仅事实
人工智能在能源消耗与效率中的双重角色
Summary
尽管人工智能显著增加了全球能源消耗，但它也提供了解决方案，以提升各行业的能源效率。
人工智能（AI）正在推动全球能源消耗显著上升，数据中心作为AI运营的核心，预计在2024年将占全球电力使用的约1.5%。这一数字预计到2030年将翻倍以上，达到约945太瓦时，约占全球电力消耗的近3%。
尽管存在这些担忧，AI正被用来提升能源效率并减少污染。在建筑管理方面，AI系统能够基于实时数据自主调整照明、通风、供暖和制冷，有望降低10%至30%的能源消耗。
在交通领域，AI优化电动汽车的充电时间表，将用电转移到需求和电价较低的非高峰时段。这不仅降低了成本，还减轻了电网的负担。
AI的应用还扩展到石油和天然气行业，通过优化运营和减少燃烧及排放，帮助减少甲烷排放——一种强效温室气体。
此外，AI通过分析地下数据，协助识别可行的地热能源地点，促进可再生能源的发展。
在城市环境中，AI驱动的交通管理系统调整红绿灯时序以减少拥堵，从而降低车辆排放，改善空气质量。
虽然AI的能源需求巨大，但其提升效率和支持可持续实践的能力，为未来能源管理呈现出复杂而充满希望的前景。
来源
AP News事实核查
使用外部来源和数据库核实文章的事实。
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Data centers accounted for approximately 1.5% of worldwide electricity use in 2024.
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This figure is projected to more than double by 2030, reaching around 945 terawatt-hours, or nearly 3% of global electricity consumption.
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AI systems in building management can autonomously adjust lighting, ventilation, heating, and cooling based on real-time data, potentially decreasing energy consumption by 10% to 30%.
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In the transportation sector, AI optimizes electric vehicle charging schedules, shifting energy use to off-peak times when demand and rates are lower.
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AI applications extend to the oil and gas industry, where they help minimize methane emissions—a potent greenhouse gas—by optimizing operations and reducing the need for flaring and venting.
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AI aids in identifying viable geothermal energy sites by analyzing subsurface data, thereby promoting the development of renewable energy sources.
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In urban settings, AI-driven traffic management systems adjust traffic light timings to reduce congestion, leading to lower vehicle emissions and improved air quality.
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