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A Methodology for Defining Electricity Demand in Energy Simulations Referred to the Italian Context

Author

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  • Paola Caputo

    (Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Bonardi 9, 20133 Milano, Italy)

  • Costa Gaia

    (Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Bonardi 9, 20133 Milano, Italy)

  • Valentina Zanotto

    (Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Bonardi 9, 20133 Milano, Italy)

Abstract

Electricity consumption in Europe is constantly increasing, despite the fact that in recent years, huge efforts in terms of programs and regulations have been made towards energy demand reduction and energy systems improvement. Since the electricity demand affects both the operation of the supply and distribution plants and the thermal loads of buildings, the importance of providing a proper definition of demand profiles is evident. The main aim of the paper is to provide a set of standard electricity profiles that can reasonably be adopted as input in energy simulations related to the built environment, with particular regards to the Italian context. The work presented in this paper originated within a wider long lasting research aimed at developing a platform for buildings’ energy simulations at district level, with particular reference to the Italian conditions. In this context, it was necessary to define hourly profiles regarding both occupancy and electricity use for lighting and appliances related to different building uses and typologies. For this purpose, the main methods and references for defining electricity loads in buildings were evaluated and average hourly profiles were accordingly developed for residential and commercial buildings. Then the related internal gains were determined and compared to the current Italian standards.

Suggested Citation

  • Paola Caputo & Costa Gaia & Valentina Zanotto, 2013. "A Methodology for Defining Electricity Demand in Energy Simulations Referred to the Italian Context," Energies, MDPI, vol. 6(12), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:12:p:6274-6292:d:30935
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    References listed on IDEAS

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    1. Räsänen, Teemu & Voukantsis, Dimitrios & Niska, Harri & Karatzas, Kostas & Kolehmainen, Mikko, 2010. "Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data," Applied Energy, Elsevier, vol. 87(11), pages 3538-3545, November.
    2. Manzano-Agugliaro, F. & Alcayde, A. & Montoya, F.G. & Zapata-Sierra, A. & Gil, C., 2013. "Scientific production of renewable energies worldwide: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 134-143.
    3. Pahud, D. & Belliardi, M. & Caputo, P., 2012. "Geocooling potential of borehole heat exchangers' systems applied to low energy office buildings," Renewable Energy, Elsevier, vol. 45(C), pages 197-204.
    4. Caputo, Paola & Costa, Gaia & Ferrari, Simone, 2013. "A supporting method for defining energy strategies in the building sector at urban scale," Energy Policy, Elsevier, vol. 55(C), pages 261-270.
    5. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    6. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    7. Tso, Geoffrey K.F & Yau, Kelvin K.W, 2003. "A study of domestic energy usage patterns in Hong Kong," Energy, Elsevier, vol. 28(15), pages 1671-1682.
    8. Cruz-Peragon, F. & Palomar, J.M. & Casanova, P.J. & Dorado, M.P. & Manzano-Agugliaro, F., 2012. "Characterization of solar flat plate collectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1709-1720.
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    7. Ugwoke, B. & Sulemanu, S. & Corgnati, S.P. & Leone, P. & Pearce, J.M., 2021. "Demonstration of the integrated rural energy planning framework for sustainable energy development in low-income countries: Case studies of rural communities in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    8. Angreine Kewo & Pinrolinvic D. K. Manembu & Per Sieverts Nielsen, 2023. "A Rigorous Standalone Literature Review of Residential Electricity Load Profiles," Energies, MDPI, vol. 16(10), pages 1-27, May.
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