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Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data

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Cited by:

  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. Loganthurai, P. & Rajasekaran, V. & Gnanambal, K., 2016. "Evolutionary algorithm based optimum scheduling of processing units in rice industry to reduce peak demand," Energy, Elsevier, vol. 107(C), pages 419-430.
  3. Huang, Pei & Sun, Yongjun, 2019. "A clustering based grouping method of nearly zero energy buildings for performance improvements," Applied Energy, Elsevier, vol. 235(C), pages 43-55.
  4. Li, Wenqiang & Gong, Guangcai & Fan, Houhua & Peng, Pei & Chun, Liang & Fang, Xi, 2021. "A clustering-based approach for “cross-scale” load prediction on building level in HVAC systems," Applied Energy, Elsevier, vol. 282(PB).
  5. van Zoest, Vera & El Gohary, Fouad & Ngai, Edith C.H. & Bartusch, Cajsa, 2021. "Demand charges and user flexibility – Exploring differences in electricity consumer types and load patterns within the Swedish commercial sector," Applied Energy, Elsevier, vol. 302(C).
  6. 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).
  7. 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.
  8. Papadopoulos, Sokratis & Bonczak, Bartosz & Kontokosta, Constantine E., 2018. "Pattern recognition in building energy performance over time using energy benchmarking data," Applied Energy, Elsevier, vol. 221(C), pages 576-586.
  9. 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.
  10. Wen, Hanguan & Liu, Xiufeng & Yang, Ming & Lei, Bo & Cheng, Xu & Chen, Zhe, 2023. "An energy demand-side management and net metering decision framework," Energy, Elsevier, vol. 271(C).
  11. Shi, Yong & Ren, Xinyue & Guo, Kun & Zhou, Yi & Wang, Jun, 2020. "Research on the economic development pattern of Chinese counties based on electricity consumption," Energy Policy, Elsevier, vol. 147(C).
  12. Zhou, Kaile & Yang, Changhui & Shen, Jianxin, 2017. "Discovering residential electricity consumption patterns through smart-meter data mining: A case study from China," Utilities Policy, Elsevier, vol. 44(C), pages 73-84.
  13. Luo, Xuan & Hong, Tianzhen & Chen, Yixing & Piette, Mary Ann, 2017. "Electric load shape benchmarking for small- and medium-sized commercial buildings," Applied Energy, Elsevier, vol. 204(C), pages 715-725.
  14. Jung, Jaesung & Cho, Yongju & Cheng, Danling & Onen, Ahmet & Arghandeh, Reza & Dilek, Murat & Broadwater, Robert P., 2013. "Monte Carlo analysis of Plug-in Hybrid Vehicles and Distributed Energy Resource growth with residential energy storage in Michigan," Applied Energy, Elsevier, vol. 108(C), pages 218-235.
  15. Eunjung Lee & Jinho Kim & Dongsik Jang, 2020. "Load Profile Segmentation for Effective Residential Demand Response Program: Method and Evidence from Korean Pilot Study," Energies, MDPI, vol. 13(6), pages 1-18, March.
  16. Al-Wakeel, Ali & Wu, Jianzhong & Jenkins, Nick, 2016. "State estimation of medium voltage distribution networks using smart meter measurements," Applied Energy, Elsevier, vol. 184(C), pages 207-218.
  17. Wang, Yanmin & Li, Zhiwei & Liu, Junjie & Lu, Xuan & Zhao, Laifu & Zhao, Yan & Feng, Yongtao, 2024. "Analyzing daily change patterns of indoor temperature in district heating systems: A clustering and regression approach," Applied Energy, Elsevier, vol. 358(C).
  18. 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.
  19. Rongheng Lin & Budan Wu & Yun Su, 2018. "An Adaptive Weighted Pearson Similarity Measurement Method for Load Curve Clustering," Energies, MDPI, vol. 11(9), pages 1-17, September.
  20. Jimyung Kang & Jee-Hyong Lee, 2015. "Electricity Customer Clustering Following Experts’ Principle for Demand Response Applications," Energies, MDPI, vol. 8(10), pages 1-24, October.
  21. 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.
  22. 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.
  23. Trotta, Gianluca, 2020. "An empirical analysis of domestic electricity load profiles: Who consumes how much and when?," Applied Energy, Elsevier, vol. 275(C).
  24. Alexander Tureczek & Per Sieverts Nielsen & Henrik Madsen, 2018. "Electricity Consumption Clustering Using Smart Meter Data," Energies, MDPI, vol. 11(4), pages 1-18, April.
  25. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
  26. Andersen, F.M. & Larsen, H.V. & Juul, N. & Gaardestrup, R.B., 2014. "Differentiated long term projections of the hourly electricity consumption in local areas. The case of Denmark West," Applied Energy, Elsevier, vol. 135(C), pages 523-538.
  27. Liu, Xiufeng & Nielsen, Per Sieverts, 2016. "A hybrid ICT-solution for smart meter data analytics," Energy, Elsevier, vol. 115(P3), pages 1710-1722.
  28. Fu, Xin & Zeng, Xiao-Jun & Feng, Pengpeng & Cai, Xiuwen, 2018. "Clustering-based short-term load forecasting for residential electricity under the increasing-block pricing tariffs in China," Energy, Elsevier, vol. 165(PB), pages 76-89.
