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市場調查報告書
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1574125

能源和電力領域的人工智慧 (AI) 市場：2024-2029 年預測

Artificial Intelligence (AI) in Energy and Power Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 152 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

能源和電力領域的人工智慧 (AI) 市場預計將從 2024 年的 59.23 億美元增至 2029 年的 177.45 億美元，預測期內複合年成長率為 24.54%。

人工智慧 (AI) 正在成為能源和電力市場中越來越重要的工具。人工智慧可以自動化和改善能源相關流程，並提供更好的能源管理，以更低的成本實現更有效率的營運。此外，您還可以減少對環境的負面影響並全面啟動更好的改進。在能源領域，人工智慧主要用於需求預測。

此外，透過分析消費行為、天氣模式和其他變數的豐富資料，人工智慧系統可以更好地了解能源的使用方式，從而使公用事業公司能夠更好地利用其資源。人工智慧將用於創建更具成本效益的能源生產和供應系統。例如，機器學習演算法可以分析來自太陽能和風力發電系統的資料，以檢測模式並預測發電量。

此外，人工智慧驅動的系統可以監控和分析建築物內的能源消耗過程，識別能源浪費或使用效率低下的地方，並確定如何以節能解決方案取代能源。這不僅有可能減少溫室氣體排放，還可以降低業主和租戶的資本成本。然而，資料不足或過時可能會創建不正確的人工智慧模型，導致營運不良，從而造成財務損失和安全風險。因此，需要有效解決此制度問題，才能使市場不受阻礙地發展。

能源和電力市場中的人工智慧 (AI) 促進因素：

  • 智慧電網的廣泛採用預計將推動能源和電力領域人工智慧 (AI) 的成長。

智慧電網是其中一個突出的應用，人工智慧正在能源和電力領域中得到應用。智慧電網提供電力，同時使用先進的感測器、通訊技術和自動化系統，以確保這些服務的高效提供。透過在決策制定時即時比較大量資料，公用事業公司可以利用人工智慧做出更好的決策，從而使執行更順暢並提高效能。

例如，2024年1月，西班牙Iberdrola Espana與BCAM合作進行了一個針對電網最佳化的AI創新資料計劃。該舉措是全球智慧電網創新中心的一部分，將在配電能力和效率方面提高電網服務的可及性和質量，特別是在可再生能源整合和經濟電氣化方面。

能源和電力人工智慧（AI）市場的地理前景：

  • 北美地區預計將佔據主要市場佔有率。

由於美國等國家可再生能源部署和智慧電網技術的顯著增加，預計北美將在人工智慧能源和電力市場中呈現最快的成長速度。美國政府增加使用可再生能源正在推動電力和能源產業人工智慧應用的增加。

美國能源資訊署報告稱，到 2022 年，可再生能源發電將占美國電力供應總量的約 13%。此外，到2022年，美國可再生能源消耗總量的約61%將來自電力部門，去年可再生能源占美國發電量的五分之一以上，即21%。此外，該地區擁有一流的公共產業和人工智慧技術供應商，垂直專注於智慧電網和綠色能源技術，從而推動未來幾年該地區市場的成長。

為什麼要購買這份報告？

  • 洞察分析：深入洞察關鍵和新興地區的市場，重點關注客戶細分、政府政策、社會經濟因素、消費者偏好、產業和其他子區隔。
  • 競爭格局：了解全球主要企業採取的策略舉措，並了解採用正確策略的市場滲透潛力。
  • 市場促進因素和未來趨勢：檢視動態因素和關鍵市場趨勢，並探討它們將如何影響未來的市場發展。
  • 可行的建議：利用洞察力做出策略決策，在動態環境中發現新的業務流和收益。
  • 迎合廣泛的受眾：對新興企業、研究機構、顧問、中小企業和大型企業有用且具有成本效益。

