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Developing a high-resolution spatial model to assess solar photovoltaic panel suitability for reduction of greenhouse gas emissions and energy costs

   Faculty of Health and Life Sciences

  Dr Paul McKenzie, Dr Saad Bhatti, Prof P Jordan  Monday, February 06, 2023  Competition Funded PhD Project (Students Worldwide)

About the Project

Low Carbon Technologies such as solar PV can reduce greenhouse gas (GHG) emissions and generate electricity for self-consumption, which cut down the import of energy from the grid which is susceptible to energy price shocks.

Geographic Information Systems (GIS) and remote sensing have demonstrated high levels of effectiveness for identifying suitable sites for solar PV at a range of spatial scales. Light Detection and Ranging (LiDAR) data are highly suited for modelling small scale features in complex landscapes. This project aims to determine the potential of solar PV to reduce CO2 emissions and reduce energy demand for a region of Northern Ireland by using LiDAR and ancillary spatial data to create a high-resolution solar PV suitability model.

The successful candidate is expected to acquire, process, and analyse geospatial data, particularly collected through remote sensing methods including LiDAR, to develop a spatial model for solar PV panel suitability. The candidate will also calculate a range of metrics based on solar PV models relating to GHG emissions and residential energy demand, along with reviewing and analysing the opportunities and challenges towards adopting solar PV panels in Northern Ireland.


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