Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy

Qin, Meng; Hu, Wei; Qi, Xinzhou; Chang, Tsangyao

doi:10.1016/j.eneco.2024.107403

Energy Economics

2024

DOI: 10.1016/j.eneco.2024.107403

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Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy

Meng Qin,

Wei Hu,

Xinzhou Qi

et al.

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Cited by 24 publications

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The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

Al‐Raeei

2024

Sustainable Development

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Future tools for supporting collaborations between technology and sustainable development include artificial intelligence (AI) applications in sustainable Urbanization roles. This article highlights the various applications of AI in advancing sustainable urbanization. From urban planning to disaster management, AI technology is revolutionizing the way cities are designed and managed. By leveraging data analytics, machine learning, and predictive modeling, AI is helping city officials make informed decisions, optimize resource usage, and improve quality of life for urban residents. Despite the immense potential of AI in sustainable urban development, there are still challenges and limitations to overcome. We show some of the most significant problems related to these issues. These include issues related to data privacy, algorithm bias, and ethical considerations. Continued research and innovation are needed to address these challenges and ensure that AI technology is used responsibly and effectively in shaping sustainable cities. As a result, AI has the power to transform urban environments and create more sustainable, resilient communities. By harnessing the capabilities of AI, cities can become more efficient, environmentally‐friendly, and prepared for the challenges of the future. It is essential for policymakers, urban planners, and technology developers to work together to harness the full potential of AI in sustainable urbanization and create a better future for all. Proactively addressing these challenges can unlock the full potential of AI in combating sustainable cities and building a sustainable future for all.

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The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

Al‐Raeei

2024

Sustainable Development

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Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review

Manikandan,

Kaviya,

Shreeharan

et al. 2024

Sustainable Development

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Artificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on the efforts of reducing carbon emissions more efficiently and effectively, this study tries to focus on AI integration with carbon capture technology. The urgency of tackling climate change means we need more advanced carbon capture, and this is an area where AI can make a huge impact in how these technologies are operated and managed. It will minimize manufacturing emissions and improve both resource efficiency as well as our planet's environmental footprint by turning waste into something of value again. Artificial intelligence could be leveraged to analyze huge data sets from carbon capture plants, searching for optimal system settings and more efficient ways of identifying patterns in the available information at a larger scale than currently possible. In addition, AI incorporated sensors and monitoring mechanisms in the supply chain can identify any operational failure at reception itself allowing for timely action to protect those areas. Artificial intelligence also helps generative design for carbon capture materials, which allows researchers to explore new types of carbon‐absorbing material, including metal–organic frameworks and polymeric materials that are important in industrial CO2, such as moisture. In addition, it increases the accuracy of reservoir simulations and controls CO2 injection systems for storage or enhanced oil recovery. Through applying AI algorithms on reservoir geology, production performance and real‐time data this study would like to facilitate the optimization of injection processes as well as minimize CO2 emissions while assuring a maximum efficiency. Artificial intelligence integrates with renewable‐based carbon capture efforts that can be employed by AI‐driven smart grid systems to improve carbon capture methods.

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Effect of sulfate freeze-thaw on the stress-strain relationship of recycled coarse aggregate self-compacting concrete: Experimental and machine learning algorithms

Zheng,

Liu,

et al. 2024

Construction and Building Materials

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy

Cited by 24 publications

References 60 publications

The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

Artificial intelligence‐driven sustainability: Enhancing carbon capture for sustainable development goals– A review

Effect of sulfate freeze-thaw on the stress-strain relationship of recycled coarse aggregate self-compacting concrete: Experimental and machine learning algorithms

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