Data and Modelling

SERG has extensive experience in collecting and analysing a range of energy generation and consumption data and this expertise underpins many of our other research activities.


8th March, 2018

SERG’s Dr Ben Anderson recently gave an Otago Energy Research Centre seminar on the SAVE project results to date. He was also invited to give an interview to the University of Otago’s radio station, RadioOne 91FM (“Aotearoa’s southernmost student radio station!”). Interview:   Seminar abstract: “Whilst overall reduction of energy demand is receiving increasing policy […]


13th February, 2018

Full paper: Anderson, Ben, Manouseli, Despoina and Nagarajan, Magesh (2018) Estimating scenarios for domestic water demand under drought conditions in England and Wales Water Science & Technology: Water Supply (Open Access (CC BY 4.0): doi:10.2166/ws.2018.035) Abstract: This paper presents preliminary results from the development of IMPETUS model, a domestic water demand microsimulation model which was […]


26th January, 2018

The 9 Case Studies showcase the breadth and applicability of the Liveable Cities research to practice and to everyday life. A copy of the case studies is available to download here: #1 Natural Capital in Birmingham. by Nick Grayson, Jonathan Sadler, James Hale, Martin Locret-Collet and Chris Bouch #2 Energy, Transport and Waste in Birmingham: […]


1st December, 2017

SERG’s Dr Ben Anderson has just started the outgoing phase of his EU H2020 Marie Skłodowska-Curie scheme-funded SPATIALEC Global Fellowship. Based at the University of Otago’s Centre for Sustainability, Ben will initially be working on combining time use and electricity monitoring data from the New Zealand GREEN Grid  project with  New Zealand Census data to […]


THERMOSS is a multidisciplinary project funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No 723562. THERMOSS aims to contribute to the wider deployment of advanced building heating and cooling technologies in the EU, with a view to significantly enhance energy efficiency of residential buildings and to facilitate their connection […]


21st November, 2017

SERG’s Dr Ben Anderson presented the SAVE study design and trial period 1 preliminary analysis at Scottish and Southern Energy Network’s Using Energy Efficiency to Defer Network Reinforcement parliamentary event at the Houses of Parliament on November 20th, 2017. With an introduction from Alan Whitehead MP (Shadow Minister (Department for Business, Energy and Industrial Strategy) […]


15th October, 2017

Dr Despina Manouseli presented a poster on the IMPETUS domestic hot water demand model at the annual Behavior Energy and Climate Conference in Sacramento, California in October 2017. The poster presented a novel, practices-based approach to hot water demand estimation ‘under normal conditions’ using microsimulation to forecast seasonal demand at the household level under various water/energy conservation scenarios. The models suggest that the installation […]


6th October, 2017

Full paper: Manouseli, D., Anderson, B. & Nagarajan, M. (2017) Domestic Water Demand During Droughts in Temperate Climates: Synthesising Evidence for an Integrated Framework, Water Resource Management. (Open Access) Abstract: Extreme weather events and variations that alter drought and flood frequency add to these pressures and there is therefore a need to develop evidence-based drought […]


28th August, 2017

SERG is to colloborate with a team led by UCL to deliver the new GB Smart Meter Research Portal (SMRP) with funding from the UK Engineering and Physical Sciences Research Council. SMRP will provide a secure, consistent and trusted channel for researchers to access high-resolution smart meter energy consumption data, which will facilitate innovative energy […]


SERG PhD student Mikey Harper is working on a number of methods to assess the potential for wind turbine development in the UK. As part of this he has produced a map of on-shore wind turbine planning applications to date and has also developed a model for predicting the likelihood of planning success for future sites. […]