Comparative Evaluation of Different Hybrid Intelligent Load-Frequency Controllers for Interconnected Electric Power Grids

Authors

  • Diem-Vuong Doan Faculty of Control and Automation, Electric Power University, Vietnam
  • Ngoc-Khoat Nguyen Faculty of Control and Automation, Electric Power University, Vietnam
Volume: 14 | Issue: 2 | Pages: 13173-13180 | April 2024 | https://doi.org/10.48084/etasr.6706

Abstract

Network frequency is considered to be one of the most crucial parameters that strongly affect the stability and economic achievements of interconnected electric power grids. System frequency usually fluctuates and deviates from the nominal values due to random and continuous load changes over time, affecting the electric equipment to significantly decrease efficiency and increase instability. A Load-Frequency Control (LFC) strategy has been proposed to solve this problem. This study compared several different control strategies, namely Fuzzy Particle Swarm Optimization (Fuzzy-PSO), Proportional Integral Derivative (PID), Fuzzy-PID, Fuzzy- Proportional Integral (PI), PSO-PI, and FPID to investigate the effectiveness of intelligent hybrid LFC controllers. The above controllers were simulated on a three-area interconnected power network with the participation of renewable energy sources. Taking into account different load cases, the Fuzzy-PSO-PID controller obtained frequency deviations in the range of 0.0015 to 0.002 Hz. The settling time was about 10 s to reach zero frequency error in each area. With the above controller quality parameters, the Fuzzy-PSO-PID controller provided better quality than the other controllers. A comparative numerical simulation in MATLAB/Simulink for various load change scenarios revealed the effectiveness of hybrid smart controllers, such as the Fuzzy-PID-PSO, outperforming the traditional ones.

Keywords:

Fuzzy-PSO-PID, Fuzzy-PID, Fuzzy-PI, PSO-PI, FPID, RE sources, Load-Frequency Control (LFC)

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How to Cite

[1]
D.-V. Doan and N.-K. Nguyen, “Comparative Evaluation of Different Hybrid Intelligent Load-Frequency Controllers for Interconnected Electric Power Grids”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 2, pp. 13173–13180, Apr. 2024.

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