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What is the optimal scale for fully autonomous municipal energy systems?

School of Engineering

About the Project

The energy transition requires the integration of large amounts of fluctuating, heterogeneously-spatially-distributed electricity into the energy system. Some characteristics of renewable energy resources means that their decentralised exploitation is necessary. These characteristics of renewables have led to discussions about energy autonomy. This is the idea that a region can become more or less independent from its surroundings by providing much or all of its energy from indigenous resources. However, most of these regions aim for so-called “balanced electricity autonomy”, meaning they generate enough electricity over the year in order to meet their annual demand, using the electricity network to balance out excesses and deficits. Arguably, this type of energy autonomy can result in inefficient reallocation of costs (at least under existing network cost redistribution systems), as the network is only used as a backup option (McKenna 2018). Hence the high costs of the capital infrastructure would need to be distributed across an ever-decreasing number of customers.

Complete energy autonomy relates to an island or off-grid solution, whereby a region can meet its energy demand at all times, perhaps with backup generators to ensure security of supply. Some islands already achieve this, based on 100% renewable energy sources, but in that case, the motivation is mainly technical due to a lack of interconnector. In other contexts such as Germany, this concept could also be economically attractive, however, given the right framework conditions.

On the one hand, economies of scale and the “portfolio effect”, whereby pooling larger areas ensures a smoother generation profile for renewable energies, are arguments for a higher aggregation of the energy (supply) system. On the other hand, higher aggregation results in more requirements for transmission and distribution network infrastructure, resulting in higher investments and energy losses that are proportional to the distance. The research hypothesis for this PhD is that there is an optimal scale at which it makes economic sense, under specific framework conditions, to implement an autonomous local energy system. It is the objective of this PhD to test this hypothesis, by carrying out a quantitative analysis that considers the above as well as the following aspects:

• Costs and potentials for renewable energies, and available area for these (provided by supervisors)
• Size of the region, in terms of population and area
• Type of region, e.g. urban/rural, type of network
• Existing energy system and infrastructure characteristics
• Consideration of existing network, i.e. “greenfield” or not

The output from the research should be in the form of a quantitative model that captures these interdependencies and is validated with empirical data for municipalities, which is therefore able to test the above hypothesis. Examples of similar functions for distribution networks relate the total costs to the number of customers, the length of the network and amount of transmitted energy (Kuosmanen 2012).

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 (), with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ()

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

Funding Notes

This project is advertised in relation to the research areas of the discipline of Engineering. The successful applicant will be expected to provide the funding for Tuition fees, living expenses and maintenance. Details of the cost of study can be found by visiting View Website. THERE IS NO FUNDING ATTACHED TO THIS PROJECT


Kuosmanen, T. (2012): Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model, Energy Economics, 34, 2189-2199

McKenna, R. (2018): The double-edged sword of decentralized energy autonomy, Energy Policy, Volume 113, February 2018, Pages 747–750,

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