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易观梅森:2023年能源使用控制报告-人工智能解决方案的作用(中译版)(19页).pdf

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1、 Perspective Controlling energy use:the role of AI-based solutions March 2023 Caroline Gabriel,Michela Venturelli and Grace Langham Controlling energy use:the role of AI-based solutions|i Analysys Mason Limited 2023 Contents Contents 1.Executive summary 1 2.Rising energy costs and usage are forcing

2、CSPs to focus on efficiencies 2 5G was designed to be energy efficient but its use cases risk a rise in consumption 4 3.CSPs can adopt a variety of strategies when it comes to tackling energy usage 6 4.AI-based solutions can enable CSPs to achieve short-term energy and cost savings 9 Selecting the o

3、ptimal business and delivery model 10 Overview of an ideal AI-based energy saving solution 12 Potential benefits of an AI-based solutions 13 5.Recommendations and conclusion 15 6.About the authors 17 List of figures Figure 1.1:Overview of an ideal AI-based energy-saving solution.2 Figure 2.1:Wholesa

4、le electricity prices,selected countries worldwide,July 2018July 2022.3 Figure 2.2:Maximum power consumption of a base station that supports multiple mobile generations,by component.5 Figure 2.3:Energy increase,generic developed country that is similar in size to the UK,2022.5 Figure 3.1:Energy mana

5、gement solutions for CSPs networks.6 Figure 4.1:Key benefits of SaaS deployments.11 Figure 4.2:Features of an ideal AI-based energy saving solution.12 Figure 4.3:Examples of major CSPs making cost and energy saving using AI-based energy saving solutions.13 Figure 4.4:Maximum percentage of power redu

6、ction achieved using various AI-based energy-saving features.14 This perspective was commissioned by Nokia.Usage is subject to the terms and conditions in our copyright notice.Analysys Mason does not endorse any of the vendors products or services.Controlling energy use:the role of AI-based solution

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本文主要讨论了电信运营商(CSPs)如何通过采用人工智能(AI)解决方案来控制能源使用。主要内容包括: 1. 由于能源成本上升和5G网络部署,CSPs正面临提高能效的压力。5G网络虽然设计上比4G更节能,但由于5G基站密度增加,可能会导致能源消耗上升。 2. CSPs可以通过多种策略来降低能源消耗,包括网络现代化、智能节能特性、资产高效使用和能源替代方式。例如,使用液冷技术可以减少55%的能耗,而AI驱动的网络设计则适用于新网络。 3. AI解决方案可以帮助CSPs在短期内实现能源和成本节约。AI可以扩展传统节能特性的潜力,例如预测流量模式和波动,提供维护和故障管理数据,并建议最可行的能源管理方法。 4. 软件即服务(SaaS)模式可以加快AI解决方案的实施,因为它提供了标准化的服务,减少了定制和安装配置的时间。 5. 文章还提供了一个理想的AI节能解决方案的概述,该方案可以实现整个移动网络的量化节能和成本节约。
5G技术如何影响能源消耗? 电信运营商如何通过AI实现能源节约? 电信运营商如何选择合适的AI能源解决方案?
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