SMAP Energy

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Determining Load Profiles for Customers in the Indicated DSO Area based on Smart Meters: A Summary Report for European Data Incubator

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LONDON, 17 February 2020 -SMAP Energy was selected to participate in the European Data Incubator – a Horizon 2020 funded program focused on building innovative data applications. This paper details the work undertaken in the project and the results achieved. Links  Report Publication – European_Data_Incubator  Online Demo (to gain access, request login information from info@smapenergy.com) – …

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Successful results from trial of Japan’s first smart-meter-enabled TOU tariff

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TOKYO, 26 November 2018 UK energy data analytics startup SMAP Energy and Japanese energy retailer Looop collaborated on the creation of Japan’s first smart-meter-enabled time of use (TOU) tariff. The program was novel in that it only relied on smart-meter data and SMAP Energy’s proprietary algorithms to optimise engagement. 1300 Japanese energy consumers joined the …

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Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes

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CAMBRIDGE, 23 Oct 2018 Authors: Eoghan O’Neill (Faculty of Economics, University of Cambridge, UK), Melvyn Weeks (Faculty of Economics and Clare College, University of Cambridge, UK) Full publication: Link We examine the distributional effects of the introduction of Time-of-Use (TOU) pricing schemes where the price per kWh of electricity usage depends on the time of …

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Demand Response Models for Smart Meter Data: Estimation of Conditional Average Treatment Effects Using Many Covariates – An Application to Electricity Smart Meter Trial Data

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Lead Investigator: Dr. Melvyn Weeks, Faculty of Economics, University of Cambridge, UK Coauthor: Eoghan O’Neil, Faculty of Economics, University of Cambridge, UK The investigation of treatment effect heterogeneity is of interest in many fields including economics and personalised medicine. In some applications, there are many available covariates and functions of covariates that are plausibly associated …

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Forecasting Intra-Day Load Profiles under Time-Of-Use tariffs Using Smart Meter Data

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Authors Kiguchi Ya , Heo Yb,  Weeks Mc, Choudhary Rad a Department of Engineering, University of Cambridge, UK b School of Civil, Environmental, and Architectural Engineering, Korea University, South Korea c Faculty of Economics and Clare College, University of Cambridge, UK d Data-centric Engineering, Alan Turing Institute, UK   Publication Details Energy, Volume 173, 15 April 2019, Pages 959-970 Received 17 February 2018, Revised 9 December 2018, Accepted 9 …

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Tariff Design: The Design of Optimal Tariffs for One-Day Ahead Load Forecasting

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Lead Investigator: Dr. Melvyn Weeks, Faculty of Economics, University of Cambridge, UK Coauthor: Bowei Guo, Faculty of Economics, University of Cambridge, UK Governments across Europe and beyond are planning to integrate large quantities of intermittent wind and solar into the electricity grid. In this context, and with the timing of renewable supply largely fixed, a …

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Time for an energy change: A deep-dive into Japan’s first smart-meter-enabled TOU tariff

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TOKYO, 27 February 2018 – Japanese energy retailer Looop Inc. announced today the offering of the Looop time-of-use (TOU) tariff – the first of its kind in Japan. The new product was created utilizing smart-meter data and SMAP Energy’s Smart-Meter Analytics Platform – which leverages novel artificial intelligence algorithms to extract behavioural insight. Why is …

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Competition Impacts of Energy Tariff Options: There and Back Again

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CAMBRIDGE, 22 March 2017 Author: Paul Monroe, Co-Founder, SMAP Energy Cambridge University Science and Policy Exchange (Link) Ensuring sufficient competition in the energy market is a key role of the regulator. One of the most popular measures for measuring competition has been in the analysis of customers switching between energy tariff plans. Unfortunately, switching rates are …

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