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Impact of Renewable Energy Utilization and Artificial Intelligence in Achieving Sustainable Development Goals

Abstract Many countries around the world are planning to reach 100% renewable energy (RE) use by 2050. In this context and due to the recent sharp increase in RE utilization in the global energy mix along with its progressive impact on the world energy sector, the evaluation and investigation of its effect on achieving sustainable development goals (SDGs) are not covered sufficiently. Here, we present an assessment of the emerging role of RE utilization and artificial intelligence (AI) toward achieving SDGs. A total of 17 SDGs were divided into three groups, namely, environment, society, and economy, as per the three key pillars of sustainable development. The RE has a positive impact toward achieving 75 targets across all SDGs by using an expert elicitation method-based consensus. However, it may negatively affect the accomplishment of the 27 targets. In addition, the AI can help the RE to enable the attainment of 42 out of 169 targets. With the current exponential growth of RE share and AI development together with addressing certain present limitations, this impact may cover additional targets in the future. Nevertheless, the present research foci neglect significant facets. The exponential growth of RE share and rapid evolution of AI need to be accompanied through the requisite regulatory insight and technology regulation to cover additional targets in the future.
- University of Wollongong Australia
- University of Technology Sydney Australia
- UNSW Sydney Australia
- National University of Malaysia Malaysia
- University of Technology Sydney Australia
Energy utilization, Renewable energy, Artificial intelligence, Impact analysis, Sustainable development goals, TK1-9971, Elicited expert, Electrical engineering. Electronics. Nuclear engineering
Energy utilization, Renewable energy, Artificial intelligence, Impact analysis, Sustainable development goals, TK1-9971, Elicited expert, Electrical engineering. Electronics. Nuclear engineering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).98 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
