IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v62y2013icp742-751.html
   My bibliography  Save this article

Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption

Author

Listed:
  • López-Rodríguez, M.A.
  • Santiago, I.
  • Trillo-Montero, D.
  • Torriti, J.
  • Moreno-Munoz, A.

Abstract

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Suggested Citation

  • López-Rodríguez, M.A. & Santiago, I. & Trillo-Montero, D. & Torriti, J. & Moreno-Munoz, A., 2013. "Analysis and modeling of active occupancy of the residential sector in Spain: An indicator of residential electricity consumption," Energy Policy, Elsevier, vol. 62(C), pages 742-751.
    • Handle: RePEc:eee:enepol:v:62:y:2013:i:c:p:742-751
    DOI: 10.1016/j.enpol.2013.07.095
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421513007386
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2013.07.095?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arghira, Nicoleta & Hawarah, Lamis & Ploix, Stéphane & Jacomino, Mireille, 2012. "Prediction of appliances energy use in smart homes," Energy, Elsevier, vol. 48(1), pages 128-134.
    2. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    3. 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.
    4. Torriti, Jacopo, 2012. "Demand Side Management for the European Supergrid: Occupancy variances of European single-person households," Energy Policy, Elsevier, vol. 44(C), pages 199-206.
    5. Ueno, Tsuyoshi & Sano, Fuminori & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data," Applied Energy, Elsevier, vol. 83(2), pages 166-183, February.
    6. Kriett, Phillip Oliver & Salani, Matteo, 2012. "Optimal control of a residential microgrid," Energy, Elsevier, vol. 42(1), pages 321-330.
    7. Gans, Will & Alberini, Anna & Longo, Alberto, 2011. "Smart Meter Devices and The Effect of Feedback on Residential Electricity Consumption: Evidence from a Natural Experiment in Northern Ireland," Energy: Resources and Markets 108202, Fondazione Eni Enrico Mattei (FEEM).
    8. Dlamini, Ndumiso G. & Cromieres, Fabien, 2012. "Implementing peak load reduction algorithms for household electrical appliances," Energy Policy, Elsevier, vol. 44(C), pages 280-290.
    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. Maruyama, Takuya & Fukahori, Tatsuya, 2020. "Households with every member out-of-home (HEMO): Comparison using the 1984, 1997, and 2012 household travel surveys in Kumamoto, Japan," Journal of Transport Geography, Elsevier, vol. 82(C).
    2. 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.
    3. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    4. Yunusov, Timur & Torriti, Jacopo, 2021. "Distributional effects of Time of Use tariffs based on electricity demand and time use," Energy Policy, Elsevier, vol. 156(C).
    5. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    6. Santiago, I. & Moreno-Munoz, A. & Quintero-Jiménez, P. & Garcia-Torres, F. & Gonzalez-Redondo, M.J., 2021. "Electricity demand during pandemic times: The case of the COVID-19 in Spain," Energy Policy, Elsevier, vol. 148(PA).
    7. Braulio-Gonzalo, Marta & Bovea, María D. & Jorge-Ortiz, Andrea & Juan, Pablo, 2021. "Which is the best-fit response variable for modelling the energy consumption of households? An analysis based on survey data," Energy, Elsevier, vol. 231(C).
    8. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    9. Torriti, Jacopo, 2020. "Temporal aggregation: Time use methodologies applied to residential electricity demand," Utilities Policy, Elsevier, vol. 64(C).
    10. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    11. Emilio J. Palacios-Garcia & Antonio Moreno-Muñoz & Isabel Santiago & Isabel M. Moreno-Garcia & María I. Milanés-Montero, 2017. "PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling," Energies, MDPI, vol. 10(10), pages 1-22, September.
    12. Bohlmann, Jessika Andreina & Inglesi-Lotz, Roula, 2018. "Analysing the South African residential sector's energy profile," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 240-252.
    13. Deepu Krishnan & Scott Kelly & Yohan Kim, 2022. "A Meta-Analysis Review of Occupant Behaviour Models for Assessing Demand-Side Energy Consumption," Energies, MDPI, vol. 15(3), pages 1-23, February.
    14. Máté János Lőrincz & José Luis Ramírez-Mendiola & Jacopo Torriti, 2021. "Impact of Time-Use Behaviour on Residential Energy Consumption in the United Kingdom," Energies, MDPI, vol. 14(19), pages 1-32, October.
    15. 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.
    16. Zhaoxia Wang & Yan Ding & Huiyan Deng & Fan Yang & Neng Zhu, 2018. "An Occupant-Oriented Calculation Method of Building Interior Cooling Load Design," Sustainability, MDPI, vol. 10(6), pages 1-29, May.
    17. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    18. Satoshi Nakano & Ayu Washizu, 2020. "On the Acceptability of Electricity Demand Side Management by Time of Day," Energies, MDPI, vol. 13(14), pages 1-21, July.
    19. Ahn, Ki-Uhn & Kim, Deuk-Woo & Park, Cheol-Soo & de Wilde, Pieter, 2017. "Predictability of occupant presence and performance gap in building energy simulation," Applied Energy, Elsevier, vol. 208(C), pages 1639-1652.

