Life cycle sustainability assessment of local renewable energy systems using fuzzy logic

Kalogerakis, Antonios (2025) Life cycle sustainability assessment of local renewable energy systems using fuzzy logic. Doctoral thesis, Lancaster University / University of Cumbria.

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Abstract

The advocacy for renewable energy technologies as a means of establishing a more sustainable and low-carbon electricity mix is evident at the UK, as reflected in national energy and climate plans. However, it remains challenging to identify realistic scenarios and evaluate the overall performance of current renewable energy technologies, taking into account their environmental, economic, and social impacts throughout their life cycle, particularly at the local level. This thesis introduces an innovative life cycle sustainability framework. This framework involves: i) developing small scale renewable energy scenarios, ii) assessing them using environmental and social life cycle assessment and costing, and iii) conducting an integrated sustainability assessment using fuzzy logic. The method is focued on the county of Cumbria, considering three scenarios spanning from 2015 to 2030, which came from Cumbria County Council documents: 1) business-as-usual deployment projections, 2) the UK renewable strategy mix, and 3) no new development of commercial wind. The results indicate that scenario 1 is the most favorable, followed by Scenarios 2 and 3. Even though scenario 1 does not achieve the highest scores in all intermediate life cycle assessments, this framework has the potential to enhance the decision-making process for local renewable energy planning. The innovation of this thesis lies in the development of a highly specialized model – which is called iCumbRIA and it is a development of this PhD – tailored specifically for the county of Cumbria. This model, utilizing real data, uniquely integrates state-of-the-art tools such as Life Cycle Sustainability Assessment (LCSA), which considers not only environmental but also economic and social parameters. The incorporation of fuzzy logic further distinguishes this thesis as a pioneer in its field. The results generated by this approach hold practical utility for decision-makers and stakeholders, offering valuable insights applicable in real-world.

Item Type:	Thesis/Dissertation (Doctoral)
Departments:	Institute of Science and Environment > Forestry and Conservation
Additional Information:	This thesis is submitted for the degree of Doctor of Philosophy (in accordance with University of Cumbria procedures and in compliance with Lancaster University regulations), submitted January 2024, revised August 2025, word count 64,403.
Depositing User:	Anna Lupton
Date Deposited:	22 Aug 2025 14:13
Last Modified:	23 Aug 2025 08:00
URI:	https://insight.cumbria.ac.uk/id/eprint/9004

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