Solar energy paper index
Artificial Intelligence and Environmental Challenges
One-line summary
A solar energy research paper on Artificial Intelligence and Environmental Challenges.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
This volume examines where artificial intelligence can provide genuine insight into environmental problems, and at what cost. Across eight chapters, contributors apply machine learning, deep learning, econometric modelling, and computational simulation to a range of pressing challenges: forecasting wind and solar energy output, deploying efficient AI on resource-constrained edge devices, quantifying risk in sustainable finance, detecting faults in photovoltaic installations, analysing air quality and CO₂ emissions data, simulating nanoplastic interactions with biological systems, and modelling urban heat transfer. A recurring theme is the critical importance of data quality — sparse, biased, or poorly curated datasets remain a fundamental obstacle to trustworthy modelling. The volume equally emphasises interpretability, recognising that environmental decision-making is ultimately a human and political process. Taken together, the chapters offer an honest, domain-grounded assessment of the current capabilities and limitations of AI as a tool for addressing environmental challenges.
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