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A highly resolved modeling technique to simulate residential power demand

Citations

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  1. Farzan, Farbod & Jafari, Mohsen A. & Gong, Jie & Farzan, Farnaz & Stryker, Andrew, 2015. "A multi-scale adaptive model of residential energy demand," Applied Energy, Elsevier, vol. 150(C), pages 258-273.
  2. Vogl, Jonathan & Kleinebrahm, Max & Raab, Moritz & McKenna, Russell & Fichtner, Wolf, 2025. "A review of challenges and opportunities in occupant modeling for future residential energy demand," Working Paper Series in Production and Energy 76, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
  3. Liang, Yile & Liu, Feng & Wang, Cheng & Mei, Shengwei, 2017. "Distributed demand-side energy management scheme in residential smart grids: An ordinal state-based potential game approach," Applied Energy, Elsevier, vol. 206(C), pages 991-1008.
  4. Dodds, Paul E., 2014. "Integrating housing stock and energy system models as a strategy to improve heat decarbonisation assessments," Applied Energy, Elsevier, vol. 132(C), pages 358-369.
  5. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
  6. 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.
  7. Muratori, Matteo & Moran, Michael J. & Serra, Emmanuele & Rizzoni, Giorgio, 2013. "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, Elsevier, vol. 58(C), pages 168-177.
  8. Fan, Jin & Li, Jun & Wu, Yanrui & Wang, Shanyong & Zhao, Dingtao, 2016. "The effects of allowance price on energy demand under a personal carbon trading scheme," Applied Energy, Elsevier, vol. 170(C), pages 242-249.
  9. Celik, Berk & Roche, Robin & Suryanarayanan, Siddharth & Bouquain, David & Miraoui, Abdellatif, 2017. "Electric energy management in residential areas through coordination of multiple smart homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 260-275.
  10. Adeoye, Omotola & Spataru, Catalina, 2019. "Modelling and forecasting hourly electricity demand in West African countries," Applied Energy, Elsevier, vol. 242(C), pages 311-333.
  11. Jiang, Tao & Li, Zening & Jin, Xiaolong & Chen, Houhe & Li, Xue & Mu, Yunfei, 2018. "Flexible operation of active distribution network using integrated smart buildings with heating, ventilation and air-conditioning systems," Applied Energy, Elsevier, vol. 226(C), pages 181-196.
  12. Pagani, M. & Maire, P. & Korosec, W. & Chokani, N. & Abhari, R.S., 2020. "District heat network extension to decarbonise building stock: A bottom-up agent-based approach," Applied Energy, Elsevier, vol. 272(C).
  13. Tang, Yanyan & Zhang, Qi & Mclellan, Benjamin & Li, Hailong, 2018. "Study on the impacts of sharing business models on economic performance of distributed PV-Battery systems," Energy, Elsevier, vol. 161(C), pages 544-558.
  14. Yilmaz, S. & Majcen, D. & Heidari, M. & Mahmoodi, J. & Brosch, T. & Patel, M.K., 2019. "Analysis of the impact of energy efficiency labelling and potential changes on electricity demand reduction of white goods using a stock model: The case of Switzerland," Applied Energy, Elsevier, vol. 239(C), pages 117-132.
  15. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2022. "Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange," Applied Energy, Elsevier, vol. 310(C).
  16. Yu, Xinran & Ergan, Semiha, 2022. "Estimating power demand shaving capacity of buildings on an urban scale using extracted demand response profiles through machine learning models," Applied Energy, Elsevier, vol. 310(C).
  17. Duygu Erten & Zekâi Şen, 2020. "Smart Home Innovative Heat Test Analysis for Heat Storage and Conductivity Coefficients," Sustainability, MDPI, vol. 12(4), pages 1-11, February.
  18. Moe Soheilian & Géza Fischl & Myriam Aries, 2021. "Smart Lighting Application for Energy Saving and User Well-Being in the Residential Environment," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
  19. Behl, Madhur & Smarra, Francesco & Mangharam, Rahul, 2016. "DR-Advisor: A data-driven demand response recommender system," Applied Energy, Elsevier, vol. 170(C), pages 30-46.
  20. Huang, Yunyou & Zhan, Jianfeng & Luo, Chunjie & Wang, Lei & Wang, Nana & Zheng, Daoyi & Fan, Fanda & Ren, Rui, 2019. "An electricity consumption model for synthesizing scalable electricity load curves," Energy, Elsevier, vol. 169(C), pages 674-683.
  21. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
  22. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
  23. Boßmann, T. & Staffell, I., 2015. "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain," Energy, Elsevier, vol. 90(P2), pages 1317-1333.
  24. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102, arXiv.org.
  25. Song, Xiaoling & Wu, Han & Zhang, Huqing & Guo, Jianxin & Zhang, Zhe & Peña-Mora, Feniosky, 2025. "Can retail electricity pricing promote microgrid operators to leverage shared energy storage services among internal aggregators?," Energy, Elsevier, vol. 314(C).
  26. Stephen Adams & Steven Greenspan & Maria Velez-Rojas & Serge Mankovski & Peter A. Beling, 2019. "Data-driven simulation for energy consumption estimation in a smart home," Environment Systems and Decisions, Springer, vol. 39(3), pages 281-294, September.
  27. Xiufeng Liu & Yanyan Yang & Rongling Li & Per Sieverts Nielsen, 2019. "A Stochastic Model for Residential User Activity Simulation," Energies, MDPI, vol. 12(17), pages 1-17, August.
  28. Good, Nicholas & Zhang, Lingxi & Navarro-Espinosa, Alejandro & Mancarella, Pierluigi, 2015. "High resolution modelling of multi-energy domestic demand profiles," Applied Energy, Elsevier, vol. 137(C), pages 193-210.
  29. Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.
  30. Varghese, Sushant & Sioshansi, Ramteen, 2020. "The price is right? How pricing and incentive mechanisms in California incentivize building distributed hybrid solar and energy-storage systems," Energy Policy, Elsevier, vol. 138(C).
  31. Chen, Jianli & Adhikari, Rajendra & Wilson, Eric & Robertson, Joseph & Fontanini, Anthony & Polly, Ben & Olawale, Opeoluwa, 2022. "Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model," Applied Energy, Elsevier, vol. 325(C).
  32. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
  33. Felipe Moraes do Nascimento & Julio Cezar Mairesse Siluk & Fernando de Souza Savian & Taís Bisognin Garlet & José Renes Pinheiro & Carlos Ramos, 2020. "Factors for Measuring Photovoltaic Adoption from the Perspective of Operators," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
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