About the Project
• Improve the consideration of non-technical aspects within these methods, for example public acceptance of wind turbines, through open data on landscape value or economic data relating to valuations in the vicinity of wind parks (Price et al. 2020, McKenna et al. 2020)• Improve the accuracy of existing methods for automatic recognition of rooftop geometries from Open Street Map and Bing Maps, in order to identify potential locations for solar PV modules (Mainzer et al. 2017).
• Consolidate and extend existing methods of land suitability assessment for renewable energy technologies based on open data. In particular, this means clarifying definitions of land use categories, offset distances and their implications. Ryberg et al. 2019, 2018.
• Explore possibilities to exploit remote-sensing data for energy system modelling, e.g. building outlines and geometry, energy infrastructure etc.
• Further developing potential assessment methods for offshore wind based on existing studies and literature in this area.
It is expected that the PhD project will build on existing tools and should therefore implement the above improvements within a modelling framework that can be interactively employed by diverse stakeholders (including experts and non-experts).
Candidates should have (or expect to achieve) the UK honours degree at 2.1 or above (or equivalent) in Engineering, Mathematics, Energy Engineering, Industrial Engineering (and Management). It is essential that the applicant has a background in Energy Systems Modelling, Programming, Geographical Information Systems (GIS), Optimization, Simulation along with knowledge of MATLAB, GAMS, ArcGIS, R, Python, Java
• Apply for Degree of Doctor of Philosophy in Engineering
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form
When applying please ensure all required documents are attached:
• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV
Informal inquiries can be made to Professor R McKenna ([email protected]), with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ([email protected])
It is possible to undertake this project by distance learning. Interested parties should contact Professor McKenna to discuss this. Distance Learning applicants should have access to a good quality computer
- Ryberg, D. S., Tulemat, Z., Stolten, D., & Robinius, M. (2019). Uniformly constrained land eligibility for onshore European wind power. Renewable Energy, 146(0960–1481), 921–931. https://doi.org/10.1016/j.renene.2019.06.127
- Ryberg, D. S., Robinius, M., Stolten, D. (2018): Evaluating Land Eligibility Constraints of Renewable Energy Sources in Europe, energies, 11, 1246.
- Price, J., Mainzer, K., Petrovic, S., Zeyringer, M., McKenna, R. (2020): The implications of landscape visual impact on future highly renewable power systems: a case study for Great Britain, IEEE Transactions on Power Systems, in press, May 2020.
- McKenna, R., Hollnaicher, S., Ostmann v. d. Leye, P., Fichtner, W. (2015): Cost-potentials for large onshore wind turbines in Europe, Energy, Volume 83, 1 April 2015, Pages 217–229.
- McKenna, Russell; Weinand, Jann Michael; Mulalic, Ismir; Petrovic, Stefan; Mainzer, Kai; Preis, Tobias; Moat, Helen Susannah (2020), Improving renewable energy resource assessments by quantifying landscape beauty, IIP Working Paper Series in Production and Energy, No. 43, April 2020.
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