Prototyping cloud application for regional green transformation supported by prospective life cycle assessment

• Published in: Computer Aided Chemical Engineering Vol. 53; pp. 3463 - 3468
• Main Authors: Kanematsu, Yuichiro, Fujii, Shoma, Oshita, Yuko, Ohara, Satoshi, Komori, Atsushi, Shimotoku, Daisuke, Iizuka, Katsura, Kawase, Junya, Kobayashi, Hiroki, Kikuchi, Yasunori
• Format: Book Chapter
• Language: English
• Published: 2024
• Subjects: Life cycle assessment; Local resource circulation; Renewable energy; Life cycle assessment; Renewable energy; Local resource circulation
• ISBN: 9780443288241; 0443288240
• ISSN: 1570-7946
• DOI: 10.1016/B978-0-443-28824-1.50578-0

Regional green transformation (GX) requires collaborative planning among local entities, integrating various technologies and life cycle thinking. A cloud-based information system prototype was developed in this study to expedite GX planning through prospective life cycle assessment (LCA), incorporating simulators, visualization tools, and local databases. The information system's conceptual design includes separate activity and data models. These models focus on the regional system's basic design, allowing planners to configure device installations, simulate mass/energy balances, and generate inventory data for LCA. Rationales are derived from previous case studies involving prospective LCA. The activity model covers local supply-demand analysis, alternative generation, mass & energy simulation, evaluation, and installation planning. The data model defines essential datasets for simulators used in prospective LCA of emerging technologies. The information system's function requirements, including prototypes for applications like GIS-based visualizers and energy flow diagrams, were defined using activity and data models. Datasets were integrated from statistical open data, and a technology database was created for matching technology with regional supply/demand. Simulators for specific technologies are being developed on a local server with plans for cloud integration, and the simulation results can used as the data to perform LCA. The entire system architecture based on an academic cloud infrastructure was discussed and the tools mentioned above will be integrated into a holistic application in near future.