IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v6y2013i12p6274-6292d30935.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/6/12/6274/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/6/12/6274/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christian Pötzinger & Markus Preißinger & Dieter Brüggemann, 2015. "Influence of Hydrogen-Based Storage Systems on Self-Consumption and Self-Sufficiency of Residential Photovoltaic Systems," Energies, MDPI, vol. 8(8), pages 1-21, August.
    2. 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.
    3. Jiménez Navarro, Juan Pablo & Cejudo López, José Manuel & Connolly, David, 2017. "The effect of feed-in-tariff supporting schemes on the viability of a district heating and cooling production system," Energy, Elsevier, vol. 134(C), pages 438-448.
    4. Giordano, P. & Caputo, P. & Vancheri, A., 2014. "Fuzzy evaluation of heterogeneous quantities: Measuring urban ecological efficiency," Ecological Modelling, Elsevier, vol. 288(C), pages 112-126.
    5. Barelli, L. & Bidini, G. & Pelosi, D. & Ciupageanu, D.A. & Cardelli, E. & Castellini, S. & Lăzăroiu, G., 2020. "Comparative analysis of AC and DC bus configurations for flywheel-battery HESS integration in residential micro-grids," Energy, Elsevier, vol. 204(C).
    6. Kılkış, Şiir & Kılkış, Birol, 2019. "An urbanization algorithm for districts with minimized emissions based on urban planning and embodied energy towards net-zero exergy targets," Energy, Elsevier, vol. 179(C), pages 392-406.
    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.
    9. Ferrari, Simone & Zagarella, Federica & Caputo, Paola & D'Amico, Antonino, 2019. "Results of a literature review on methods for estimating buildings energy demand at district level," Energy, Elsevier, vol. 175(C), pages 1130-1137.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    2. Amin, Amin & Mourshed, Monjur, 2024. "Community stochastic domestic electricity forecasting," Applied Energy, Elsevier, vol. 355(C).
    3. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    4. Alaia Sola & Cristina Corchero & Jaume Salom & Manel Sanmarti, 2018. "Simulation Tools to Build Urban-Scale Energy Models: A Review," Energies, MDPI, vol. 11(12), pages 1-24, November.
    5. Hernández-Escobedo, Q. & Saldaña-Flores, R. & Rodríguez-García, E.R. & Manzano-Agugliaro, F., 2014. "Wind energy resource in Northern Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 890-914.
    6. Frayssinet, Loïc & Merlier, Lucie & Kuznik, Frédéric & Hubert, Jean-Luc & Milliez, Maya & Roux, Jean-Jacques, 2018. "Modeling the heating and cooling energy demand of urban buildings at city scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2318-2327.
    7. McLoughlin, Fintan & Duffy, Aidan & Conlon, Michael, 2015. "A clustering approach to domestic electricity load profile characterisation using smart metering data," Applied Energy, Elsevier, vol. 141(C), pages 190-199.
    8. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    9. Tooke, Thoreau Rory & van der Laan, Michael & Coops, Nicholas C., 2014. "Mapping demand for residential building thermal energy services using airborne LiDAR," Applied Energy, Elsevier, vol. 127(C), pages 125-134.
    10. Giasemidis, Georgios & Haben, Stephen & Lee, Tamsin & Singleton, Colin & Grindrod, Peter, 2017. "A genetic algorithm approach for modelling low voltage network demands," Applied Energy, Elsevier, vol. 203(C), pages 463-473.
    11. Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
    12. Tarek Rakha & Rawad El Kontar, 2019. "Community energy by design: A simulation-based design workflow using measured data clustering to calibrate Urban Building Energy Models (UBEMs)," Environment and Planning B, , vol. 46(8), pages 1517-1533, October.
    13. 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.
    14. Buso, Tiziana & Corgnati, Stefano Paolo, 2017. "A customized modelling approach for multi-functional buildings – Application to an Italian Reference Hotel," Applied Energy, Elsevier, vol. 190(C), pages 1302-1315.
    15. Yanxia Li & Chao Wang & Sijie Zhu & Junyan Yang & Shen Wei & Xinkai Zhang & Xing Shi, 2020. "A Comparison of Various Bottom-Up Urban Energy Simulation Methods Using a Case Study in Hangzhou, China," Energies, MDPI, vol. 13(18), pages 1-23, September.
    16. Belliardi, Marco & Caputo, Paola & Ferla, Giulio & Cereghetti, Nerio & Antonioli Mantegazzini, Barbara, 2023. "An innovative application of 5GDHC: A techno-economic assessment of shallow geothermal systems potential in different European climates," Energy, Elsevier, vol. 280(C).
    17. Krarti, Moncef & Aldubyan, Mohammad & Williams, Eric, 2020. "Residential building stock model for evaluating energy retrofit programs in Saudi Arabia," Energy, Elsevier, vol. 195(C).
    18. Rae, Callum & Kerr, Sandy & Maroto-Valer, M. Mercedes, 2020. "Upscaling smart local energy systems: A review of technical barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    19. Marjana Šijanec Zavrl & Gašper Stegnar & Andraž Rakušček & Henrik Gjerkeš, 2016. "A Bottom-Up Building Stock Model for Tracking Regional Energy Targets—A Case Study of Kočevje," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    20. Allegrini, Jonas & Orehounig, Kristina & Mavromatidis, Georgios & Ruesch, Florian & Dorer, Viktor & Evins, Ralph, 2015. "A review of modelling approaches and tools for the simulation of district-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1391-1404.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:6:y:2013:i:12:p:6274-6292:d:30935. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.