MODEL PREDICTIVE CONTROL (MPC) AND PROPORTIONAL-INTEGRAL-DERIVATIVE (PID) CONTROLLERS FOR LOAD FREQUENCY CONTROL SCHEME

MPC and PID Controllers for Load Frequency Control

Authors

  • Akhilesh Singh Electrical Engineering Department, Uttarakhand Technical University Campus Institute, NPSEI, Pithoragarh
  • Nagendra Kumar Electrical & Electronics Engineering Department, GL Bajaj Institute of Technology and Management, Greater Noida,
  • Manoj Badoni Electrical and Instrumentation Engineering Department TIET, Punjab, India
  • Rajeev Kumar Electrical and Electronics Engineering Department, KIET Group of Institutions Ghaziabad https://orcid.org/0000-0003-3705-2667
  • Bhagawati Prasad Joshi Mathematics Department, Graphic Era Hill University, Bhimtal, India
  • sunil semwal tula's institute, Dehradun India

DOI:

https://doi.org/10.55766/sujst6790

Keywords:

Automatic Control Error (ACE), Load Frequency Control (LFC), Proportional Integral Derivative (PID, Model Predictive Control (MPC)

Abstract

This study aims to examine the use of Proportional Integral Derivative (PID) and Model Predictive Control (MPC) in Load Frequency Control (LFC). A balance between the generation and the load is necessary to ensure the consistency of the electrical supply. These days, MPC techniques are becoming popular due to their merits over conventional PID controllers. In this study, performance of the designed PID and MPC schemes has been tested and compared for two area interconnected power system. This system consists hydro unit in area-1 and three Thermal units in area-2. A step load perturbation scenario in both areas has been obtained to evaluate the effectiveness of the designed control strategies. The results show that both the designed control approaches performed successfully however, the MPC scheme outperform the PID scheme in terms of time domain specifications like reduced oscillation and smaller settling time. It can be concluded that MPC can be used as a secondary controller for LFC applications in future research.

References

Afaneh, T., Mohamed, O., and Abu Elhaija, W. (2022). Load frequency model predictive control of a large-scale multi-source power system. Energies, 15(23):9210. https://doi.org/10.3390/en15239210

Ahmed Khan, I., Mokhlis, H., Mansor, N.N., Illias, H.A., Awalin, L.J., and Wang, L. (2023). New trends and future directions in load frequency control and flexible power system: A comprehensive review. Alexandria Engineering Journal, 71:263-308. https://doi.org/10.1016/j.aej.2023.03.040

Amiri, F., and Hatami, A. (2023). Load frequency control for two-area hybrid microgrids using model predictive control optimized by grey wolf-pattern search algorithm. Soft Computing, 27(23):18227-18243. https://doi.org/10.1007/s00500-023-08077-0

Asuk, A., and Trodden, P. (2023). Feedback optimizing MPC for load frequency control and economic dispatch. IFAC-Papers On Line, 56(2):10935-10940. https://doi.org/10.1016/j.ifacol.2023.10.781

Banis, F., Guericke, D., Madsen, H., and Poulsen, N.K. (2020). Load-frequency control in microgrids using target-adjusted MPC. IET Renewable Power Generation, 14(1):118-124. https://doi.org/10.1049/iet-rpg.2019.0487

Bünning, F., Warrington, J., Heer, P., Smith, R.S., and Lygeros, J. (2022). Robust MPC with data-driven demand forecasting for frequency regulation with heat pumps. Control Engineering Practice, 122:105101. https://doi.org/10.1016/j.conengprac.2022.105101

Das, A., and Sengupta, A. (2024). Model predictive control for resilient frequency management in power systems. Electronics Engineering, 106(5):6131-6157. https://doi.org/10.1007/s00202-024-02352-5

Ersdal, A.M., Fabozzi, D., Imsland, L., and Thornhill, N.F. (2014). Model predictive control for power system frequency control taking into account imbalance uncertainty. IFAC Proceedings Volumes, 47(3):981-986. https://doi.org/10.3182/20140824-6-ZA-1003.01631

