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A Novel Prairie Dog-Based Meta-Heuristic Optimization Algorithm for Improved Control, Better Transient Response, and

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A new Prairie Dog Optimization (PDO) algorithm effectively tunes controllers for hybrid renewable energy systems (HRESs) in microgrids. This method improves power quality and system stability during disturbances.

Keywords:
batterybee colony optimizationfuel cellhybrid renewable energy sourcesphotovoltaicspower qualityproportional integral (PI)thermal exchange optimization

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Renewable Energy Systems

Background:

  • Growing electricity demand necessitates reliable power grids.
  • Hybrid Renewable Energy Systems (HRESs) offer improved reliability and reduced losses in microgrids (MGs).
  • Efficient controllers are crucial for managing HRES integration and mitigating power quality (PQ) issues.

Purpose of the Study:

  • To propose a novel Prairie Dog Optimization (PDO) algorithm for tuning Proportional Integral (PI) controllers in PV-, FC-, and battery-based HRESs.
  • To evaluate the effectiveness of the PDO algorithm in compensating load demand and mitigating PQ problems within an MG system.
  • To demonstrate the superiority of the PDO algorithm compared to existing optimization techniques.

Main Methods:

  • Development of a MATLAB/Simulink model for a PV-, FC-, and battery-based HRES.
  • Implementation of the Prairie Dog Optimization (PDO) algorithm to tune PI controller parameters.
  • Testing the MG system under various intentional PQ disturbances (swell, unbalanced load, oscillatory transient, notch).
  • Comparative analysis with Bee Colony Optimization (BCO), thermal exchange optimization, and PI techniques.

Main Results:

  • The PDO algorithm achieved optimal PI controller gains for effective load compensation and PQ mitigation.
  • Simulation results demonstrated significant improvements in Total Harmonic Distortion (THD) minimization.
  • Enhanced control of active and reactive power, improved power factor, and reduced voltage deviation were observed.
  • Stable terminal voltage, DC-link voltage, grid voltage, and grid current were maintained during PQ faults.

Conclusions:

  • The proposed PDO algorithm is efficient and robust for optimizing PI controllers in HRES-based MGs.
  • PDO significantly enhances overall system operation, power quality, and stability.
  • The PDO method shows strong potential for real-time implementation in microgrid applications.