  29. Emilio Ghiani & Alessandro Serpi & Virginia Pilloni & Giuliana Sias & Marco Simone & Gianluca Marcialis & Giuliano Armano & Paolo Attilio Pegoraro, 2018. "A Multidisciplinary Approach for the Development of Smart Distribution Networks," Energies, MDPI, vol. 11(10), pages 1-29, September.
  30. Zhou, Kai-le & Yang, Shan-lin & Shen, Chao, 2013. "A review of electric load classification in smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 103-110.
  31. Alexander Martin Tureczek & Per Sieverts Nielsen, 2017. "Structured Literature Review of Electricity Consumption Classification Using Smart Meter Data," Energies, MDPI, vol. 10(5), pages 1-19, April.
  32. Gerossier, Alexis & Barbier, Thibaut & Girard, Robin, 2017. "A novel method for decomposing electricity feeder load into elementary profiles from customer information," Applied Energy, Elsevier, vol. 203(C), pages 752-760.
  33. Kang, J. & Reiner, D., 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics 2143, Faculty of Economics, University of Cambridge.
  34. Roberta Padulano & Giuseppe Giudice, 2018. "A Mixed Strategy Based on Self-Organizing Map for Water Demand Pattern Profiling of Large-Size Smart Water Grid Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(11), pages 3671-3685, September.
  35. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
  36. Al-Wakeel, Ali & Wu, Jianzhong & Jenkins, Nick, 2017. "k-means based load estimation of domestic smart meter measurements," Applied Energy, Elsevier, vol. 194(C), pages 333-342.
  37. 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.
  38. Erik Dahlquist & Fredrik Wallin & Koteshwar Chirumalla & Reza Toorajipour & Glenn Johansson, 2023. "Balancing Power in Sweden Using Different Renewable Resources, Varying Prices, and Storages Like Batteries in a Resilient Energy System," Energies, MDPI, vol. 16(12), pages 1-28, June.
  39. Markovič, Rene & Gosak, Marko & Grubelnik, Vladimir & Marhl, Marko & Virtič, Peter, 2019. "Data-driven classification of residential energy consumption patterns by means of functional connectivity networks," Applied Energy, Elsevier, vol. 242(C), pages 506-515.
  40. Voulis, Nina & Warnier, Martijn & Brazier, Frances M.T., 2018. "Understanding spatio-temporal electricity demand at different urban scales: A data-driven approach," Applied Energy, Elsevier, vol. 230(C), pages 1157-1171.
  41. Alexandra E. Ioannou & Enrico F. Creaco & Chrysi S. Laspidou, 2021. "Exploring the Effectiveness of Clustering Algorithms for Capturing Water Consumption Behavior at Household Level," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
  42. Hsu, David, 2015. "Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data," Applied Energy, Elsevier, vol. 160(C), pages 153-163.
  43. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
  44. Anam-Nawaz Khan & Naeem Iqbal & Atif Rizwan & Rashid Ahmad & Do-Hyeun Kim, 2021. "An Ensemble Energy Consumption Forecasting Model Based on Spatial-Temporal Clustering Analysis in Residential Buildings," Energies, MDPI, vol. 14(11), pages 1-25, May.
  45. Yang, Ying & Campana, Pietro Elia & Yan, Jinyue, 2020. "Potential of unsubsidized distributed solar PV to replace coal-fired power plants, and profits classification in Chinese cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  46. Rhodes, Joshua D. & Cole, Wesley J. & Upshaw, Charles R. & Edgar, Thomas F. & Webber, Michael E., 2014. "Clustering analysis of residential electricity demand profiles," Applied Energy, Elsevier, vol. 135(C), pages 461-471.
  47. Huang, Wenxin & Wang, Jianguo & Wang, Jianping & Zeng, Haiyan & Zhou, Mi & Cao, Jinxin, 2024. "EV charging load profile identification and seasonal difference analysis via charging sessions data of charging stations," Energy, Elsevier, vol. 288(C).
  48. 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.
  49. 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.
  50. Liukkonen, M. & Hiltunen, T., 2014. "Adaptive monitoring of emissions in energy boilers using self-organizing maps: An application to a biomass-fired CFB (circulating fluidized bed)," Energy, Elsevier, vol. 73(C), pages 443-452.
  51. Andersen, F.M. & Larsen, H.V. & Gaardestrup, R.B., 2013. "Long term forecasting of hourly electricity consumption in local areas in Denmark," Applied Energy, Elsevier, vol. 110(C), pages 147-162.
  52. 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).
  53. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
  54. Pullinger, Martin & Zapata-Webborn, Ellen & Kilgour, Jonathan & Elam, Simon & Few, Jessica & Goddard, Nigel & Hanmer, Clare & McKenna, Eoghan & Oreszczyn, Tadj & Webb, Lynda, 2024. "Capturing variation in daily energy demand profiles over time with cluster analysis in British homes (September 2019 – August 2022)," Applied Energy, Elsevier, vol. 360(C).
  55. Turowski, M. & Heidrich, B. & Weingärtner, L. & Springer, L. & Phipps, K. & Schäfer, B. & Mikut, R. & Hagenmeyer, V., 2024. "Generating synthetic energy time series: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
  56. Angreine Kewo & Pinrolinvic D. K. Manembu & Per Sieverts Nielsen, 2020. "Synthesising Residential Electricity Load Profiles at the City Level Using a Weighted Proportion (Wepro) Model," Energies, MDPI, vol. 13(14), pages 1-28, July.
  57. Yang, Ting & Ren, Minglun & Zhou, Kaile, 2018. "Identifying household electricity consumption patterns: A case study of Kunshan, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 861-868.
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