    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. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    2. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    3. Römer, Benedikt & Reichhart, Philipp & Kranz, Johann & Picot, Arnold, 2012. "The role of smart metering and decentralized electricity storage for smart grids: The importance of positive externalities," Energy Policy, Elsevier, vol. 50(C), pages 486-495.
    4. 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.
    5. Torriti, Jacopo, 2020. "Temporal aggregation: Time use methodologies applied to residential electricity demand," Utilities Policy, Elsevier, vol. 64(C).
    6. Valeria Di Cosmo & Sean Lyons & Anne Nolan, 2014. "Estimating the Impact of Time-of-Use Pricing on Irish Electricity Demand," The Energy Journal, , vol. 35(2), pages 117-136, April.
    7. Reina, Vincent J. & Kontokosta, Constantine, 2017. "Low hanging fruit? Regulations and energy efficiency in subsidized multifamily housing," Energy Policy, Elsevier, vol. 106(C), pages 505-513.
    8. Ian H. Rowlands & Tobi Reid & Paul Parker, 2015. "Research with disaggregated electricity end‐use data in households: review and recommendations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(5), pages 383-396, September.
    9. Cossent, Rafael & Gómez, Tomás & Olmos, Luis, 2011. "Large-scale integration of renewable and distributed generation of electricity in Spain: Current situation and future needs," Energy Policy, Elsevier, vol. 39(12), pages 8078-8087.
    10. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    11. Guo, Zhifeng & Zhou, Kaile & Zhang, Chi & Lu, Xinhui & Chen, Wen & Yang, Shanlin, 2018. "Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 399-412.
    12. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    13. Yildiz, B. & Bilbao, J.I. & Dore, J. & Sproul, A.B., 2017. "Recent advances in the analysis of residential electricity consumption and applications of smart meter data," Applied Energy, Elsevier, vol. 208(C), pages 402-427.
    14. Schleich, Joachim & Faure, Corinne & Klobasa, Marian, 2017. "Persistence of the effects of providing feedback alongside smart metering devices on household electricity demand," Energy Policy, Elsevier, vol. 107(C), pages 225-233.
    15. Yu, Yihua & Guo, Jin, 2016. "Identifying electricity-saving potential in rural China: Empirical evidence from a household survey," Energy Policy, Elsevier, vol. 94(C), pages 1-9.
    16. Torriti, Jacopo, 2013. "The significance of occupancy steadiness in residential consumer response to Time-of-Use pricing: Evidence from a stochastic adjustment model," Utilities Policy, Elsevier, vol. 27(C), pages 49-56.
    17. Jacopo Torriti & Philipp Grunewald, 2014. "Demand Side Response: Patterns in Europe and Future Policy Perspectives under Capacity Mechanisms," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    18. Favero, Filippo & Grossi, Luigi, 2023. "Analysis of individual natural gas consumption and price elasticity: Evidence from billing data in Italy," Energy Economics, Elsevier, vol. 118(C).
    19. Du, Limin & Guo, Jin & Wei, Chu, 2017. "Impact of information feedback on residential electricity demand in China," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 324-334.
    20. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.

    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:eee:enepol:v:62:y:2013:i:c:p:742-751. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    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.