Load-Frequency Control in a Two-Area Power System Using the Fuzzy-PID Method
Main Article Content
Abstract
Power systems are plant units connected to each other, with the electrical power flow constantly moving between them and the load. All systems must be implemented in such a way that they remain stable not only under normal conditions but also after the implementation of unwanted inputs or malfunctions and should be able to return to stable nominal conditions as soon as possible. The basic factors of stability control in a power system are the frequency of different areas and the amount of power flow between them. Now that the main goals of stability control in a power system have been stated, these indicators must be kept at their desired levels through the design and implementation of controllers. This paper first describes the mechanism of load frequency control (LFC). The parameters of several types of complementary controllers are then designed based on the proposed algorithm. The controllers designed on the simulated power system are finally applied, and the effect of each controller on faster damping of frequency fluctuations is discussed. In this study, a multi-area power system is simulated and the effect of disturbance in each area and the performance of the proposed controller in controlling the frequency of the whole network are investigated. The case studies show that the share of active and reactive power generation sources in each region have the greatest impact on frequency control, given that the proposed control coefficients are determined using fuzzy logic in the shortest possible time and the number of transient oscillations eliminated, resulting in a steady system.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
- Creative Commons Copyright License
The journal allows readers to download and share all published articles as long as they properly cite such articles; however, they cannot change them or use them commercially. This is classified as CC BY-NC-ND for the creative commons license.
- Retention of Copyright and Publishing Rights
The journal allows the authors of the published articles to hold copyrights and publishing rights without restrictions.
References
H. Alhelou, M.-E. Hamedani-Golshan, R. Zamani, E. Heydarian-Forushani, and P. Siano, “Challenges and opportunities of load frequency control in conventional, modern and future smart power systems: A comprehensive review,” Energies, vol. 11, no. 10, 2018, Art. no. 2497.
Z. Yan and Y. Xu, “Data-driven load frequency control for stochastic power systems: A deep reinforcement learning method with continuous action search,” IEEE Transactions on Power Systems, vol. 34, no. 2, pp. 1653–1656, Mar. 2019.
C. Chen, M. Cui, X. Fang, B. Ren, and Y. Chen, “Load altering attack-tolerant defense strategy for load frequency control system,” Applied Energy, vol. 280, Dec. 2020, Art. no. 116015.
M.-H. Khooban, T. Niknam, M. Shasadeghi, T. Dragicevic, and F. Blaabjerg, “Load frequency control in microgrids based on a stochastic noninteger controller,” IEEE Transactions on Sustainable Energy, vol. 9, no. 2, pp. 853–861, Apr. 2018.
J. Li, T. Yu, and X. Zhang, “Coordinated load frequency control of multi-area integrated energy system using multi-agent deep reinforcement learning,” Applied Energy, vol. 306, Jan. 2022, Art. no. 117900.
X. Shang-Guan, Y. He, C. Zhang, L. Jiang, J. W. Spencer, and M. Wu, “Sampled-data based discrete and fast load frequency control for power systems with wind power,” Applied Energy, vol. 259, Feb. 2020, Art. no. 114202.
M.-H. Khooban, T. Dragicevic, F. Blaabjerg, and M. Delimar, “Shipboard microgrids: A novel approach to load frequency control,” IEEE Transactions on Sustainable Energy, vol. 9, no. 2, pp. 843–852, Apr. 2018.
D. Yu, H. Zhu, W. Han, and D. Holburn, “Dynamic multi agent-based management and load frequency control of PV/fuel cell/ wind turbine/ CHP in autonomous microgrid system,” Energy, vol. 173, pp. 554–568, Apr. 2019.
M.-H. Khooban, “Secondary load frequency control of time-delay stand-alone microgrids with electric vehicles,” IEEE Transactions on Industrial Electronics, vol. 65, no. 9, pp. 7416–7422, Sep. 2018.
