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Revealing household characteristics from smart meter data

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  1. Viegas, Joaquim L. & Vieira, Susana M. & Melício, R. & Mendes, V.M.F. & Sousa, João M.C., 2016. "Classification of new electricity customers based on surveys and smart metering data," Energy, Elsevier, vol. 107(C), pages 804-817.
  2. Jacqueline Nicole Adams & Zsófia Deme Bélafi & Miklós Horváth & János Balázs Kocsis & Tamás Csoknyai, 2021. "How Smart Meter Data Analysis Can Support Understanding the Impact of Occupant Behavior on Building Energy Performance: A Comprehensive Review," Energies, MDPI, vol. 14(9), pages 1-23, April.
  3. Fletcher, James & Malalasekera, Weeratunge, 2016. "Development of a user-friendly, low-cost home energy monitoring and recording system," Energy, Elsevier, vol. 111(C), pages 32-46.
  4. Guo, Zhifeng & O'Hanley, Jesse R. & Gibson, Stuart, 2022. "Predicting residential electricity consumption patterns based on smart meter and household data: A case study from the Republic of Ireland," Utilities Policy, Elsevier, vol. 79(C).
  5. Chen, Zhiqiang & Li, Jianbin & Cheng, Long & Liu, Xiufeng, 2023. "Federated-WDCGAN: A federated smart meter data sharing framework for privacy preservation," Applied Energy, Elsevier, vol. 334(C).
  6. Villar-Rodriguez, Esther & Del Ser, Javier & Oregi, Izaskun & Bilbao, Miren Nekane & Gil-Lopez, Sergio, 2017. "Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis," Energy, Elsevier, vol. 137(C), pages 118-128.
  7. Akito Ozawa & Ryota Furusato & Yoshikuni Yoshida, 2017. "Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan," Sustainability, MDPI, vol. 9(4), pages 1-23, March.
  8. Anukoolthamchote, Pam Chasuta & Assané, Djeto & Konan, Denise Eby, 2020. "Net electricity load profiles: Shape and variability considering customer-mix at transformers on the island of Oahu, Hawai'i," Energy Policy, Elsevier, vol. 147(C).
  9. Shi, Xunpeng & Wang, Keying & Cheong, Tsun Se & Zhang, Hongwu, 2020. "Prioritizing driving factors of household carbon emissions: An application of the LASSO model with survey data," Energy Economics, Elsevier, vol. 92(C).
  10. Barbetta, Gian Paolo & Canino, Paolo & Cima, Stefano, 2015. "The impact of energy audits on energy efficiency investment of public owners. Evidence from Italy," Energy, Elsevier, vol. 93(P1), pages 1199-1209.
  11. Julien Lancelot Michellod & Declan Kuch & Christian Winzer & Martin K. Patel & Selin Yilmaz, 2022. "Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector," Energies, MDPI, vol. 15(20), pages 1-25, October.
  12. Moreno Jaramillo, Andres F. & Laverty, David M. & Morrow, D. John & Martinez del Rincon, Jesús & Foley, Aoife M., 2021. "Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks," Renewable Energy, Elsevier, vol. 179(C), pages 445-466.
  13. Roberts, Mike B. & Haghdadi, Navid & Bruce, Anna & MacGill, Iain, 2019. "Characterisation of Australian apartment electricity demand and its implications for low-carbon cities," Energy, Elsevier, vol. 180(C), pages 242-257.
  14. Trotta, Gianluca, 2020. "An empirical analysis of domestic electricity load profiles: Who consumes how much and when?," Applied Energy, Elsevier, vol. 275(C).
  15. Melville, Emilia & Christie, Ian & Burningham, Kate & Way, Celia & Hampshire, Phil, 2017. "The electric commons: A qualitative study of community accountability," Energy Policy, Elsevier, vol. 106(C), pages 12-21.
  16. Gonçalves, Rui & Ribeiro, Vitor Miguel & Pereira, Fernando Lobo, 2023. "Variable Split Convolutional Attention: A novel Deep Learning model applied to the household electric power consumption," Energy, Elsevier, vol. 274(C).
  17. Li, Jianbin & Chen, Zhiqiang & Cheng, Long & Liu, Xiufeng, 2022. "Energy data generation with Wasserstein Deep Convolutional Generative Adversarial Networks," Energy, Elsevier, vol. 257(C).
