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Fuzzy analytic hierarchy process based generation management for interconnected power system.

T Varshney1, A V Waghmare2, V P Singh2

  • 1Department of EECE, SSET, Sharda University, Greater Noida, Uttar Pradesh, 201310, India.

Scientific Reports
|May 20, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a Fuzzy Analytic Hierarchy Process (FAHP) to optimize automatic generation control (AGC) in two-area power systems. The method effectively weights sub-objective functions for improved PID controller performance.

Keywords:
AGCAHPFuzzy AHPJaya optimization algorithmPID controllerPower system

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Optimization Techniques

Background:

  • Decision-making involves complex attribute assessment and weight determination.
  • Automatic Generation Control (AGC) in two-area power systems (2-APS) requires balancing multiple objectives.
  • Existing methods may not adequately handle the multi-attribute nature of AGC optimization.

Purpose of the Study:

  • To propose a Fuzzy Analytic Hierarchy Process (FAHP) for determining weights of sub-objective functions in AGC.
  • To design a Proportional-Integral-Derivative (PID) controller optimized using these weights.
  • To evaluate the performance of the proposed controller against other optimization algorithms.

Main Methods:

  • Utilized FAHP, a multi-attribute decision-making (MADM) technique, to assign weights to integral-time-absolute-errors (ITAE) of tie-line power fluctuation, frequency deviations, and area control errors.
  • Integrated FAHP-derived weights into a single objective function for PID controller design.
  • Employed the Jaya Optimization Algorithm (JOA) for optimizing the objective function, comparing it with Sine Cosine Algorithm (SCA), Luus-Jaakola Algorithm (LJA), Nelder-Mead Simplex Algorithm (NMSA), Symbiotic Organism Search Algorithm (SOSA), and Elephant Herding Optimization Algorithm (EHOA).

Main Results:

  • The Jaya Optimization Algorithm (JOA)-based PID controller demonstrated effective performance in automatic generation control under various load conditions.
  • Experimental data and statistical analysis, including Friedman rank test, validated the superiority of the JOA-based controller.
  • The FAHP method successfully integrated multiple performance criteria into a single objective function for controller optimization.

Conclusions:

  • The proposed FAHP-based approach provides an effective framework for optimizing AGC in 2-APS.
  • The JOA is a robust optimization algorithm for tuning PID controllers in power systems.
  • This study offers a valuable contribution to the field of power system stability and control.