{"title":"分布式智能电网中数字基础设施的环境评价","authors":"Daniela Wohlschlager, Anika Neitz-Regett, Bastian Lanzinger","doi":"10.1109/SEGE52446.2021.9535061","DOIUrl":null,"url":null,"abstract":"This paper examines the life cycle-based direct environmental impact of information and communication technology (ICT) in German smart grids. Specifically, it explores the global warming potential associated with smart metering infrastructure and the use case of decentralized flexibility markets. Results show an annual footprint of 513,679 t CO2-eq. for the intelligent metering infrastructure expected in low-voltage levels by 2030. Digitalization measures required for a household to provide flexibility from decentralized assets cause approx. 27 to 43 kg CO2-eq. per household and year. Given the marginal data volume associated with the use case, the operation and production phases of hardware cause the greatest impact. Accordingly, considerable reduction potentials lie in decarbonizing the electricity mix and ensuring high energy efficiency and longevity of components. As more data-intensive use cases emerge, the method provided in this paper enables further environmental assessments of direct effects and the derivation of recommendations for a sustainable technical design. First qualitative estimations of indirect environmental effects indicate the need for subsequent research in the context of smart grids, including behavioral research and energy system modeling approaches.","PeriodicalId":438266,"journal":{"name":"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Environmental Assessment of Digital Infrastructure in Decentralized Smart Grids\",\"authors\":\"Daniela Wohlschlager, Anika Neitz-Regett, Bastian Lanzinger\",\"doi\":\"10.1109/SEGE52446.2021.9535061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper examines the life cycle-based direct environmental impact of information and communication technology (ICT) in German smart grids. Specifically, it explores the global warming potential associated with smart metering infrastructure and the use case of decentralized flexibility markets. Results show an annual footprint of 513,679 t CO2-eq. for the intelligent metering infrastructure expected in low-voltage levels by 2030. Digitalization measures required for a household to provide flexibility from decentralized assets cause approx. 27 to 43 kg CO2-eq. per household and year. Given the marginal data volume associated with the use case, the operation and production phases of hardware cause the greatest impact. Accordingly, considerable reduction potentials lie in decarbonizing the electricity mix and ensuring high energy efficiency and longevity of components. As more data-intensive use cases emerge, the method provided in this paper enables further environmental assessments of direct effects and the derivation of recommendations for a sustainable technical design. First qualitative estimations of indirect environmental effects indicate the need for subsequent research in the context of smart grids, including behavioral research and energy system modeling approaches.\",\"PeriodicalId\":438266,\"journal\":{\"name\":\"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SEGE52446.2021.9535061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEGE52446.2021.9535061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
本文研究了德国智能电网中基于生命周期的信息和通信技术(ICT)对环境的直接影响。具体来说,它探讨了与智能计量基础设施和分散灵活市场用例相关的全球变暖潜力。结果表明,年足迹为513,679 t co2当量。预计到2030年,低压水平的智能计量基础设施。家庭为分散资产提供灵活性所需的数字化措施引起了广泛的关注。27至43千克二氧化碳当量按家庭和年计算。考虑到与用例相关的边缘数据量,硬件的操作和生产阶段会产生最大的影响。因此,相当大的减排潜力在于使电力结构脱碳,并确保组件的高能效和寿命。随着更多数据密集型用例的出现,本文提供的方法可以对直接影响进行进一步的环境评估,并为可持续技术设计提供建议。首先,对间接环境影响的定性估计表明,需要在智能电网的背景下进行后续研究,包括行为研究和能源系统建模方法。
Environmental Assessment of Digital Infrastructure in Decentralized Smart Grids
This paper examines the life cycle-based direct environmental impact of information and communication technology (ICT) in German smart grids. Specifically, it explores the global warming potential associated with smart metering infrastructure and the use case of decentralized flexibility markets. Results show an annual footprint of 513,679 t CO2-eq. for the intelligent metering infrastructure expected in low-voltage levels by 2030. Digitalization measures required for a household to provide flexibility from decentralized assets cause approx. 27 to 43 kg CO2-eq. per household and year. Given the marginal data volume associated with the use case, the operation and production phases of hardware cause the greatest impact. Accordingly, considerable reduction potentials lie in decarbonizing the electricity mix and ensuring high energy efficiency and longevity of components. As more data-intensive use cases emerge, the method provided in this paper enables further environmental assessments of direct effects and the derivation of recommendations for a sustainable technical design. First qualitative estimations of indirect environmental effects indicate the need for subsequent research in the context of smart grids, including behavioral research and energy system modeling approaches.