  18. Liu, Xiufeng & Nielsen, Per Sieverts, 2016. "A hybrid ICT-solution for smart meter data analytics," Energy, Elsevier, vol. 115(P3), pages 1710-1722.
  19. Fateh Nassim Melzi & Allou Same & Mohamed Haykel Zayani & Latifa Oukhellou, 2017. "A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors," Energies, MDPI, vol. 10(10), pages 1-21, September.
  20. Kiguchi, Y. & Weeks, M. & Arakawa, R., 2021. "Predicting winners and losers under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 236(C).
  21. Rafik Nafkha & Krzysztof Gajowniczek & Tomasz Ząbkowski, 2018. "Do Customers Choose Proper Tariff? Empirical Analysis Based on Polish Data Using Unsupervised Techniques," Energies, MDPI, vol. 11(3), pages 1-17, February.
  22. Verma, Anoop & Asadi, Ali & Yang, Kai & Tyagi, Satish, 2015. "A data-driven approach to identify households with plug-in electrical vehicles (PEVs)," Applied Energy, Elsevier, vol. 160(C), pages 71-79.
  23. 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.
  24. Wu, Xin & Jiao, Dian & Liang, Kaixin & Han, Xiao, 2019. "A fast online load identification algorithm based on V-I characteristics of high-frequency data under user operational constraints," Energy, Elsevier, vol. 188(C).
  25. Ute Paukstadt & Jörg Becker, 2021. "Uncovering the business value of the internet of things in the energy domain – a review of smart energy business models," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(1), pages 51-66, March.
  26. von Loessl, Victor, 2023. "Smart meter-related data privacy concerns and dynamic electricity tariffs: Evidence from a stated choice experiment," Energy Policy, Elsevier, vol. 180(C).
  27. Yang Yu & Guangyi Liu & Wendong Zhu & Fei Wang & Bin Shu & Kai Zhang & Ram Rajagopal & Nicolas Astier, 2016. "Economic information from Smart Meter: Nexus Between Demand Profile and Electricity Retail Price Between Demand Profile and Electricity Retail Price," Papers 1701.02646, arXiv.org.
  28. Alexis Gerossier & Robin Girard & George Kariniotakis, 2019. "Modeling and Forecasting Electric Vehicle Consumption Profiles," Energies, MDPI, vol. 12(7), pages 1-14, April.
  29. Fernanda Spada Villar & Pedro Henrique Juliano Nardelli & Arun Narayanan & Renan Cipriano Moioli & Hader Azzini & Luiz Carlos Pereira da Silva, 2021. "Noninvasive Detection of Appliance Utilization Patterns in Residential Electricity Demand," Energies, MDPI, vol. 14(6), pages 1-23, March.
  30. Fang, Hongliang & Wang, Yan-Wu & Xiao, Jiang-Wen & Cui, Shichang & Qin, Zhaoyu, 2021. "A new mining framework with piecewise symbolic spatial clustering," Applied Energy, Elsevier, vol. 298(C).
  31. Claeys, Robbert & Cleenwerck, Rémy & Knockaert, Jos & Desmet, Jan, 2024. "Capturing multiscale temporal dynamics in synthetic residential load profiles through Generative Adversarial Networks (GANs)," Applied Energy, Elsevier, vol. 360(C).
  32. Wen, Hanguan & Liu, Xiufeng & Yang, Ming & Lei, Bo & Xu, Cheng & Chen, Zhe, 2024. "A novel approach for identifying customer groups for personalized demand-side management services using household socio-demographic data," Energy, Elsevier, vol. 286(C).
  33. Kang, J. & Reiner, D., 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Cambridge Working Papers in Economics 2142, Faculty of Economics, University of Cambridge.
  34. Konstantin Hopf & Mariya Sodenkamp & Thorsten Staake, 2018. "Enhancing energy efficiency in the residential sector with smart meter data analytics," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(4), pages 453-473, November.
  35. Khosrowpour, Ardalan & Jain, Rishee K. & Taylor, John E. & Peschiera, Gabriel & Chen, Jiayu & Gulbinas, Rimas, 2018. "A review of occupant energy feedback research: Opportunities for methodological fusion at the intersection of experimentation, analytics, surveys and simulation," Applied Energy, Elsevier, vol. 218(C), pages 304-316.
