IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6028-d640685.html
   My bibliography  Save this article

An Optimal Energy Management System for University Campus Using the Hybrid Firefly Lion Algorithm (FLA)

Author

Listed:
  • Haneef Ullah

    (Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Murad Khan

    (Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Irshad Hussain

    (Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Ibrar Ullah

    (Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Peerapong Uthansakul

    (School of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Naeem Khan

    (Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

Abstract

As the world population and its dependency on energy is growing exponentially day by day, the existing energy generating resources are not enough to fulfill their needs. In the conventional grid system, most of the generated energy is wasted because of improper demand side management (DSM). This leads to a difficulty in keeping the equilibrium between the user need and electric power production. To overcome these difficulties, smart grid (SG) is introduced, which is composed of the integration of two-way communication between the user and utility. To utilize the existing energy resources in a better way, SG is the best option since a large portion of the generated energy is consumed by the educational institutes. Such institutes also need un-interrupted power supply at the lowest cost. Therefore, in this paper, we have taken a university campus load. We have not only applied two bio-inspired heuristic algorithms for energy scheduling—namely, the Firefly Algorithm (FA) and the Lion Algorithm (LA)—but also proposed a hybrid version, FLA, for more optimal results. Our main objectives are a reduction in both, that is, the cost of energy and the waiting time of consumers or end users. For this purpose, in our proposed model, we have divided all appliances into two categories—shiftable appliances and non-shiftable appliances. Shiftable appliances are feasible to be used in any of the time slots and can be planned according to the day-ahead pricing signal (DAP), provided by the utility, while non-shiftable appliances can be used for a specified duration and cannot be planned with the respective DAP signal. So, we have scheduled shiftable appliances only. We have also used renewable energy sources (RES) for achieving maximum end user benefits. The simulation results show that our proposed hybrid algorithm, FLA, has reduced the cost excellently. We have also taken into consideration the consumers’ waiting times, due to scheduling of appliances.

Suggested Citation

  • Haneef Ullah & Murad Khan & Irshad Hussain & Ibrar Ullah & Peerapong Uthansakul & Naeem Khan, 2021. "An Optimal Energy Management System for University Campus Using the Hybrid Firefly Lion Algorithm (FLA)," Energies, MDPI, vol. 14(19), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6028-:d:640685
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6028/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6028/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Awais Manzoor & Nadeem Javaid & Ibrar Ullah & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2017. "An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes," Energies, MDPI, vol. 10(9), pages 1-28, August.
    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. Satish Suresh Tanavade & Ganesh Nagraj Patil & C. V. Sudhir & A. M. Saravanan, 2023. "Strategic Energy Management and Carbon Footprint Reduction in University Campuses: A Comprehensive Review," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 15-27, November.
    2. Ibrar Ullah & Irshad Hussain & Khalid Rehman & Piotr Wróblewski & Wojciech Lewicki & Balasubramanian Prabhu Kavin, 2022. "Exploiting the Moth–Flame Optimization Algorithm for Optimal Load Management of the University Campus: A Viable Approach in the Academia Sector," Energies, MDPI, vol. 15(10), pages 1-27, May.
    3. Hongli Liu & Luoqi Wang & Ji Li & Lei Shao & Delong Zhang, 2023. "Research on Smart Power Sales Strategy Considering Load Forecasting and Optimal Allocation of Energy Storage System in China," Energies, MDPI, vol. 16(8), pages 1-18, 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. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
    2. Godiana Hagile Philipo & Josephine Nakato Kakande & Stefan Krauter, 2022. "Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping," Energies, MDPI, vol. 15(14), pages 1-18, July.
    3. Huiru Zhao & Hao Lu & Bingkang Li & Xuejie Wang & Shiying Zhang & Yuwei Wang, 2020. "Stochastic Optimization of Microgrid Participating Day-Ahead Market Operation Strategy with Consideration of Energy Storage System and Demand Response," Energies, MDPI, vol. 13(5), pages 1-16, March.
    4. M. Bilal Nasir & Asif Hussain & Kamran Ali Khan Niazi & Mashood Nasir, 2022. "An Optimal Energy Management System (EMS) for Residential and Industrial Microgrids," Energies, MDPI, vol. 15(17), pages 1-18, August.
    5. Andrzej Ożadowicz, 2017. "A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies," Energies, MDPI, vol. 10(11), pages 1-22, November.
    6. Hafiz Majid Hussain & Nadeem Javaid & Sohail Iqbal & Qadeer Ul Hasan & Khursheed Aurangzeb & Musaed Alhussein, 2018. "An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid," Energies, MDPI, vol. 11(1), pages 1-28, January.

    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:14:y:2021:i:19:p:6028-:d:640685. 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.