  Data analysis plays an important role in the development of intelligent
energy networks (IENs). This article reviews and discusses the application of
data analysis methods for energy big data. The installation of smart energy
meters has provided a huge volume of data at different time resolutions,
suggesting data analysis is required for clustering, demand forecasting, energy
generation optimization, energy pricing, monitoring and diagnostics. The
currently adopted data analysis technologies for IENs include pattern
recognition, machine learning, data mining, statistics methods, etc. However,
existing methods for data analysis cannot fully meet the requirements for
processing the big data produced by the IENs and, therefore, more comprehensive
data analysis methods are needed to handle the increasing amount of data and to
mine more valuable information.
