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How the Italian Residential Sector Could Contribute to Load Flexibility in Demand Response Activities: A Methodology for Residential Clustering and Developing a Flexibility Strategy

Author

Listed:
  • Francesco Mancini

    (Department of Planning, Design and Technology of Architecture, Sapienza University of Rome, Via Flaminia, 72-00197 Rome, Italy)

  • Sabrina Romano

    (Energy Technologies Department (DTE), Italian National Agency for Technologies, Energy and Sustainable Economic Development (ENEA), Via Anguillarese, 301-00123 Rome, Italy)

  • Gianluigi Lo Basso

    (Department of Astronautics, Electrical Energy Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Jacopo Cimaglia

    (Department of Astronautics, Electrical Energy Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Livio de Santoli

    (Department of Astronautics, Electrical Energy Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

Abstract

This work aims at exploring the potential contribution of the Italian residential sector in implementing load flexibility for Demand Response activities. In detail, by combining experimental and statistical approaches, a method to estimate the load profile of a dwelling cluster of 751 units has been presented. To do so, 14 dwelling archetypes have been defined and the algorithm to categorise the sample units has been built. Then, once the potential flexible loads for each archetype have been evaluated, a control strategy for applying load time shifting has been implemented. That strategy accounts for both the power demand profile and the hourly electricity price. Specifically, it has been assumed that end users access a pricing mechanism following the hourly trend of electricity economic value, which is traded day by day in the Italian spot market, instead of the current Time of Use (TOU) system. In such a way, it is possible to flatten the dwellings cluster profile, limiting undesired and unexpected results on the balancing market. In the end, monthly and yearly flexibility indexes have been defined along with the strategy effectiveness parameter. From calculations, it emerges that a dwelling cluster for the Italian residential sector is characterised by a flexibility index of 10.3% and by a strategy effectiveness equal to 34%. It is noteworthy that the highest values for flexibility purpose have been registered over the heating season (winter) for the weekends.

Suggested Citation

  • Francesco Mancini & Sabrina Romano & Gianluigi Lo Basso & Jacopo Cimaglia & Livio de Santoli, 2020. "How the Italian Residential Sector Could Contribute to Load Flexibility in Demand Response Activities: A Methodology for Residential Clustering and Developing a Flexibility Strategy," Energies, MDPI, vol. 13(13), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3359-:d:378850
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    2. Manfren, Massimiliano & Nastasi, Benedetto & Tronchin, Lamberto & Groppi, Daniele & Garcia, Davide Astiaso, 2021. "Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
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    5. Rajavelu Dharani & Madasamy Balasubramonian & Thanikanti Sudhakar Babu & Benedetto Nastasi, 2021. "Load Shifting and Peak Clipping for Reducing Energy Consumption in an Indian University Campus," Energies, MDPI, vol. 14(3), pages 1-16, January.
    6. Francesco Mancini & Jacopo Cimaglia & Gianluigi Lo Basso & Sabrina Romano, 2021. "Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study," Energies, MDPI, vol. 14(11), pages 1-21, May.
    7. Guglielmina Mutani & Pamela Vocale & Kavan Javanroodi, 2023. "Toward Improved Urban Building Energy Modeling Using a Place-Based Approach," Energies, MDPI, vol. 16(9), pages 1-17, May.
    8. Pastore, Lorenzo Mario & Lo Basso, Gianluigi & Ricciardi, Guido & de Santoli, Livio, 2023. "Smart energy systems for renewable energy communities: A comparative analysis of power-to-X strategies for improving energy self-consumption," Energy, Elsevier, vol. 280(C).

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