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

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Quantum Computing:An Environment for Intelligent Large Scale Real Application

Part of the book series: Studies in Big Data ((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.

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Authors and Affiliations

  1. Department of EEE, Mahendra Institute of Engineering and Technology, Namakkal, Tamilnadu, India

    K. Jagatheesan

  2. Department of CSE, University Institute of Technology, Burdwan, Westbengal, India

    Sourav Samanta

  3. Department of CS, St. Xavier’s College Burdwan, Burdwan, Westbengal, India

    Alokeparna Choudhury

  4. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

  5. Department of EEE, Hindusthan College of Engineering and Technology, Coimbatore, Tamilnadu, India

    B. Anand

  6. Faculty of Engineering, Department of Electronics and Electrical Communications Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

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  5. B. Anand
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  1. Faculty of Computers and Information, Cairo University , Cairo, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computer and Information Sciences, Mansoura University, Mansoura, Egypt

    Mohamed Elhoseny

  3. Systems Research Institute, Polish Academy of Sciences , Warsaw, Poland

    Janusz Kacprzyk

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Jagatheesan, K., Samanta, S., Choudhury, A., Dey, N., Anand, B., Ashour, A.S. (2018). Quantum Inspired Evolutionary Algorithm in Load Frequency Control of Multi-area Interconnected Thermal Power System with Non-linearity. In: Hassanien, A., Elhoseny, M., Kacprzyk, J. (eds) Quantum Computing:An Environment for Intelligent Large Scale Real Application . Studies in Big Data, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-319-63639-9_16

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