{"title":"人工智能(AI)与环境生命周期评估、光伏、智能电网和小岛屿经济的关系","authors":"Chr. Lamnatou , C. Cristofari , D. Chemisana","doi":"10.1016/j.seta.2024.104005","DOIUrl":null,"url":null,"abstract":"<div><div>Considering the gaps in the literature on Artificial Intelligence (AI) modelling, this article aims to: i) present models that combine AI and environmental Life Cycle Assessment (LCA), ii) analyse the role of AI in photovoltaics, smart grids and small-island economies. The methodology used is based upon selection of publications and analysis. Regarding LCA/AI models, the results show that AI can anticipate environmental impacts but model performance depends on the amount of data available. LCA/AI models can be used for eco-design and decision-making. However, it is necessary to develop standardised methodologies to evaluate AI environmental impacts. Regarding AI and photovoltaics, AI provides remarkably interesting applications: design, optimisation and prediction of parameters related to different kinds of photovoltaics (concentrating, building-integrated, etc.). As for AI and smart grids, AI offers advantages such as integration of intermittent renewable energy sources and decentralised-grid management. With respect to AI and small-island economies, factors such as effective energy storage, energy plans and estimation of the degree of susceptibility to disasters are important. Generally speaking, and considering the above-mentioned issues, it can be argued that AI poses multiple challenges: machine-learning models on a large-scale basis; the internet of things; options to reduce negative environmental impacts and so on.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"71 ","pages":"Article 104005"},"PeriodicalIF":7.1000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence (AI) in relation to environmental life-cycle assessment, photovoltaics, smart grids and small-island economies\",\"authors\":\"Chr. Lamnatou , C. Cristofari , D. Chemisana\",\"doi\":\"10.1016/j.seta.2024.104005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Considering the gaps in the literature on Artificial Intelligence (AI) modelling, this article aims to: i) present models that combine AI and environmental Life Cycle Assessment (LCA), ii) analyse the role of AI in photovoltaics, smart grids and small-island economies. The methodology used is based upon selection of publications and analysis. Regarding LCA/AI models, the results show that AI can anticipate environmental impacts but model performance depends on the amount of data available. LCA/AI models can be used for eco-design and decision-making. However, it is necessary to develop standardised methodologies to evaluate AI environmental impacts. Regarding AI and photovoltaics, AI provides remarkably interesting applications: design, optimisation and prediction of parameters related to different kinds of photovoltaics (concentrating, building-integrated, etc.). As for AI and smart grids, AI offers advantages such as integration of intermittent renewable energy sources and decentralised-grid management. With respect to AI and small-island economies, factors such as effective energy storage, energy plans and estimation of the degree of susceptibility to disasters are important. Generally speaking, and considering the above-mentioned issues, it can be argued that AI poses multiple challenges: machine-learning models on a large-scale basis; the internet of things; options to reduce negative environmental impacts and so on.</div></div>\",\"PeriodicalId\":56019,\"journal\":{\"name\":\"Sustainable Energy Technologies and Assessments\",\"volume\":\"71 \",\"pages\":\"Article 104005\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Energy Technologies and Assessments\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213138824004016\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Technologies and Assessments","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213138824004016","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Artificial Intelligence (AI) in relation to environmental life-cycle assessment, photovoltaics, smart grids and small-island economies
Considering the gaps in the literature on Artificial Intelligence (AI) modelling, this article aims to: i) present models that combine AI and environmental Life Cycle Assessment (LCA), ii) analyse the role of AI in photovoltaics, smart grids and small-island economies. The methodology used is based upon selection of publications and analysis. Regarding LCA/AI models, the results show that AI can anticipate environmental impacts but model performance depends on the amount of data available. LCA/AI models can be used for eco-design and decision-making. However, it is necessary to develop standardised methodologies to evaluate AI environmental impacts. Regarding AI and photovoltaics, AI provides remarkably interesting applications: design, optimisation and prediction of parameters related to different kinds of photovoltaics (concentrating, building-integrated, etc.). As for AI and smart grids, AI offers advantages such as integration of intermittent renewable energy sources and decentralised-grid management. With respect to AI and small-island economies, factors such as effective energy storage, energy plans and estimation of the degree of susceptibility to disasters are important. Generally speaking, and considering the above-mentioned issues, it can be argued that AI poses multiple challenges: machine-learning models on a large-scale basis; the internet of things; options to reduce negative environmental impacts and so on.
期刊介绍:
Encouraging a transition to a sustainable energy future is imperative for our world. Technologies that enable this shift in various sectors like transportation, heating, and power systems are of utmost importance. Sustainable Energy Technologies and Assessments welcomes papers focusing on a range of aspects and levels of technological advancements in energy generation and utilization. The aim is to reduce the negative environmental impact associated with energy production and consumption, spanning from laboratory experiments to real-world applications in the commercial sector.