  36. Shimoda, Yoshiyuki & Yamaguchi, Yohei & Iwafune, Yumiko & Hidaka, Kazuyoshi & Meier, Alan & Yagita, Yoshie & Kawamoto, Hisaki & Nishikiori, Soichi, 2020. "Energy demand science for a decarbonized society in the context of the residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  37. Claeys, Robbert & Cleenwerck, Rémy & Knockaert, Jos & Desmet, Jan, 2023. "Stochastic generation of residential load profiles with realistic variability based on wavelet-decomposed smart meter data," Applied Energy, Elsevier, vol. 350(C).
  38. Nilsson, Anders & Bartusch, Cajsa, 2024. "Empowered or enchained? Exploring consumer perspectives on Direct Load Control," Energy Policy, Elsevier, vol. 192(C).
  39. Wang, Fei & Lu, Xiaoxing & Chang, Xiqiang & Cao, Xin & Yan, Siqing & Li, Kangping & Duić, Neven & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Household profile identification for behavioral demand response: A semi-supervised learning approach using smart meter data," Energy, Elsevier, vol. 238(PB).
  40. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  41. Krzysztof Gajowniczek & Tomasz Ząbkowski, 2015. "Data Mining Techniques for Detecting Household Characteristics Based on Smart Meter Data," Energies, MDPI, vol. 8(7), pages 1-21, July.
  42. Gouveia, João Pedro & Seixas, Júlia & Mestre, Ana, 2017. "Daily electricity consumption profiles from smart meters - Proxies of behavior for space heating and cooling," Energy, Elsevier, vol. 141(C), pages 108-122.
  43. Chen, Xiao & Zanocco, Chad & Flora, June & Rajagopal, Ram, 2022. "Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation," Applied Energy, Elsevier, vol. 318(C).
  44. Salah Bouktif & Ali Ouni & Sanja Lazarova-Molnar, 2022. "Towards a Rigorous Consideration of Occupant Behaviours of Residential Households for Effective Electrical Energy Savings: An Overview," Energies, MDPI, vol. 15(5), pages 1-30, February.
  45. David Bienvenido-Huertas & Jesús A. Pulido-Arcas & Carlos Rubio-Bellido & Alexis Pérez-Fargallo, 2021. "Prediction of Fuel Poverty Potential Risk Index Using Six Regression Algorithms: A Case-Study of Chilean Social Dwellings," Sustainability, MDPI, vol. 13(5), pages 1-30, February.
  46. Guo, Peiyang & Lam, Jacqueline C.K. & Li, Victor O.K., 2019. "Drivers of domestic electricity users’ price responsiveness: A novel machine learning approach," Applied Energy, Elsevier, vol. 235(C), pages 900-913.
  47. Lesley Thomson & David Jenkins, 2023. "The Use of Real Energy Consumption Data in Characterising Residential Energy Demand with an Inventory of UK Datasets," Energies, MDPI, vol. 16(16), pages 1-29, August.
  48. Fransson, Victor & Bagge, Hans & Johansson, Dennis, 2019. "Impact of variations in residential use of household electricity on the energy and power demand for space heating – Variations from measurements in 1000 apartments," Applied Energy, Elsevier, vol. 254(C).
  49. 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).
  50. Liu, Gang & Wang, Kun & Hao, Xiaochen & Zhang, Zhipeng & Zhao, Yantao & Xu, Qingquan, 2022. "SA-LSTMs: A new advance prediction method of energy consumption in cement raw materials grinding system," Energy, Elsevier, vol. 241(C).
  51. Souhaib Ben Taieb & Raphael Huser & Rob J. Hyndman & Marc G. Genton, 2015. "Probabilistic time series forecasting with boosted additive models: an application to smart meter data," Monash Econometrics and Business Statistics Working Papers 12/15, Monash University, Department of Econometrics and Business Statistics.
  52. Lee, Dasom & Hess, David J., 2021. "Data privacy and residential smart meters: Comparative analysis and harmonization potential," Utilities Policy, Elsevier, vol. 70(C).
  53. Michalec, Aleksandra & Hayes, Enda & Longhurst, James & Tudgey, David, 2019. "Enhancing the communication potential of smart metering for energy and water," Utilities Policy, Elsevier, vol. 56(C), pages 33-40.
  54. Wen, Lulu & Zhou, Kaile & Yang, Shanlin & Li, Lanlan, 2018. "Compression of smart meter big data: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 59-69.
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