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How can energy demand profiles and potential responses to time of use tariffs be segmented?

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Source

This question was published as part of the set of ARIs in this document:

Beis areas research interest interim update 2020

Related UKRI funded projects


  • OFfSET - Optimised Forecasting for Switching Energy Tariffs

    "The Optimising & Forecasting for Switching Energy Tariffs ""OFfSET"" project brings Samsung's UK-based Research team together with energy market disruptors Labrador and home energy managemen...

    Funded by: Innovate UK

    Lead research organisation: SAMSUNG ELECTRONICS (UK) LIMITED

    Why might this be relevant?

    The OFfSET project specifically focuses on time-of-use tariffs and energy demand profiles, which directly addresses the question.

  • Distributional Effects of Dynamic Pricing for Responsive Electricity Demand (DEePRED)

    Peak electricity demand is becoming an increasingly significant problem for UK electricity networks as it causes imbalances between demand and supply with negative impacts on system costs and the environment. The residen...

    Funded by: EPSRC

    Lead research organisation: University of Reading

    Why might this be relevant?

    The DEePRED project aims to analyze the distributional effects of time-of-use tariffs, which directly addresses the question.

  • Advanced Dynamic Energy Pricing and Tariffs (ADEPT)

    This project addresses a crucial research question that must be answered in the near term is How complicated can, or should, a dynamic electricity tariff be? , such that it is accepted by the public and offers clear enha...

    Funded by: EPSRC

    Lead research organisation: University of Oxford

    Why might this be relevant?

    The ADEPT project addresses the question partially by looking at dynamic electricity tariffs, but it does not specifically mention time-of-use tariffs or energy demand profiles.

  • Residential Electricity Demand: Peaks, Sequences of Activities and Markov chains (REDPeAk)

    Peak electricity demand is becoming an increasingly significant problem for UK networks as it causes imbalances between demand and supply with negative impacts on system costs and the environment. The residential sector ...

    Funded by: EPSRC

    Lead research organisation: University of Reading

  • Celes - Enabling Demand Side Response

    The project is to take a concept - Celes - and turn it into a useful pre-production prototype. Celes is a device for the home that will measure and control electricity usage - mainly for time insensitive application (&q...

    Funded by: Innovate UK

    Lead research organisation: EFC LIMITED

  • SmartSTOR

    The UK has committed itself to the universal roll out of smart meters - 53million for all homes and small businesses with 3.6million installed so far. An enabler for half hourly billing, smart meters are seen as a prec...

    Funded by: Innovate UK

    Lead research organisation: POWERVAULT LTD

  • Multiscale Modelling to maximise Demand Side Management (Part 2)

    Modern energy systems are complex technical, social and economic endeavours formed through the assembly of a broad set of elements and shaped by the actions of many multiple actors including consumers, suppliers and regu...

    Funded by: EPSRC

    Lead research organisation: University of Nottingham

  • Skyprospector - Predicting savings from “microgeneration aware” dynamic demand technology

    Skyprospector is a service that enables electricity customers to determine the mix of microgeneration and dynamic demand shifting technologies that provides the best return on investment for their context. The Skyprospec...

    Funded by: Innovate UK

    Lead research organisation: CLEAN ENERGY PROSPECTOR LTD

  • Responsive Algorithmic Enterprise (RAE)

    Demand side response is a method whereby financial incentives are used to encourage customers to lower electricity use at peak times. This enables load, voltage, thermal, balance and other constraints on the electricity ...

    Funded by: EPSRC

    Lead research organisation: University of Reading

  • New Methods and Data for Energy Research (NEMDER)

    Energy system modelling has been driven, at best, annual data series at national or regional level. The roll-out of smart meters along with the increasing availability of new forms of user data from crowdsourced platform...

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    Lead research organisation: CRANFIELD UNIVERSITY