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Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages

Author

Listed:
  • Cátia Silva

    (GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Rue 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, Rue Dr.Antonio Bernardino de Almeida 431, 4200-072 Porto, Portugal)

  • Zita Vale

    (Polytechnic of Porto, Praça de Gomes Teixeira, 4099-002 Porto, Portugal)

Abstract

The need for new business models to replace existing ones, soon obsolete, is a subject often discussed among researchers in the area. It is essential to find a practical solution that includes the concepts of demand response and distributed generation in the energy markets, these being the future of the electricity grid. It is believed that these resources can bring advantages to the operation of the system, namely increasing technical efficiency. However, one of the problems is the aggregation of small resources as a result of the associated uncertainties. The authors propose a business model with three main phases used in planning: optimal scheduling, aggregation, and remuneration. In this paper, a new phase was added, the classification, with the main purpose of assisting the aggregator of these small resources in operating situations. The focus is on the fair remuneration of participants in the management of the market, in addition to minimizing operating costs. After testing four different remuneration methods, it was proved that the method proposed by the authors obtained better results, proving the viability of the proposed model.

Suggested Citation

  • Cátia Silva & Pedro Faria & Zita Vale, 2019. "Demand Response and Distributed Generation Remuneration Approach Considering Planning and Operation Stages," Energies, MDPI, vol. 12(14), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2721-:d:248826
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    References listed on IDEAS

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    1. Iver Bakken Sperstad & Magnus Korpås, 2019. "Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties," Energies, MDPI, vol. 12(7), pages 1-24, March.
    2. Cátia Silva & Pedro Faria & Zita Vale, 2019. "Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response," Energies, MDPI, vol. 12(7), pages 1-24, April.
    3. Shariatzadeh, Farshid & Mandal, Paras & Srivastava, Anurag K., 2015. "Demand response for sustainable energy systems: A review, application and implementation strategy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 343-350.
    4. Robin Pilling & Shi Chung Chang & Peter B. Luh, 2017. "Shapley Value-Based Payment Calculation for Energy Exchange between Micro- and Utility Grids," Games, MDPI, vol. 8(4), pages 1-12, October.
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    Cited by:

    1. Marina Bertolini & Gregorio Morosinotto, 2023. "Business Models for Energy Community in the Aggregator Perspective: State of the Art and Research Gaps," Energies, MDPI, vol. 16(11), pages 1-26, June.
    2. Carlos Ramos & Zita Vale & Peter Palensky & Hiroaki Nishi, 2021. "Sustainable Energy Consumption," Energies, MDPI, vol. 14(20), pages 1-3, October.
    3. Gabriel Santos & Pedro Faria & Zita Vale & Tiago Pinto & Juan M. Corchado, 2020. "Constrained Generation Bids in Local Electricity Markets: A Semantic Approach," Energies, MDPI, vol. 13(15), pages 1-27, August.

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