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Mr Ed Sharp
Central House
14 Upper Woburn Place
  • Research Associate
  • Bartlett School Env, Energy & Resources
  • Faculty of the Built Environment

I am a geospatialist and energy modelller researching the spatio-temporal variation of renewable weather driven supply, domestic energy demand, non domestic stock models and air pollution in Europe. My overall aim is to improve aggregated scenario modelling by introducing spatial and temporal variation at a fine resolution using knowledge and methods from data science, GIScience and industry.

Examples of recent work I have done as part of my PhD and elsewhere can be seen on my blog at www.esenergyvis.wordpress.com .

Research Themes
Research Summary

Working as part of the Energy, Space Time Group I have been part of two large projects. The SiCEDS project developed an interactive energy demand simulation tool for cities to assist stakeholders in making decisions where to invest money in energy infrastructure and efficiency measures. The project has been funded by innovate UK and is being carried out in conjunction with the Energy Savings Trust, Aecom and Fraser Nash and will shortly be available commercially. The second, ongoing, project aims to investigate the roles of transmission and storage in a high renewables future for Europe.

I have worked on the development of novel methods to estimate demand and generation, data identification, extraction and cleaning, model testing and calibration, analysis and visualisation for both projects.

Alongside these projects I have collaborated on publications with colleagues, supervised masters students and presented at conferences and professional events.

During my PhD I developed a modelling framework to facilitate disaggregation of national energy scenarios to an hourly temporal and 0.5o spatial resolution.  The model analysis focused on wind generation simulation, where multiple spatial configurations of capacity were simulated as well as demand scenarios depicting changing building stock, population and heating technologies. High resolution weather data drove modelling, representing a 30 year climatology. Simulations using this framework have been used to develop forecasting models and have been fed into dynamic dispatch modelling.

Teaching Summary

I have supervised a number of research students on the Energy Institute's Economics and Policy of Energy and the Environment Masters degree, all of whom have passed with distinction.

I have also taught on Energy Systems and Research Methods course on he Energy Institute's MRes in Energy Demand Studies and the Institute for Environmental Design and Engineering's MSc of the same name.

I advise a number of PhD and Masters student on the effective use of weather data and or Python in their simulation and analysis.

Academic Background
2015 PhD Doctor of Philosophy – Energy Modelling University College London
2011 MRes Master of Research – Energy Systems and the Environment University College London
2010 MSc Master of Science – Geographical Information Systems University College London
2004 BSc Bachelor of Science – Geography University of Leeds
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