Integrated model for the assessment of power generation alternatives through analytic hierarchy process and a fuzzy inference system. Case study of Spain

Jose M. Rivero-Iglesias, Javier Puente, Isabel Fernandez and Omar León

Renewable Energy, 2023, vol. 211, issue C, 563-581

Abstract: The main objective of this research was to create a robust hierarchical model to evaluate the power generation technologies in the energy mix of any country, with particular emphasis on its use in the case study of Spain. An exhaustive literature review allowed to identify a balanced number of the most relevant criteria that the model should consider to evaluate the seven alternatives that cover most of the Spanish energy demand. Through expert knowledge, the Analytic Hierarchy Process (AHP) methodology allowed to obtain the local and global weights of the criteria used in the model. Using these weights and the assessments of alternatives for each criterion, their ranking was determined through both AHP and a novel fuzzy inference system (FIS), whose inference rules were automatically constructed based on the weights of the criteria and a distance minimization method. The design of this FIS constitutes the main contribution of the work, firstly, because it avoids a second round of experts consultations and, secondly, because it systematically conceptualises the knowledge base that allows to infer the individual evaluation of any alternative, without the risk of rank reversal that may occur if using only AHP. The results of the case study of Spain showed that environmental was the most important criterion. In terms of the comparative AHP merit order, Photovoltaic (PV) was ranked first and Coal last. In addition, the individual assessment of the technologies through FIS yielded results consistent with the previous AHP ranking. Finally, a sensitivity analysis was performed, which showed good stability in the results obtained.

Keywords: Multi-criteria decision making (MCDM); Analytic hierarchic process (AHP); Fuzzy inference system (FIS); Power generation technologies; National power systems (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:211:y:2023:i:c:p:563-581

DOI: 10.1016/j.renene.2023.04.101

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