ijepes.2022.108208 ↗
33. Uyioghosa, I.E., and Saha, A.K. (2020, January 29–31). DMPC scheme for load frequency control with application to interconnected power system. Proceedings of the 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa.10.1109/SAUPEC/RobMech/PRASA48453.2020.9041073 ↗
34. DMPC-based load frequency control of multi-area power systems with heterogeneous energy storage system considering SOC consensus10.1016/j.epsr.2023.110064 ↗
35. Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs10.1109/TSG.2023.3345314 ↗
36. Solomon, E., Khan, B., Boulkaibet, I., Neji, B., Khezami, N., Ali, A., Mahela, O.P., and Pascual Barrera, A.E. (2023). Mitigating Low-Frequency Oscillations and Enhancing the Dynamic Stability of Power System Using Optimal Coordination of Power System Stabilizer and Unified Power Flow Controller. Sustainability, 15.10.3390/su15086980 ↗
37. Robust and coordinated tuning of PSS and FACTS-PODs of interconnected systems considering signal transmission delay using ant lion optimizer10.1007/s40313-018-0408-5 ↗
38. Solomon, E. (2022). Damping of Low Frequency Oscillation through Optimal Sizing of Unified Power Flow Controller and Power System Stabilizer Employing Antlion Optimization. [Ph.D. Thesis, Dilla University].
39. Power system stability
40. A novel recursive approach for real-time transient stability assessment based on corrected kinetic energy10.1016/j.asoc.2016.06.045 ↗
41. Meegahapola, L., Sguarezi, A., Bryant, J.S., Gu, M., Conde D., E.R., and Cunha, R.B.A. (2020). Power system stability with power-electronic converter interfaced renewable power generation: Present issues and future trends. Energies, 13.10.3390/en13133441 ↗