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Line Overload Alleviations in Wind Energy Integrated Power Systems Using Automatic Generation Control

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  • Kaleem Ullah

    (US-Pakistan Center for Advanced Study in Energy, University of Engineering and Technology Peshawar, Peshawar 25000, Pakistan)

  • Abdul Basit

    (US-Pakistan Center for Advanced Study in Energy, University of Engineering and Technology Peshawar, Peshawar 25000, Pakistan)

  • Zahid Ullah

    (Department of Electrical Engineering, University of Management and Technology Lahore, Sialkot Campus, Sialkot 51310, Pakistan)

  • Rafiq Asghar

    (Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang (UMP), Pekan 26600, Malaysia)

  • Sheraz Aslam

    (Department of Electrical Engineering, Computer Engineering and Informatics, Cyprus University of Technology, Limassol 3036, Cyprus)

  • Ayman Yafoz

    (Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Modern power systems are largely based on renewable energy sources, especially wind power. However, wind power, due to its intermittent nature and associated forecasting errors, requires an additional amount of balancing power provided through the automatic generation control (AGC) system. In normal operation, AGC dispatch is based on the fixed participation factor taking into account only the economic operation of generating units. However, large-scale injection of additional reserves results in large fluctuations of line power flows, which may overload the line and subsequently reduce the system security if AGC follows the fixed participation factor’s criteria. Therefore, to prevent the transmission line overloading, a dynamic dispatch strategy is required for the AGC system considering the capacities of the transmission lines along with the economic operation of generating units. This paper proposes a real-time dynamic AGC dispatch strategy, which protects the transmission line from overloading during the power dispatch process in an active power balancing operation. The proposed method optimizes the control of the AGC dispatch order to prevent power overflows in the transmission lines, which is achieved by considering how the output change of each generating unit affects the power flow in the associated bus system. Simulations are performed in Dig SILENT software by developing a 5 machine 8 bus Pakistan’s power system model integrating thermal power plant units, gas turbines, and wind power plant systems. Results show that the proposed AGC design efficiently avoids the transmission line congestions in highly wind-integrated power along with the economic operation of generating units.

Suggested Citation

  • Kaleem Ullah & Abdul Basit & Zahid Ullah & Rafiq Asghar & Sheraz Aslam & Ayman Yafoz, 2022. "Line Overload Alleviations in Wind Energy Integrated Power Systems Using Automatic Generation Control," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:11810-:d:919551
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    References listed on IDEAS

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    1. Aslam, Sheraz & Herodotou, Herodotos & Mohsin, Syed Muhammad & Javaid, Nadeem & Ashraf, Nouman & Aslam, Shahzad, 2021. "A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. Kaleem Ullah & Abdul Basit & Zahid Ullah & Sheraz Aslam & Herodotos Herodotou, 2021. "Automatic Generation Control Strategies in Conventional and Modern Power Systems: A Comprehensive Overview," Energies, MDPI, vol. 14(9), pages 1-43, April.
    3. Amil Daraz & Suheel Abdullah Malik & Athar Waseem & Ahmad Taher Azar & Ihsan Ul Haq & Zahid Ullah & Sheraz Aslam, 2021. "Automatic Generation Control of Multi-Source Interconnected Power System Using FOI-TD Controller," Energies, MDPI, vol. 14(18), pages 1-18, September.
    4. Kaleem Ullah & Abdul Basit & Zahid Ullah & Fahad R. Albogamy & Ghulam Hafeez, 2022. "Automatic Generation Control in Modern Power Systems with Wind Power and Electric Vehicles," Energies, MDPI, vol. 15(5), pages 1-24, February.
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    Cited by:

    1. Iqrar Hussain & Aun Haider & Zahid Ullah & Mario Russo & Giovanni Mercurio Casolino & Babar Azeem, 2023. "Comparative Analysis of Eight Numerical Methods Using Weibull Distribution to Estimate Wind Power Density for Coastal Areas in Pakistan," Energies, MDPI, vol. 16(3), pages 1-18, February.
    2. Kaleem Ullah & Zahid Ullah & Sheraz Aslam & Muhammad Salik Salam & Muhammad Asjad Salahuddin & Muhammad Farooq Umer & Mujtaba Humayon & Haris Shaheer, 2023. "Wind Farms and Flexible Loads Contribution in Automatic Generation Control: An Extensive Review and Simulation," Energies, MDPI, vol. 16(14), pages 1-34, July.
    3. Ahmad Saeed & Ebrahim Shahzad & Adnan Umar Khan & Athar Waseem & Muhammad Iqbal & Kaleem Ullah & Sheraz Aslam, 2023. "Three-Pond Model with Fuzzy Inference System-Based Water Level Regulation Scheme for Run-of-River Hydropower Plant," Energies, MDPI, vol. 16(6), pages 1-29, March.

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