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A Novel Evolving Framework for Energy Management in Combined Heat and Electricity Systems with Demand Response Programs

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Listed:
  • Ting Chen

    (Department of Electric Power Engineering, Fujian Vocational & Technical College of Water Conservancy & Electric Power, Yong’an 366000, China)

  • Lei Gan

    (State Grid Hubei Shiyan Power Supply Company, Shiyan 442000, China)

  • Sheeraz Iqbal

    (Department of Electrical Engineering, University of Azad Jammu and Kashmir, Muzaffarabad 13100, Pakistan)

  • Marek Jasiński

    (WWSIS “Horyzont”, 54-239 Wrocław, Poland)

  • Mohammed A. El-Meligy

    (Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Mohamed Sharaf

    (Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Samia G. Ali

    (Department of Electrical Power and Machines, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt)

Abstract

In recent years, demand response programs (DRPs) have become an effective method of encouraging users to participate in energy system operations. The problem of optimal energy flow (OEF) is a complex challenge in multiple power systems. Accordingly, this study aims to propose a novel evolving framework for optimal OEF operation of an electricity, heat, and gas integrating system, taking into account flexible heat and electricity demands. To this end, a switching idea between input energy carriers has been introduced to combine the traditional DRP with demand-side energy supply management. Switching between the feeding energy carriers could change how power is supplied to the end users and thus would affect the total cost of the grid. Operators of integrated systems minimize the operational costs associated with supplying flexible power to users in this study. Considering the high nonlinearity of the problem, a novel optimization algorithm is presented for solving the complex OEF based on the improved teaching–learning-based optimization algorithm (ITLBOA). According to the outcomes, flexible DRP reduces operational prices and smooths power demand curves for power and heating networks.

Suggested Citation

  • Ting Chen & Lei Gan & Sheeraz Iqbal & Marek Jasiński & Mohammed A. El-Meligy & Mohamed Sharaf & Samia G. Ali, 2023. "A Novel Evolving Framework for Energy Management in Combined Heat and Electricity Systems with Demand Response Programs," Sustainability, MDPI, vol. 15(13), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10481-:d:1186007
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    References listed on IDEAS

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