Abstract
In response to the soaring energy crisis and the related pollution problems worldwide, it is essential to apply new technologies that use renewable energy sources in both an efficient and environmentally friendly manner. In this way, biomass offers one of the largest potential among renewable energy sources. The aim of this work is to demonstrate a novel fuzzy-based methodology for selecting hybrid energy systems fuelled by biogas. Fuzzy multi-rules and fuzzy multi-sets are used to evaluate the main operational characteristics of five types of renewable sources fuelled by biogas. The possibility of using the methodology for energy storage system evaluation is also assessed. The construction of the fuzzy multi-rules and fuzzy multi-sets is based on the following methods: Mamdani (fuzzification process), Max-Min (inference process), and Center of Gravity (defuzzification process). Several criteria are used: costs, efficiency, cogeneration, life-cycle, technical maturity, power application range, and environmental impacts. The methodology considers three different settings with two different constraints: costs and environment. One of the most relevant aspects presented by this work is about the previous classification of the criteria. It was created according to the different relevance observed among the attributes. The purpose of the proposed arrangement is to facilitate the understanding of the methodology and to increase the possibility of incorporating the decision makers’ preferences on the decision-aid process. These aspects are essential to strengthen the final decision.
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Barin, A., Canha, L.N., Magnago, K.M., Matos, M.A., Wottrich, B. (2011). A Novel Fuzzy-Based Methodology for Biogas Fuelled Hybrid Energy Systems Decision Making. In: Gopalakrishnan, K., Khaitan, S.K., Kalogirou, S. (eds) Soft Computing in Green and Renewable Energy Systems. Studies in Fuzziness and Soft Computing, vol 269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22176-7_7
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DOI: https://doi.org/10.1007/978-3-642-22176-7_7
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