IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v131y2014icp267-278.html
   My bibliography  Save this item

Forecasting household consumer electricity load profiles with a combined physical and behavioral approach

Citations

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


Cited by:

  1. Ildar Daminov & Rémy Rigo-Mariani & Raphael Caire & Anton Prokhorov & Marie-Cécile Alvarez-Hérault, 2021. "Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime," Energies, MDPI, vol. 14(5), pages 1-27, March.
  2. Marwan, Marwan, 2020. "The impact of probability of electricity price spike and outside temperature to define total expected cost for air conditioning," Energy, Elsevier, vol. 195(C).
  3. Trotter, Ian Michael & Féres, José Gustavo & Bolkesjø, Torjus Folsland & de Hollanda, Lavínia Rocha, 2015. "Simulating Brazilian Electricity Demand Under Climate Change Scenarios," Working Papers in Applied Economics 208689, Universidade Federal de Vicosa, Departamento de Economia Rural.
  4. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
  5. Ntumba Marc-Alain Mutombo & Bubele Papy Numbi, 2022. "Development of a Linear Regression Model Based on the Most Influential Predictors for a Research Office Cooling Load," Energies, MDPI, vol. 15(14), pages 1-20, July.
  6. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
  7. Nick MacMackin, & Miller, Lindsay & Carriveau, Rupp, 2019. "Modeling and disaggregating hourly effects of weather on sectoral electricity demand," Energy, Elsevier, vol. 188(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. Wang, Yao & Lin, Boqiang & Li, Minyang, 2021. "Is household electricity saving a virtuous circle? A case study of the first-tier cities in China," Applied Energy, Elsevier, vol. 285(C).
  10. García-Villalobos, J. & Zamora, I. & Knezović, K. & Marinelli, M., 2016. "Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks," Applied Energy, Elsevier, vol. 180(C), pages 155-168.
  11. Hegazy Rezk & Rania M. Ghoniem & Seydali Ferahtia & Ahmed Fathy & Mohamed M. Ghoniem & Reem Alkanhel, 2022. "A Comparison of Different Renewable-Based DC Microgrid Energy Management Strategies for Commercial Buildings Applications," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
  12. Knobel, Alexander & Chokaev, Bekhan, 2014. "Possible Economic Outcomes of a Trade Agreement with the European Union," EconStor Preprints 121853, ZBW - Leibniz Information Centre for Economics.
  13. David Macii & Daniele Fontanelli & Grazia Barchi, 2020. "A Distribution System State Estimator Based on an Extended Kalman Filter Enhanced with a Prior Evaluation of Power Injections at Unmonitored Buses," Energies, MDPI, vol. 13(22), pages 1-25, November.
  14. Andersen, Frits Møller & Baldini, Mattia & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2017. "Households’ hourly electricity consumption and peak demand in Denmark," Applied Energy, Elsevier, vol. 208(C), pages 607-619.
  15. Meireles, I. & Sousa, V. & Bleys, B. & Poncelet, B., 2022. "Domestic hot water consumption pattern: Relation with total water consumption and air temperature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
  16. Sandels, C. & Brodén, D. & Widén, J. & Nordström, L. & Andersson, E., 2016. "Modeling office building consumer load with a combined physical and behavioral approach: Simulation and validation," Applied Energy, Elsevier, vol. 162(C), pages 472-485.
  17. Pinrolinvic D. K. Manembu & Angreine Kewo & Rasmus Bramstoft & Per Sieverts Nielsen, 2023. "A Systematicity Review on Residential Electricity Load-Shifting at the Appliance Level," Energies, MDPI, vol. 16(23), pages 1-22, November.
  18. Kipping, A. & Trømborg, E., 2015. "Hourly electricity consumption in Norwegian households – Assessing the impacts of different heating systems," Energy, Elsevier, vol. 93(P1), pages 655-671.
  19. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
  20. Di Piazza, A. & Di Piazza, M.C. & La Tona, G. & Luna, M., 2021. "An artificial neural network-based forecasting model of energy-related time series for electrical grid management," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 184(C), pages 294-305.
  21. Lusis, Peter & Khalilpour, Kaveh Rajab & Andrew, Lachlan & Liebman, Ariel, 2017. "Short-term residential load forecasting: Impact of calendar effects and forecast granularity," Applied Energy, Elsevier, vol. 205(C), pages 654-669.
  22. Linas Gelažanskas & Kelum A. A. Gamage, 2015. "Forecasting Hot Water Consumption in Residential Houses," Energies, MDPI, vol. 8(11), pages 1-16, November.
  23. Zhou, Xin & Tian, Shuai & An, Jingjing & Yan, Da & Zhang, Lun & Yang, Junyan, 2022. "Modeling occupant behavior’s influence on the energy efficiency of solar domestic hot water systems," Applied Energy, Elsevier, vol. 309(C).
  24. Fuentes, E. & Arce, L. & Salom, J., 2018. "A review of domestic hot water consumption profiles for application in systems and buildings energy performance analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1530-1547.
  25. Gallo Cassarino, Tiziano & Sharp, Ed & Barrett, Mark, 2018. "The impact of social and weather drivers on the historical electricity demand in Europe," Applied Energy, Elsevier, vol. 229(C), pages 176-185.
  26. Kazmi, Hussain & Munné-Collado, Íngrid & Mehmood, Fahad & Syed, Tahir Abbas & Driesen, Johan, 2021. "Towards data-driven energy communities: A review of open-source datasets, models and tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  27. Adeoye, Omotola & Spataru, Catalina, 2019. "Modelling and forecasting hourly electricity demand in West African countries," Applied Energy, Elsevier, vol. 242(C), pages 311-333.
  28. Kipping, A. & Trømborg, E., 2017. "Modeling hourly consumption of electricity and district heat in non-residential buildings," Energy, Elsevier, vol. 123(C), pages 473-486.
  29. Lin, Haiyang & Wang, Qinxing & Wang, Yu & Liu, Yiling & Sun, Qie & Wennersten, Ronald, 2017. "The energy-saving potential of an office under different pricing mechanisms – Application of an agent-based model," Applied Energy, Elsevier, vol. 202(C), pages 248-258.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.