H. Zhang, J. Liu, and S. Xu, “H-infinity load frequency control of networked power systems via an event-triggered scheme,” IEEE Transactions on Industrial Electronics, vol. 67, no. 8, pp. 7104–7113, Aug. 2020.
A. Abbaspour, A. Sargolzaei, P. Forouzannezhad, K. K. Yen, and A. I. Sarwat, “Resilient control design for load frequency control system under false data injection attacks,” IEEE Transactions on Industrial Electronics, vol. 67, no. 9, pp. 7951–7962, Sep. 2020.
A. Abazari, H. Monsef, and B. Wu, “Coordination strategies of distributed energy resources including FESS, DEG, FC and WTG in load frequency control (LFC) scheme of hybrid isolated micro-grid,” International Journal of Electrical Power & Energy Systems, vol. 109, pp. 535–547, Jul. 2019.
K. Lu, W. Zhou, G. Zeng, and Y. Zheng, “Constrained population extremal optimization-based robust load frequency control of multi-area interconnected power system,” International Journal of Electrical Power & Energy Systems, vol. 105, pp. 249–271, Feb. 2019.
H. Luo, I. A. Hiskens, and Z. Hu, “Stability analysis of load frequency control systems with sampling and transmission delay,” IEEE Transactions on Power Systems, vol. 35, no. 5, pp. 3603–3615, Sep. 2020.
J. Khalid, M. A. Ramli, M. S. Khan, and T. Hidayat, “Efficient load frequency control of renewable integrated power system: A twin delayed DDPG-based deep reinforcement learning approach,” IEEE Access, vol. 10, pp. 51 561–51 574, 2022.
Z. Wang and Y. Liu, “Adaptive terminal sliding mode based load frequency control for multi-area interconnected power systems with PV and energy storage,” IEEE Access, vol. 9, pp. 120 185–120 192, 2021.
X.-C. Shangguan, Y. He, C.-K. Zhang, L. Jin, W. Yao, L. Jiang, and M. Wu, “Control performance standards-oriented event-triggered load frequency control for power systems under limited communication bandwidth,” IEEE Transactions on Control Systems Technology, vol. 30, no. 2, pp. 860–868, Mar. 2022.
K. S. Xiahou, Y. Liu, and Q. H. Wu, “Robust load frequency control of power systems against random time-delay attacks,” IEEE Transactions on Smart Grid, vol. 12, no. 1, pp. 909–911, Jan. 2021.
M. Gheisarnejad, “An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control,” Applied Soft Computing, vol. 65, pp. 121–138, Apr. 2018.
N. Jalali, H. Razmi, and H. Doagou-Mojarrad, “Optimized fuzzy self-tuning PID controller design based on tribe-DE optimization algorithm and rule weight adjustment method for load frequency control of interconnected multi-area power systems,” Applied Soft Computing, vol. 93, Aug. 2020, Art. no. 106424.
J. R. Nayak, B. Shaw, and B. K. Shahu, “Load frequency control of hydro-thermal power system using fuzzy PID controller optimized by hybrid DECRPSO algorithm,” International Journal of Pure and Applied Mathematics, vol. 114, no. 9, pp. 147–155, 2017.
X. Jin, K. Chen, Y. Zhao, J. Ji, and P. Jing, “Simulation of hydraulic transplanting robot control system based on fuzzy PID controller,” Measurement, vol. 164, Nov. 2020, Art. no. 108023.
Y. Wang, Q. Jin, and R. Zhang, “Improved fuzzy PID controller design using predictive functional control structure,” ISA Transactions, vol. 71, pp. 354–363, Nov. 2017.
D. Somwanshi, M. Bundele, G. Kumar, and G. Parashar, “Comparison of fuzzy-PID and PID controller for speed control of DC motor using LabVIEW,” Procedia Computer Science, vol. 152, pp. 252–260, 2019.
G. Chen, Z. Li, Z. Zhang, and S. Li, “An improved ACO algorithm optimized fuzzy PID controller for load frequency control in multi area interconnected power systems,” IEEE Access, vol. 8, pp. 6429–6447, 2020.