公司使用我們的報告的目的是什麼？

產業與市場考量、機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開拓、競爭影響

調查範圍

  • 過去的資料/預測，2022-2029
  • 成長機會、挑戰、供應鏈前景、法規結構、顧客行為、趨勢分析
  • 競爭定位、策略和市場佔有率分析
  • 區域收益成長和預測分析，包括細分市場和國家
  • 公司概況（策略、產品、財務資訊、主要發展等）

目錄

第1章簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關人員的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章 能源與電力領域的人工智慧市場：依技術分類

  • 介紹
  • 機器學習
  • 自然語言處理
  • 電腦視覺
  • 其他

第6章 能源與電力領域的人工智慧市場：依應用分類

  • 介紹
  • 需求預測
  • 最佳化能源生產和發行
  • 能源管理
  • 智慧電網
  • 智慧電錶
  • 其他

第7章 能源與電力領域的人工智慧市場：依最終用戶分類

  • 介紹
  • 商業/工業
  • 住宅

第8章能源與電力領域的人工智慧市場：按地區分類

  • 介紹
  • 北美洲
    • 依技術
    • 按用途
    • 最終用戶
    • 按國家/地區
  • 南美洲
    • 依技術
    • 按用途
    • 最終用戶
    • 按國家/地區
  • 歐洲
    • 依技術
    • 按用途
    • 最終用戶
    • 按國家/地區
  • 中東/非洲
    • 依技術
    • 按用途
    • 最終用戶
    • 按國家/地區
  • 亞太地區
    • 依技術
    • 按用途
    • 最終用戶
    • 按國家/地區

第9章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第10章 公司簡介

  • General Electric
  • Siemens Energy
  • Schneider Electric
  • ABB Ltd.
  • Honeywell International Inc.
  • C3.ai Inc.
  • Eaton Corporation Plc
  • IBM Corporation
簡介目錄
Product Code: KSI061614652

Artificial Intelligence (AI) in the energy and power market is projected to witness a CAGR of 24.54% during the forecast period to reach US$17.745 billion by 2029, up from US$5.923 billion in 2024.

Artificial intelligence (AI) has been increasingly becoming a significant tool in the energy and power markets. It can automate and improve energy-related processes and provide more efficient operation at lower cost by providing better energy management. Additionally, it reduces adverse environmental impacts and fully initiates better enhancements. In energy sectors, AI is used mainly for demand forecasting.

Moreover, by analyzing the wealth of data available on consumer behavior, weather patterns, and other variables, AI systems can give a much more accurate idea of how energy is used, allowing utility companies to manage their resources better. AI is used to create more cost-effective energy production and distribution systems. For example, machine learning algorithms can analyze solar or wind energy systems data to detect patterns and predict how much power will be generated.

Additionally, AI-powered systems can monitor and analyze energy-consuming processes in buildings, identify where it is being wasted or used inefficiently, and how they can be replaced with an energy-saving solution. This has the potential to reduce greenhouse gas emissions as well as achieve capital cost savings for building owners and tenants. However, insufficient or outdated data could result in wrong AI models, leading to poor operationalization, financial loss, and safety danger. Hence, the system must be effectively dealt with for the market to grow without any hindrances.

ARTIFICIAL INTELLIGENCE (AI) IN ENERGY AND POWER MARKET DRIVER:

  • Increasing smart grid deployment is expected to drive AI in the energy and power market growth.

One of the prominent applications is smart grids, where AI is employed in the energy and power sectors. Smart grids use advanced sensors, communication technologies, and automation systems while providing electricity to ensure an efficient delivery of these services. Comparing large volumes of data in real-time as they come to a decision helps the utility make decisions better with AI, which is applied for smoother execution and performance improvement.

For instance, in January 2024, Spain's Iberdrola Espana is teaming with BCAM on the AI Innovation Data Space project targeting grid optimization. The initiative is part of the Global Smart Grids Innovation Hub, an interoperable workspace aimed at enhancing the access and quality of grid services in terms of distribution capacity and efficiency, especially for renewable integration and economic electrification.