Gorbachev, S., Guo, J., Mani, A., Li, L., Li, L., Dou, C., Yue, D., and Zhang, Z. (2023). MPC-based LFC for interconnected power systems with PVA and ESS under model uncertainty and communication delay. Protection and Control of Modern Power Systems, 8(4):1-17. https://doi.org/10.1186/s41601-023-00325-7

Gulzar, M.M., Rizvi, S.T.H., Javed, M.Y., Sibtain, D., and Salah ud Din, R. (2019). Mitigating the load frequency fluctuations of interconnected power systems using model predictive controller. Electronics, 8(2):156. https://doi.org/10.3390/electronics8020156

Hu, Z., Zhang, K., Su, R., and Wang, R. (2024). Robust cooperative load frequency control for enhancing wind energy integration in multi-area power systems. IEEE Transactions on Automation Science and Engineering, 22:1508-1518. https://doi.org/10.1109/TASE.2024.3367030

Khokhar, B., and Parmar, K.P.S. (2022). A novel adaptive intelligent MPC scheme for frequency stabilization of a microgrid considering SoC control of EVs. Applied Energy, 309:118423. https://doi.org/10.1016/j.apenergy.2021.118423

Kumar, N., Tyagi, B., and Kumar, V. (2016). Multi-area AGC scheme using imperialist competition algorithm in restructured power system. Applied Soft Computing, 48:160-168. https://doi.org/10.1016/j.asoc.2016.07.005

Kumar, N., Tyagi, B., and Kumar, V. (2017). Multi-area deregulated automatic generation control scheme of power system using imperialist competitive algorithm based robust controller. IETE Journal of Research, 64(4):528-537. https://doi.org/10.1080/03772063.2017.1362965

Kumar, R., Ashfaq, H., Singh, R., and Kumar, R. (2024). A heuristic approach for insertion of multiple-complex coefficient-filter based DSTATCOM to enhancement of power quality in distribution system. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-024-19778-5

Kumar, R., Diwania, S., Khetrapal, P., and Singh, S. (2022a). Performance assessment of the two metaheuristic techniques and their hybrid for power system stability enhancement with PV-STATCOM. Neural Computing and Applications, 34(5):3723-3744. https://doi.org/10.1007/s00521-021-06637-9

Kumar, R., Diwania, S., Khetrapal, P., Singh, S., and Badoni, M. (2021b). Multimachine stability enhancement with hybrid PSO-BFOA based PV-STATCOM. Sustainable Computing: Informatics and Systems, 32:100615. https://doi.org/10.1016/j.suscom.2021.100615

Kumar, R., Diwania, S., Singh, R., Ashfaq, H., Khetrapal, P., and Singh, S. (2022b). An intelligent hybrid Wind-PV farm as a static compensator for overall stability and control of multimachine power system. ISA Transactions, 123:286-302. https://doi.org/10.1016/j.isatra.2021.05.014

Kumar, R., Singh, R., and Ashfaq, H. (2020). Stability enhancement of multi-machine power systems using Ant Colony Optimization-based static synchronous compensator. Computers and Electrical Engineering, 83:1-17. https://doi.org/10.1016/j.compeleceng.2020.106589

Kumar, R., Singh, R., Ashfaq, H., Singh, S.K., and Badoni, M. (2021a). Power system stability enhancement by damping and control of Sub-synchronous torsional oscillations using Whale Optimization Algorithm-based Type-2 wind turbines. ISA Transactions, 108:240-256. https://doi.org/10.1016/j.isatra.2020.08.037

Liu, X., Zhang, Y., and Lee, K.Y. (2016). Robust distributed MPC for load frequency control of uncertain power systems. Control Engineering Practice, 56:136-147. https://doi.org/10.1016/j.conengprac.2016.08.007

Ma, M., Zhang, C., Liu, X., and Chen, H. (2017). Distributed model predictive load frequency control of the multi-area power system after deregulation. IEEE Transactions on Industrial Electronics, 64(6):5129-5139. https://doi.org/10.1109/TIE.2016.2613923

