Goal programming models with interval coefficients for the sustainable selection of marine renewable energy projects in the UK
•Adoption and development of interval coefficient goal programming models for marine renewable energy project selection.•Addressing the uncertainty associated with the coefficients and goals in the model.•Identification of potential marine renewable energy zones in the UK using the K-means clusterin...
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Published in | European journal of operational research Vol. 293; no. 2; pp. 748 - 760 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.09.2021
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Subjects | |
Online Access | Get full text |
ISSN | 0377-2217 1872-6860 |
DOI | 10.1016/j.ejor.2020.12.038 |
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Abstract | •Adoption and development of interval coefficient goal programming models for marine renewable energy project selection.•Addressing the uncertainty associated with the coefficients and goals in the model.•Identification of potential marine renewable energy zones in the UK using the K-means clustering method.
In this paper, a strategic decision making model for the sustainable development of marine renewable energy is proposed, and a specific application to the United Kingdom (UK) is demonstrated. As an island nation the UK benefits from significant marine energy potential which is providing an increasing contribution to UK's renewable energy portfolio. The paper investigates the question of how decision makers can be aided to reach a decision on which types of marine renewable energy projects should be chosen for development given that strategic energy planning is subject to a number of uncertain parameters and multiple sustainability objectives. In this context, the contribution of this paper lies in the combination of renewable energy portfolio selection and the application of multi-objective methods. Interval coefficient goal programming models are adopted in order to address the impreciseness and uncertainty associated with the goals and coefficients of the models in the context of renewable energy selection. The potential renewable energy projects are clustered in order to aid the decision making process and preferential weight sensitivity methods are employed. Conclusions are drawn for optimistic and pessimistic scenarios in the context of UK marine renewable energy planning. |
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AbstractList | •Adoption and development of interval coefficient goal programming models for marine renewable energy project selection.•Addressing the uncertainty associated with the coefficients and goals in the model.•Identification of potential marine renewable energy zones in the UK using the K-means clustering method.
In this paper, a strategic decision making model for the sustainable development of marine renewable energy is proposed, and a specific application to the United Kingdom (UK) is demonstrated. As an island nation the UK benefits from significant marine energy potential which is providing an increasing contribution to UK's renewable energy portfolio. The paper investigates the question of how decision makers can be aided to reach a decision on which types of marine renewable energy projects should be chosen for development given that strategic energy planning is subject to a number of uncertain parameters and multiple sustainability objectives. In this context, the contribution of this paper lies in the combination of renewable energy portfolio selection and the application of multi-objective methods. Interval coefficient goal programming models are adopted in order to address the impreciseness and uncertainty associated with the goals and coefficients of the models in the context of renewable energy selection. The potential renewable energy projects are clustered in order to aid the decision making process and preferential weight sensitivity methods are employed. Conclusions are drawn for optimistic and pessimistic scenarios in the context of UK marine renewable energy planning. |
Author | Jones, Dylan Akbari, Negar Arabikhan, Farzad |
Author_xml | – sequence: 1 givenname: Negar orcidid: 0000-0001-6734-0374 surname: Akbari fullname: Akbari, Negar email: negar.akbari@port.ac.uk organization: Centre for Blue Governance, Faculty of Business and Law, University of Portsmouth, Richmond building, Portland street, Portsmouth PO1 3DE, United Kingdom – sequence: 2 givenname: Dylan surname: Jones fullname: Jones, Dylan organization: Centre for Operational Research and Logistics (CORL), School of Mathematics and Physics, University of Portsmouth, Lion Gate Building, Lion Terrace, Portsmouth PO1 3HF, United Kingdom – sequence: 3 givenname: Farzad surname: Arabikhan fullname: Arabikhan, Farzad organization: School of Computing, University of Portsmouth, Buckingham Building, Portsmouth, PO1 3HE, United Kingdom |
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Keywords | Interval analysis Uncertainty Marine renewable energy Clustering Goal programming Offshore wind Energy |
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