Artificial Intelligence (AI) in Energy and Power Market Geographical Outlook:

  • The North American region is expected to hold a substantial market share.

North America is expected to experience one of the fastest growth rates in the AI energy and power market due to high incremental changes in renewable energy adoption and smart grid technologies dominantly across countries such as the United States. The growth in the use of renewable energy sources by the United States government has facilitated an increase in AI applications across its power and energy industry.

The U.S. Energy Information Administration reported that renewable energy generated approximately 13 percent of the entire U.S. electricity supply in 2022. Additionally, about 61% of all U.S. renewable energy consumption in 2022 was in the electric power sector, and renewables accounted for more than a fifth, i.e., 21% of U.S. electricity generation last year. Additionally, this region boasts some of the top utilities and AI technology providers, with a vertical focus on smart grid and green energy technologies, leading to regional market growth in the years ahead.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

Market Segmentation:

The Artificial Intelligence (AI) in Energy and Power Market is segmented and analyzed as below:

By Technology

  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Others

By Application

  • Demand Forecasting
  • Energy Production and Distribution Optimization
  • Energy Management
  • Smart Grids
  • Smart Meter
  • Others

By End-User

  • Commercial and Industrial
  • Residential

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • Israel
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Vietnam
  • Indonesia
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key benefits for the stakeholders

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Process

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. AI IN ENERGY AND POWER MARKET BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. Machine Learning
  • 5.3. Natural Language Processing
  • 5.4. Computer Vision
  • 5.5. Others

6. AI IN ENERGY AND POWER MARKET BY APPLICATION

  • 6.1. Introduction
  • 6.2. Demand Forecasting
  • 6.3. Energy Production and Distribution Optimization
  • 6.4. Energy Management
  • 6.5. Smart Grids
  • 6.6. Smart Meter
  • 6.7. Others

7. AI IN ENERGY AND POWER MARKET BY END-USER

  • 7.1. Introduction
  • 7.2. Commercial and Industrial
  • 7.3. Residential

8. AI IN ENERGY AND POWER MARKET BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Technology
    • 8.2.2. By Application
    • 8.2.3. End-User
    • 8.2.4. By Country
      • 8.2.4.1. USA
      • 8.2.4.2. Canada
      • 8.2.4.3. Mexico
  • 8.3. South America
    • 8.3.1. By Technology
    • 8.3.2. By Application
    • 8.3.3. End-User
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
      • 8.3.4.2. Argentina
      • 8.3.4.3. Others
  • 8.4. Europe
    • 8.4.1. By Technology
    • 8.4.2. By Application
    • 8.4.3. End-User
    • 8.4.4. By Country
      • 8.4.4.1. UK
      • 8.4.4.2. Germany
      • 8.4.4.3. France
      • 8.4.4.4. Spain
      • 8.4.4.5. Others
  • 8.5. Middle East and Africa
    • 8.5.1. By Technology
    • 8.5.2. By Application
    • 8.5.3. End-User
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
      • 8.5.4.2. Israel
      • 8.5.4.3. UAE
      • 8.5.4.4. Others
  • 8.6. Asia Pacific
    • 8.6.1. By Technology
    • 8.6.2. By Application
    • 8.6.3. End-User
    • 8.6.4. By Country
      • 8.6.4.1. China
      • 8.6.4.2. Japan
      • 8.6.4.3. India
      • 8.6.4.4. South Korea
      • 8.6.4.5. Australia
      • 8.6.4.6. Vietnam
      • 8.6.4.7. Indonesia
      • 8.6.4.8. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. General Electric
  • 10.2. Siemens Energy
  • 10.3. Schneider Electric
  • 10.4. ABB Ltd.
  • 10.5. Honeywell International Inc.
  • 10.6. C3.ai Inc.
  • 10.7. Eaton Corporation Plc
  • 10.8. IBM Corporation