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Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution

Author

Listed:
  • Naila

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

  • Shaikh Saaqib Haroon

    (Department of Electrical Engineering, University of Engineering & Technology, Taxila 47050, Pakistan)

  • Shahzad Hassan

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

  • Salman Amin

    (Department of Electrical Engineering, University of Engineering & Technology, Taxila 47050, Pakistan)

  • Intisar Ali Sajjad

    (Department of Electrical Engineering, University of Engineering & Technology, Taxila 47050, Pakistan)

  • Asad Waqar

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

  • Muhammad Aamir

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

  • Muneeb Yaqoob

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

  • Imtiaz Alam

    (Department of Electrical Engineering, Bahria University, Islamabad 44000, Pakistan)

Abstract

This paper presents an optimization method for solving the Power Economic Dispatch (PED) problem of thermal generation units with multiple fuels and valve point loadings. The proposed optimizer is a variant of Differential Evolution (DE) characterized as a Stud Differential Evolution (SDE), which has been proposed earlier and implemented on a hydrothermal energy system. In SDE, an operator named Stud Crossover (SC) is introduced in the conventional DE during the trial vector updating process. In SC operator, a best vector gives its optimal information to all other population members through mating. The proposed algorithm’s effectiveness to solve Multiple Fuel PED problem, with and without Valve Point Loading Effects (VPLEs), has been validated by testing it on 10 machine multiple fuel standard test systems having 2400 MW, 2500 MW, 2600 MW, and 2700 MW load demands. The results depict the strength of SDE over various other methods in the literature.

Suggested Citation

  • Naila & Shaikh Saaqib Haroon & Shahzad Hassan & Salman Amin & Intisar Ali Sajjad & Asad Waqar & Muhammad Aamir & Muneeb Yaqoob & Imtiaz Alam, 2018. "Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution," Energies, MDPI, vol. 11(6), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1393-:d:149704
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    References listed on IDEAS

    as
    1. Qun Niu & Zhuo Zhou & Hong-Yun Zhang & Jing Deng, 2012. "An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects," Energies, MDPI, vol. 5(9), pages 1-19, September.
    2. Secui, Dinu Calin, 2016. "A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 113(C), pages 366-384.
    3. Adarsh, B.R. & Raghunathan, T. & Jayabarathi, T. & Yang, Xin-She, 2016. "Economic dispatch using chaotic bat algorithm," Energy, Elsevier, vol. 96(C), pages 666-675.
    4. Vo, Dieu Ngoc & Ongsakul, Weerakorn, 2012. "Economic dispatch with multiple fuel types by enhanced augmented Lagrange Hopfield network," Applied Energy, Elsevier, vol. 91(1), pages 281-289.
    5. Modiri-Delshad, Mostafa & Aghay Kaboli, S. Hr. & Taslimi-Renani, Ehsan & Rahim, Nasrudin Abd, 2016. "Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options," Energy, Elsevier, vol. 116(P1), pages 637-649.
    6. Kheshti, Mostafa & Kang, Xiaoning & Bie, Zhaohong & Jiao, Zaibin & Wang, Xiuli, 2017. "An effective Lightning Flash Algorithm solution to large scale non-convex economic dispatch with valve-point and multiple fuel options on generation units," Energy, Elsevier, vol. 129(C), pages 1-15.
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