Quantum Inspired Evolutionary Algorithm in Load Frequency Control of Multi-area Interconnected Thermal Power System with Non-linearity

  • K. Jagatheesan
  • Sourav Samanta
  • Alokeparna Choudhury
  • Nilanjan Dey
  • B. Anand
  • Amira S. Ashour
Chapter
Part of the Studies in Big Data book series (SBD, volume 33)

Abstract

Load Frequency Control (LFC) is an important issue in power system to maintain power system stability and quality of generated power supply during sudden load demand period. In order to overcome this issue, power systems are interconnected and secondary controllers are introduced to regulate the power system parameters within a specified limit during sudden load demand period. In this present work, three area single stage reheat thermal power systems are interconnected and each area comprises governor unit, reheated unit, turbine unit, Governor Dead Band (GDB), Generation Rate Constraint (GRC) non-linear components and boiler dynamics effect. One Percent (1%) Step Load Perturbation (SLP) is considered in thermal area 1 of the investigated power system. The Proportional-Integral-Derivative (PID) controller is introduced as a secondary controller. Since tuning of the controller gain values play a vital role, evolutionary algorithms are introduced to tune the controller gain values. In the current work, the Genetic Algorithm (GA), Quantum Inspired Genetic Algorithm (QIGA) and Quantum Inspired Evolutionary Algorithm (QIEA) are proposed for tuning of controller gain values. The cumulative comparisons of the simulation result are clearly reported that QIGA and QIEA are more superior to the GA based PID controller performance in the same investigated power system in terms of time domain specification parameters.

Keywords

Load frequency control Interconnected power system Genetic algorithm Quantum inspired genetic algorithm Quantum inspired evolutionary algorithm Step load perturbation Objective function Optimal gain values Time domain specification 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • K. Jagatheesan
    • 1
  • Sourav Samanta
    • 2
  • Alokeparna Choudhury
    • 3
  • Nilanjan Dey
    • 4
  • B. Anand
    • 5
  • Amira S. Ashour
    • 6
  1. 1.Department of EEEMahendra Institute of Engineering and TechnologyNamakkalIndia
  2. 2.Department of CSEUniversity Institute of TechnologyBurdwanIndia
  3. 3.Department of CSSt. Xavier’s College BurdwanBurdwanIndia
  4. 4.Department of Information TechnologyTechno India College of TechnologyKolkataIndia
  5. 5.Department of EEEHindusthan College of Engineering and TechnologyCoimbatoreIndia
  6. 6.Faculty of Engineering, Department of Electronics and Electrical Communications EngineeringTanta UniversityTantaEgypt

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