IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1771-d760323.html
   My bibliography  Save this article

Automatic Generation Control in Modern Power Systems with Wind Power and Electric Vehicles

Author

Listed:
  • 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)

  • Fahad R. Albogamy

    (Computer Sciences Program, Turabah University College, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Ghulam Hafeez

    (Department of Electrical Engineering, University of Engineering and Technology, Mardan 23200, Pakistan)

Abstract

The modern power system is characterized by the massive integration of renewables, especially wind power. The intermittent nature of wind poses serious concerns for the system operator owing to the inaccuracies in wind power forecasting. Forecasting errors require more balancing power for maintaining frequency within the nominal range. These services are now offered through conventional power plants that not only increase the operational cost but also adversely affect the environment. The modern power system emphasizes the massive penetration of wind power that will replace conventional power plants and thereby impact the provision of system services from conventional power plants. Therefore, there is an emergent need to find new control and balancing solutions, such as regulation reserves from wind power plants and electric vehicles, without trading off their natural behaviors. This work proposes real-time optimized dispatch strategies for automatic generation control (AGC) to utilize wind power and the storage capacity of electric vehicles for the active power balancing services of the grid. The proposed dispatch strategies enable the AGC to appropriately allocate the regulating reserves from wind power plants and electric vehicles, considering their operational constraints. Simulations are performed in DIgSILENT software by developing a power system AGC model integrating the generating units and an EVA model. The inputs for generating units are considered by selecting a particular day of the year 2020, when wind power plants are generating high power. Different coordinated dispatch strategies are proposed for the AGC model to incorporate the reserve power from wind power plants and EVs. The performance of the proposed dispatch strategies is accessed and discussed by obtaining responses of the generating units and EVs during the AGC operation to counter the initial power imbalances in the network. The results reveal that integration of wind power and electric vehicles alongside thermal power plants can effectively reduce real-time power imbalances acquainted in power systems due to massive penetration of wind power that subsequently improves the power system security. Moreover, the proposed dispatch strategy reduces the operational cost of the system by allowing the conventional power plant to operate at their lower limits and therefore utilizes minimum reserves for the active power balancing services.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1771-:d:760323
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1771/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/5/1771/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Guille, Christophe & Gross, George, 2009. "A conceptual framework for the vehicle-to-grid (V2G) implementation," Energy Policy, Elsevier, vol. 37(11), pages 4379-4390, November.
    3. Rahmat Khezri & Arman Oshnoei & Mehrdad Tarafdar Hagh & SM Muyeen, 2018. "Coordination of Heat Pumps, Electric Vehicles and AGC for Efficient LFC in a Smart Hybrid Power System via SCA-Based Optimized FOPID Controllers," Energies, MDPI, vol. 11(2), pages 1-21, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Hiramani Shukla & Srete Nikolovski & More Raju & Ankur Singh Rana & Pawan Kumar, 2022. "A Particle Swarm Optimization Technique Tuned TID Controller for Frequency and Voltage Regulation with Penetration of Electric Vehicles and Distributed Generations," Energies, MDPI, vol. 15(21), pages 1-32, November.
    3. 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.
    4. 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.
