Abstract
The objective of the research has been to create a model to comprehensively analyse national electricity systems. To this end, specialized literature was selected and also the opinions of a set of experts were sought. This way, it was decided which generation technologies were to be assessed, the criteria and sub-criteria to be used and their relative importance. This work presents the case study of the Spanish electricity system, analysed exclusively from the environmental dimension.
The methodology used is based on assessing each technology in a two-phase process: in the first phase, weights were obtained for every criterion and sub-criterion by means of an AHP, which also allowed to establish a first comparative ranking of technologies. The second phase includes a fuzzy inference system, which uses the weights of the criteria obtained in the AHP to attain individual fuzzy assessments of each technology.
The results showed that the most important environmental criterion is the CO2 emission, and that the best rated technology is Photovoltaic, while the worst rated is Coal.
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Acknowledgements
This work was financially supported by the State Research Agency of the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033), via the project ‘Speeding Up the transition towards Resilient circular economy networks: forecasting, inventory and production control, reverse logistics and supply chain dynamics” (SPUR, grant ref. PID2020-117021GB-I00).
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Rivero-Iglesias, J.M., Perez-Bernardo, J.M., Puente, J., Gomez, A. (2023). Analysis of the Environmental Dimension in an Evaluation Model of Electricity Generation Technologies Through AHP and a Fuzzy Inference System in Spain. In: García Márquez, F.P., Segovia Ramírez, I., Bernalte Sánchez, P.J., Muñoz del Río, A. (eds) IoT and Data Science in Engineering Management. CIO 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 160. Springer, Cham. https://doi.org/10.1007/978-3-031-27915-7_69
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