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Ramping of Demand Response Event with Deploying Distinct Programs by an Aggregator

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  • Omid Abrishambaf

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • Pedro Faria

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • Zita Vale

    (IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

Abstract

System operators have moved towards the integration of renewable resources. However, these resources make network management unstable as they have variations in produced energy. Thus, some strategic plans, like demand response programs, are required to overcome these concerns. This paper develops an aggregator model with a precise vision of the demand response timeline. The model at first discusses the role of an aggregator, and thereafter is presented an innovative approach to how the aggregator deals with short and real-time demand response programs. A case study is developed for the model using real-time simulator and laboratory resources to survey the performance of the model under practical challenges. The real-time simulation uses an OP5600 machine that controls six laboratory resistive loads. Furthermore, the actual consumption profiles are adapted from the loads with a small-time step to precisely survey the behavior of each load. Also, remuneration costs of the event during the case study have been calculated and compared using both actual and simulated demand reduction profiles in the periods prior to event, such as the ramp period.

Suggested Citation

  • Omid Abrishambaf & Pedro Faria & Zita Vale, 2020. "Ramping of Demand Response Event with Deploying Distinct Programs by an Aggregator," Energies, MDPI, vol. 13(6), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1389-:d:333259
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    References listed on IDEAS

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    Cited by:

    1. Cátia Silva & Pedro Faria & Zita Vale, 2023. "Demand Response Implementation: Overview of Europe and United States Status," Energies, MDPI, vol. 16(10), pages 1-20, May.
    2. Jin Zhang & Liang Che & Lei Wang & Udaya K. Madawala, 2020. "Game-Theory Based V2G Coordination Strategy for Providing Ramping Flexibility in Power Systems," Energies, MDPI, vol. 13(19), pages 1-17, September.
    3. Zita Vale & Pedro Faria & Omid Abrishambaf & Luis Gomes & Tiago Pinto, 2021. "MARTINE—A Platform for Real-Time Energy Management in Smart Grids," Energies, MDPI, vol. 14(7), pages 1-18, March.
    4. Ningxuan Guo & Yinan Wang & Gangfeng Yan & Jian Hou, 2020. "Non-Cooperative Game in Block Bidding Markets Considering Demand Response," Energies, MDPI, vol. 13(13), pages 1-18, June.
    5. Pedro Faria & Zita Vale, 2023. "Demand Response in Smart Grids," Energies, MDPI, vol. 16(2), pages 1-3, January.

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