Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden

被引:19
|
作者
Liu, Bokai [1 ]
Penaka, Santhan Reddy [1 ]
Lu, Weizhuo [1 ]
Feng, Kailun [1 ]
Rebbling, Anders [2 ]
Olofsson, Thomas [1 ]
机构
[1] Umea Univ, Dept Appl Phys & Elect, Intelligent Human Bldg Interact Lab, S-90187 Umea, Sweden
[2] Umea Univ, Dept Appl Phys & Elect, S-90187 Umea, Sweden
基金
欧盟地平线“2020”; 瑞典研究理事会;
关键词
Energy retrofits; Data-driven modeling; Decision support systems (DSS); Quantitative analysis; Open ecosystem platform; STOCHASTIC PREDICTIONS; SENSITIVITY-ANALYSIS; PLANNED BEHAVIOR; NANOCOMPOSITES; RENOVATION; FRAMEWORK;
D O I
10.1016/j.techsoc.2023.102347
中图分类号
D58 [社会生活与社会问题]; C913 [社会生活与社会问题];
学科分类号
摘要
This paper presents an open digital ecosystem based on a web-framework with a functional back-end server for user-centric energy retrofits. This data-driven web framework is proposed for building energy renovation benchmarking as part of an energy advisory service development for the Va center dot sterbotten region, Sweden. A 4-tier architecture is developed and programmed to achieve users' interactive design and visualization via a web browser. Six data-driven methods are integrated into this framework as backend server functions. Based on these functions, users can be supported by this decision-making system when they want to know if a renovation is needed or not. Meanwhile, influential factors (input values) from the database that affect energy usage in buildings are to be analyzed via quantitative analysis, i.e., sensitivity analysis. The contributions to this open ecosystem platform in energy renovation are: 1) A systematic framework that can be applied to energy efficiency with data-driven approaches, 2) A user-friendly web-based platform that is easy and flexible to use, and 3) integrated quantitative analysis into the framework to obtain the importance among all the relevant factors. This computational framework is designed for stakeholders who would like to get preliminary information in energy advisory. The improved energy advisor service enabled by the developed platform can significantly reduce the cost of decision-making, enabling decision-makers to participate in such professional knowledge-required decisions in a deliberate and efficient manner. This work is funded by the AURORAL project, which integrates an open and interoperable digital platform, demonstrated through regional large-scale pilots in different countries of Europe by interdisciplinary applications.
引用
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页数:13
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