Conclusions
The main conclusions based on the results obtained for the city of Glasgow are the following.
Deployment of renewable technologies within cities could certainly make a significant contribution towards the overall electricity demand of EVs, both in the short-term and long-term future.
In the short term, existing areas of easily developed vacant and derelict land has the potential to meet the electricity demand through the development of solar PV arrays. This land would be sufficient to meet the energy requirements of both Scenario 2024 and Scenario 2030.
In the long term, policy relaxation has the potential to open up significant areas of vacant and derelict land to development. Furthermore, it is still technically possible to meet the increased electricity demand seen in Scenario 2050. This, however require significant changes to the city landscape, with a strong socio-political consensus needed between private companies, the city council, and local residents to realise the overall aims of providing clean energy within the city confines.
Car parks could prove to be an invaluable resource when looking for additonal areas of land to make contribtions towards EV electricity demand. They may prove to be a particularly viable solution in cities where the electrical grid is less developed than that of Glasgows, as these canopies can be co-located with charge points to supply vehicles independantly from the grid.
Issues & Further Work
The EVs demand calculations were obtained by drawing upon assumptions, and charging behaviours were not considered. The results could have been made more accurate if charging behaviours had been taken in to consideration. However, to do so, we would have needed to predict future charging patterns, and as there are many variables involved, this would have increased the uncertainty of the results obtained.
Due to the intricate nature of calculating shading with time, more comprehensive geometric data could be added to make it more accurate. Independent site appraisal would also predict how shading from buildings would affect the energy output of a solar array. The same would be necessary to predict turbulence on wind turbines performance. A full cost analysis was not preformed due to predicted fast changing prices of technology over the scenarios time-scale; optimizing for cost of renewable deployment would improve the robustness of the project.
The GOMAP GIS software is complex and requires a vast amount of detailed data including site coordinates and technical appraisals of sites in order to provide a complete evaluation of land areas and constraints. While we were helped greatly by the fact that much of the data had already been inputted, manipulating this data to simulate policy changes or contributions often proved complicated and time consuming. Obtaining land areas involving the chosen policy combinations often gave inconsistent results between simulations. This meant that a fresh installation of the software had to be redownloaded numerous times to ensure the final areas used were correct and not carrying any changes from previous simulations.
For this project it would be beneficial to create and implement additional layers of information to develop a more comprehensive analysis of charge point distribution across the city. This could be achieved by adding a layer of already existing charge point locations. This, in combination with existing layers showing available land and the current 11kV grid network, would allow for a strategy for targetting areas lacking in existing charge points.