Location, Location, Location: Strategic Planning for Renewable Energy Siting

One of the main challenges in renewable energy (RE) development in the UK is the lack of strategic planning in siting of RE technologies, which often results in lower than expected device performance, longer project development lifecycles and lower profitability for developers. The PhD student will help develop a methodology for creating spatially-explicit RE strategies. Specifically (s)he will 1) map, at high spatial and temporal resolution (spatial: 100*100m grid; temporal: monthly or seasonal aggregate measures derived from hourly data), RE resources and potential profitability of different RE technologies across a region, permitting understanding of how potential supply varies at different times and how this compares to grid capacity and demand at different locations. 2) Map at equally high resolution, the "biodiversity value" of different locations. There are a number of ways in which "biodiversity value" can be measured, and it is our intention to develop a scoring system that reflects planning legislation. For example, particularly locations that host high densities of the designated features of Natura 2000 sites would be given higher weighting, as would UK Biodiversity Action Plan priority species and habitats. (3) Identify, map and account for other constraints that could or will affect the development of a renewable installation, e.g., urban area or locations where resistance from people living in the vicinity of a proposed development is likely. (4) Identify the best locations for installation, where, for example, they would be more profitable, or where land-use conflict is minimised.

The ultimate output of the PhD is a user-friendly, useful and flexible decision support tool that can be refined as better information becomes available, but which permits far better strategic planning for RE in the UK than is currently in place. The tool will allow real-time exploration of different scenarios: one may, e.g., wish to explore how the location of the top 10% of most favourable locations changes if one ascribes a different scoring system or weighting to biodiversity or if dual-axis solar-tracking devices instead of static panels are used. While suitably challenging for a PhD student, the availability of pre-existing datasets and topic of the study being an established focal area of research of the supervisory team, ensures that the PhD has a very high chance of successful completion with the prescribed timeframe. During the PhD, the student will acquire skills that are highly desirable in the work place. These include technical skills such as engineering-based modelling and spatial analyses, and transferrable skills such as strategic thinking, time management and stakeholder engagement.