    5. Matheus Sene Paulo & Andrei de Oliveira Almeida & Pedro Machado de Almeida & Pedro Gomes Barbosa, 2023. "Control of an Offshore Wind Farm Considering Grid-Connected and Stand-Alone Operation of a High-Voltage Direct Current Transmission System Based on Multilevel Modular Converters," Energies, MDPI, vol. 16(16), pages 1-27, August.
    6. Yuxuan Wang & Bingxu Zhang & Chenyang Li & Yongzhang Huang, 2022. "Collaborative Robust Optimization Strategy of Electric Vehicles and Other Distributed Energy Considering Load Flexibility," Energies, MDPI, vol. 15(8), pages 1-22, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Zahid Ullah & Kaleem Ullah & Cesar Diaz-Londono & Giambattista Gruosso & Abdul Basit, 2023. "Enhancing Grid Operation with Electric Vehicle Integration in Automatic Generation Control," Energies, MDPI, vol. 16(20), pages 1-18, October.
    3. Mubbashir Ali & Jussi Ekström & Matti Lehtonen, 2018. "Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems," Energies, MDPI, vol. 11(5), pages 1-11, May.
    4. Chaouachi, Aymen & Bompard, Ettore & Fulli, Gianluca & Masera, Marcelo & De Gennaro, Michele & Paffumi, Elena, 2016. "Assessment framework for EV and PV synergies in emerging distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 719-728.
    5. Kley, Fabian & Lerch, Christian & Dallinger, David, 2011. "New business models for electric cars--A holistic approach," Energy Policy, Elsevier, vol. 39(6), pages 3392-3403, June.
    6. Guo, Shiliang & Li, Pengpeng & Ma, Kai & Yang, Bo & Yang, Jie, 2022. "Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles," Applied Energy, Elsevier, vol. 325(C).
    7. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    8. Jayawardena, A.V. & Meegahapola, L.G. & Robinson, D.A. & Perera, S., 2015. "Microgrid capability diagram: A tool for optimal grid-tied operation," Renewable Energy, Elsevier, vol. 74(C), pages 497-504.
    9. Luo, Lizi & Wu, Zhi & Gu, Wei & Huang, He & Gao, Song & Han, Jun, 2020. "Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction," Energy, Elsevier, vol. 192(C).
    10. Galus, Matthias D. & Zima, Marek & Andersson, Göran, 2010. "On integration of plug-in hybrid electric vehicles into existing power system structures," Energy Policy, Elsevier, vol. 38(11), pages 6736-6745, November.
    11. Schill, Wolf-Peter, 2011. "Electric Vehicles in Imperfect Electricity Markets: The case of Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39(10), pages 6178-6189.
    12. Héctor Migallón & Akram Belazi & José-Luis Sánchez-Romero & Héctor Rico & Antonio Jimeno-Morenilla, 2020. "Settings-Free Hybrid Metaheuristic General Optimization Methods," Mathematics, MDPI, vol. 8(7), pages 1-25, July.
    13. Luo, Qingsong & Zhou, Yimin & Hou, Weicheng & Peng, Lei, 2022. "A hierarchical blockchain architecture based V2G market trading system," Applied Energy, Elsevier, vol. 307(C).
    14. van der Kam, Mart & van Sark, Wilfried, 2015. "Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study," Applied Energy, Elsevier, vol. 152(C), pages 20-30.
    15. Carreiro, Andreia M. & Jorge, Humberto M. & Antunes, Carlos Henggeler, 2017. "Energy management systems aggregators: A literature survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1160-1172.
    16. Schücking, Maximilian & Jochem, Patrick & Fichtner, Wolf & Wollersheim, Olaf & Stella, Kevin, 2017. "Charging strategies for economic operations of electric vehicles in commercial applications," MPRA Paper 91599, University Library of Munich, Germany.
    17. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    18. David Wozabal & Christoph Graf & David Hirschmann, 2016. "The effect of intermittent renewables on the electricity price variance," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 687-709, July.
    19. Da Xie & Haoxiang Chu & Yupu Lu & Chenghong Gu & Furong Li & Yu Zhang, 2015. "The Concept of EV’s Intelligent Integrated Station and Its Energy Flow," Energies, MDPI, vol. 8(5), pages 1-28, May.
    20. Solomon Feleke & Raavi Satish & Workagegn Tatek & Almoataz Y. Abdelaziz & Adel El-Shahat, 2022. "DE-Algorithm-Optimized Fuzzy-PID Controller for AGC of Integrated Multi Area Power System with HVDC Link," Energies, MDPI, vol. 15(17), pages 1-21, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1771-:d:760323. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.