Mao, T., He, S., Guan, Y., Liu, M., Zhao, W., Wang, T., and Tang, W. (2023). A novel allocation strategy based on the model predictive control of primary frequency regulation power for multiple distributed energy storage aggregators. Energies, 16(17):6140. https://doi.org/10.3390/en16176140

Mohsenian-Rad, A.-H., Wong, V.W.S., Jatskevich, J., Schober, R., and Leon-Garcia, A. (2010). Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1(3):320-331. https://doi.org/10.1109/TSG.2010.2089069

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(2):573. https://doi.org/10.3390/en15020573

Pushkarna, M., Ashfaq, H., Singh, R., and Kumar, R. (2022). A new analytical method for optimal sizing and sitting of Type-IV DG in an unbalanced distribution system considering power loss minimization. Journal of Electrical Engineering & Technology, 17(5):2579-2590. https://doi.org/10.1007/s42835-022-01064-9

Pushkarna, M., Ashfaq, H., Singh, R., and Kumar, R. (2024). An optimal placement and sizing of type-IV DG with reactive power support using UPQC in an unbalanced distribution system using particle swarm optimization. Energy Systems, 15(1):353-370. https://doi.org/10.1007/s12667-022-00551-2

Qi, X., Zheng, J., and Mei, F. (2022). Model predictive control-based load-frequency regulation of grid-forming inverter-based power systems. Frontiers in Energy Research, 10:932788. https://doi.org/10.3389/fenrg.2022.932788

Singh, A., Kumar, N., Joshi, B.P., and Singh, B.K. (2018). Load frequency control with time delay in restructured environment. Journal of Intelligent and Fuzzy Systems, 35(5):4945-4951. https://doi.org/10.3233/JIFS-169778

Yang, D., Wang, B., Cai, G., Ma, J., Tian, J., Chen, Z., and Wang, L. (2020). Inertia-adaptive model predictive control-based load frequency control for interconnected power systems with wind power. IET Renewable Power Generation, 14(8):1146-1154. https://doi.org/10.1049/iet-gtd.2020.0018

Yang, J., Sun, X., Liao, K., He, Z., and Cai, L. (2019). Model predictive control-based load frequency control for power systems with wind turbine generators. IET Renewable Power Generation, 13(15):2871-2879. https://doi.org/10.1049/iet-rpg.2018.6179

Zeng, G.-Q., Xie, X.-Q., and Chen, M.-R. (2017). An adaptive model predictive load frequency control method for multi-area interconnected power systems with photovoltaic generations. Energies, 10(11):1840. https://doi.org/10.3390/en10111840

Zhang, J., Qin, D., Ye, Y., He, Y., Fu, X., Yang, J., Shi, G., and Zhang, H. (2021). Multi-time scale economic scheduling method based on day-ahead robust optimization and intraday MPC rolling optimization for microgrid. IEEE Access, 9:140315-140324. https://doi.org/10.1109/ACCESS.2021.3118716

Zhao, N., Gorbachev, S., Yue, D., Kuzin, V., Dou, C., Zhou, X., and Dai, J. (2022). Model predictive-based frequency control of power system incorporating air-conditioning loads with communication delay. International Journal of Electrical Power & Energy Systems, 138:107856. https://doi.org/10.1016/j.ijepes.2021.107856

Downloads

Published

2025-03-17

How to Cite

Singh, A., Kumar, N., Badoni, M., Kumar, R., Prasad Joshi, B. P. J., & semwal, sunil. (2025). MODEL PREDICTIVE CONTROL (MPC) AND PROPORTIONAL-INTEGRAL-DERIVATIVE (PID) CONTROLLERS FOR LOAD FREQUENCY CONTROL SCHEME: MPC and PID Controllers for Load Frequency Control. Suranaree Journal of Science and Technology, 32(1), 010352(1–14). https://doi.org/10.55766/sujst6790