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Structured Literature Review of Electricity Consumption Classification Using Smart Meter Data

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Cluster Analysis of Smart Metering Data

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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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A clustering approach to domestic electricity load profile characterisation using smart metering data

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Characterising domestic electricity consumption patterns by dwelling and occupant socio-economic variables: An Irish case study

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Unraveling electricity consumption profiles in households through clusters: Combining smart meters and door-to-door surveys

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Determining the relationship between a household’s lifestyle and its electricity consumption in Japan by analyzing measured electric load profiles

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Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior

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Cross-domain feature selection and coding for household energy behavior

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Classification of new electricity customers based on surveys and smart metering data

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Hopfield–K-Means clustering algorithm: A proposal for the segmentation of electricity customers

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Dynamic clustering segmentation applied to load profiles of energy consumption from Spanish customers

inferredcites →https://doi.org/10.1016/j.rser.2014.08.035openalex-snapshot

Demand side management using artificial neural networks in a smart grid environment

inferredcites →https://doi.org/10.1049/iet-gtd.2009.0161openalex-snapshot

Renyi entropy-based classification of daily electrical load patterns

inferredcites →https://doi.org/10.1109/tii.2016.2528819openalex-snapshot

Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data

inferredcites →https://doi.org/10.1109/tpwrs.2006.873122openalex-snapshot

Comparisons Among Clustering Techniques for Electricity Customer Classification

inferredcites →https://doi.org/10.1109/tpwrs.2013.2266122openalex-snapshot

Smart Meter Driven Segmentation: What Your Consumption Says About You

inferredcites →https://doi.org/10.1109/tpwrs.2014.2377213openalex-snapshot

Impacts of Raw Data Temporal Resolution Using Selected Clustering Methods on Residential Electricity Load Profiles

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Segmentation and Classification of Commercial Building Occupants by Energy-Use Efficiency and Predictability

inferredcites →https://doi.org/10.1109/tsg.2015.2409786openalex-snapshot

Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data

inferredcites →https://doi.org/10.1111/j.1467-9892.2010.00677.xopenalex-snapshot

Random effects mixture models for clustering electrical load series

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A Guide to Conducting a Standalone Systematic Literature Review

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Data-Driven Baseline Estimation of Residential Buildings for Demand Response

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Electricity Customer Clustering Following Experts’ Principle for Demand Response Applications

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On the Inequity of Flat-rate Electricity Tariffs

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