Prioritizing Water-Efficient Strategies in Renewable Energy Technologies Using Koch Snowflake Fuzzy Decision Support System
Keywords:
Water Consumption Reduction, Renewable Energy Projects, Koch Snowflake Fuzzy Sets, Environmental Effectiveness, Fuzzy Decision-makingAbstract
Renewable energy projects provide significant environmental and economic benefits. However, they may also involve negative impacts and potential challenges, including excessive water consumption associated with some renewable energy technologies. In this context, a key problem is the uncertainty regarding which strategies should be prioritized to effectively reduce water consumption. This gap in the literature negatively affects both academic research and the development of national energy and environmental strategies. Therefore, the main purpose of this study is to prioritize strategies for reducing excessive water consumption in renewable energy technologies according to their importance levels. For this purpose, Koch Snowflake fuzzy sets are developed and integrated into the decision-making model to manage uncertainty more effectively. Moreover, cluster-based expert selection and the SIWEC and MABAC methods are employed together to obtain comprehensive and precise results. This study contributes to the literature by providing a systematic prioritization approach for evaluating strategies aimed at reducing excessive water consumption in renewable energy technologies under uncertainty. The findings indicate that the most effective investment strategy for reducing water consumption is the development of battery technologies that use water efficiently.
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