Demand charges and user flexibility – Exploring differences in electricity consumer types and load patterns within the Swedish commercial sector

Identifying and estimating the effects of a mandatory billing demand charge

(2019) Isak Öhrlund et al.   APPLIED ENERGY

Demand response in the service sector – Theoretical, technical and practical potentials

(2019) Katharina Wohlfarth et al.   APPLIED ENERGY

A Hybrid Machine Learning Model for Electricity Consumer Categorization Using Smart Meter Data

(2018) Zigui Jiang et al.   Energies

A Dedicated Mixture Model for Clustering Smart Meter Data: Identification and Analysis of Electricity Consumption Behaviors

(2017) Fateh Melzi et al.   Energies

An overview of Demand Response: Key-elements and international experience

(2017) Nikolaos G. Paterakis et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers

(2016) Dongsik Jang et al.   ENERGY POLICY

Uptake and usage of cost-reflective electricity pricing: Insights from psychology and behavioural economics

(2016) Elizabeth V. Hobman et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

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

(2016) Stephen Haben et al.   IEEE Transactions on Smart Grid

Demand responses of Korean commercial and industrial businesses to critical peak pricing of electricity

(2015) Dongsik Jang et al.   JOURNAL OF CLEANER PRODUCTION

Clustering time-series energy data from smart meters

(2014) Alexander Lavin et al.   Energy Efficiency

Classification and Clustering of Electricity Demand Patterns in Industrial Parks

(2012) Luis Hernández et al.   Energies

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

(2012) Fintan McLoughlin et al.   ENERGY AND BUILDINGS

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

(2010) Teemu Räsänen et al.   APPLIED ENERGY