World Energy Outlook [2] , Co2 emissions from fuel combustion highlights 2016 Key trend in CO2 emission from fuel combustion, Key World Energy Statistics, p.12, 2015. ,
Long-term forecasting of hourly electricity load: Identication of consumption proles and segmentation of customers, Energy Conversion and Management, pp.244-252, 2013. ,
Long term forecasting of hourly electricity consumption in local areas in Denmark Applied Energy Dierentiated long term projections of the hourly electricity consumption in local areas, pp.147-162, 2013. ,
Multiscale stochastic prediction of electricity demand in smart grids using Bayesian networks, Applied Energy, vol.193, pp.369-380, 2017. ,
DOI : 10.1016/j.apenergy.2017.01.017
A novel multi-time-scale modeling for electric power demand forecasting: From short-term to medium-term horizon, Electric Power Systems Research, pp.142-58, 2017. ,
Optimal twotier forecasting power generation model in smart grids, CoRR, abs/1502, p.530, 2015. ,
Benchmarking smart metering deployment in the EU-27 with a focus on electricity, 2014. ,
Bilan prévisionnel de l'équilibre ore-demande d'électricité en france, 2016, ch. Consommation d'électricité en France, p.40 ,
Residential load models for network planning purposes , in 2010 Modern Electric Power Systems, p.16, 2010. ,
Load models for operation and planning of electricity distribution networks with metering data, theses, 2012. ,
Local Short and Middle Term Electricity Load Forecasting With Semi-Parametric Additive Models, IEEE Transactions on Smart Grid, vol.5, issue.1, p.440446, 2014. ,
DOI : 10.1109/TSG.2013.2278425
MOD-DR: Microgrid optimal dispatch with demand response, Applied Energy, vol.187, pp.758-776, 2017. ,
DOI : 10.1016/j.apenergy.2016.11.093
A review of electric load classication in smart grid environment, Renewable and Sustainable Energy Reviews, p.110, 2013. ,
Modèles semi-paramétriques appliqués à la prévision des séries temporelles Cas de la consommation d'électricité Smart meter data: Balancing consumer privacy concerns with legitimate applications, 807814. [22] F. McLoughlin, A. Duffy, and M. Conlon, A clustering approach to domestic electricity load prole characterisation using smart metering data, Applied Energy, pp.41-141, 2007. ,
Customer classication and load proling method for distribution systems, IEEE Transactions on Power Delivery, vol.26, p.17551763, 2011. ,
DOI : 10.1109/tpwrd.2011.2142198
R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, 2015. ,
Clustering analysis of residential electricity demand proles, pp.461-471, 2014. ,
Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data, Applied Energy, vol.87, issue.11, pp.3538-3545, 2010. ,
DOI : 10.1016/j.apenergy.2010.05.015
Load research and load estimation in electricity distribution, theses, Technical research center of Finland, 1996. ,
Smart electricity grids and meters in the EU Member States, European Parliament, 2015. ,
A review of the decomposition methodology for extracting and identifying the uctuation characteristics in electricity demand forecasting, Renewable and Sustainable Energy Reviews, 2016. ,
Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China, Applied Energy, vol.156, pp.156-502, 2015. ,
DOI : 10.1016/j.apenergy.2015.07.037
Classication of new electricity customers based on surveys and smart metering data, Energy Region Year 2 categories 8 categories 9 categories 12 categories Blois, 2010. ,