GSTDTAP  > 资源环境科学
DOI10.1016/j.enbuild.2020.110710
Embedding energy optimization in organizations: A case study of a Swiss decentralized renewable energy system
Johannes Meuer, Francesco Lamaro and Nadège Vetterli
2021
出版年2021
国家瑞士
领域资源环境
英文摘要Decentralized renewable energy systems (DRES) integrate renewable energy sources with energy-efficient building technologies and represent an important instrument for a sustainable built environment. Given their technological complexity, DRES also include comprehensive monitoring systems that offer important opportunities to optimize energy flows and increase energy efficiency. For these reasons, research has developed a range of automated optimization models and algorithms, such as association rule mining or fault detection diagnosis. To date, however, it remains unclear under what conditions these advanced and automated technologies may best be integrated to optimize DRES. This paper provides a complementary industry perspective, drawing on an in-depth case study of the optimization activities within one of the most advanced DRES in Switzerland. Over the course of five years, some of the optimization measures helped reduce energy consumption by 55–60%. Yet, the optimization potential of other measures remained unclear. The case study shows that, while technical aspects have given rise to optimization potential, organizational aspects have prevented, or at least delayed, the application of scientific algorithms, and have thus obstructed the realization of this optimization potential. These findings call for researchers to better integrate the technical and operational aspects into the optimization of energy systems and also offer important recommendations for policymakers, investors, and energy planners.
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来源平台Centre for Energy Policy and Economics
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文献类型科技报告
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/342422
专题资源环境科学
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Johannes Meuer, Francesco Lamaro and Nadège Vetterli. Embedding energy optimization in organizations: A case study of a Swiss decentralized renewable energy system,2021.
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