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市場調查報告書

用於輸配電網絡(T&D)預測管理的人工智能(AI):減少停電,DER集成,勞動力管理,預測資產管理的高級分析

AI for Predictive T&D Network Management: Advanced Analytics for Outage Mitigation, DER Integration, Workforce Management, and Predictive Asset Management

出版商 Guidehouse Insights (formerly Navigant Research) 商品編碼 954111
出版日期 內容資訊 英文 43 Pages; 19 Tables, Charts & Figures
訂單完成後即時交付
價格
用於輸配電網絡(T&D)預測管理的人工智能(AI):減少停電,DER集成,勞動力管理,預測資產管理的高級分析 AI for Predictive T&D Network Management: Advanced Analytics for Outage Mitigation, DER Integration, Workforce Management, and Predictive Asset Management
出版日期: 2020年08月12日內容資訊: 英文 43 Pages; 19 Tables, Charts & Figures
簡介

人工智能技術對輸配電網絡(T&D)的運營產生重大影響。對於許多應用程序而言,來自機器學習和深度學習(ML/DL)解決方案的分析可以幫助降低成本,提高可靠性和服務質量並提高整體網格效率。公用事業公司將越來越依賴基於AI的解決方案來加速DER(分佈式能源)的採用,同時降低成本並保持性能。用於T&D管理的AI技術可幫助公用事業公司最大程度地減少電力中斷,提高移動工作人員的效率,改善負載計劃,管理實時電能質量以及對資產進行預測性維護。

本報告分析了用於傳輸和分配網絡(T&D)的預測管理的人工智能(AI)解決方案的最新情況,人工智能解決方案的特性和優勢,引入它們所需的各種條件和操作技術。 (OT),當前要解決的問題,促進/抑制技術普及的主要因素,支持AI的應用的主要應用領域和普及,未來全球市場增長前景(按地區/用途劃分)等將一起交付。

目錄

第1章執行摘要

  • 簡介
  • 市場預測

第2章市場問題

  • 簡介
  • 基於AI的傳輸和分發(T&D)管理應用程序
    • 電能質量管理
    • 降低存儲電壓
    • 需求響應(DR)
    • DER(分佈式能源)績效管理
    • 狀態估計/切換順序管理
    • 無人機影像監控
    • 氣象分析
    • 資產的預測斷電
    • 非資產故障預測
    • 電源故障管理系統(OMS)
    • 工作計劃
    • 車輛碰撞響應
    • 盜竊
    • 網格優化和網絡規劃
    • 技能規劃
  • 基於AI的解決方案部署模型
    • OT(運營技術)供應商解決方案
    • 專門為電力公司提供數據分析的提供商
    • 通用分析工具
  • 市場促進因素
    • 停止緩解和恢復
    • 勞動力規劃
    • 電力負荷計劃和DER集成
  • 市場障礙
    • 數據收集,數據質量差,來自多個來源的數據集
    • 費用
    • 複雜度
    • 對員工的影響
    • 非傳統採購模式
  • 市場趨勢
    • DER的快速增長
    • 快速滲透ADMS(高級配電管理系統)和DER管理系統
    • 新進入市場的公司和公司合併
    • 公用事業公司創建基於R的解決方案並使用數據湖
  • 輔助技術
    • AMS(資產管理系統)/APM(資產績效管理)系統
    • GIS(地理信息系統)解決方案
    • 負荷預測解決方案
    • C&I DR(商業/工業DR)/DERMS(分佈式能源管理系統)
    • 電網優化系統
    • 天氣預報系統
    • 透過量預測系統

第3章主要行業參與者

  • Hitachi ABB Power Grids
  • C3.ai
  • Clevest Solutions
  • General Electric
  • Grid4C
  • Open Systems International
  • OSIsoft
  • SAS Institute
  • Schneider Electric
  • Siemens

第4章市場預測

  • 簡介
  • 世界市場預測
    • 區域預報
    • 按來源進行的預測
    • 按功能類別進行的預測
  • 結論和建議

第5章縮寫詞和縮寫列表

第6章目錄

第7章圖形和表格列表

第8章分析範圍,信息來源,分析方法,說明

目錄
Product Code: MF-AINM-20

AI technology has profound implications for the operation of electric transmission and distribution (T&D) networks. In many applications, the superior insights derived from machine and deep learning solutions can reduce costs, improve reliability and service quality, and enhance efficiency throughout the grid. Traditional decision-making associated with grid management is not expected to remain adequate in the near future. Utilities will likely become increasingly dependent on AI-based solutions to incorporate distributed energy resources (DER) at an accelerating pace while maintaining acceptable performance metrics and keeping costs low. AI technologies for T&D management can help utilities minimize outages, make mobile workers more effective, improve load planning, manage real-time power quality, perform predictive asset maintenance, and more.

AI analytics solutions may be developed as a module for traditional operational technology (OT) systems such as advanced distribution management systems (ADMSs) or energy management systems (EMSs), or they may come from analytics solutions providers with an emphasis on utility operations. These vendors specialize in analyzing data files from smart meters or sensors connected to network assets and providing insights. Alternatively, some utilities may rely on general purpose business intelligence platforms that include AI capabilities. These platforms may be implemented in collaboration with partners or use internally developed tools as do-it-yourself (DIY) platforms.

This report describes the current landscape for AI technology solutions for T&D network management and presents drivers and barriers to implementation. It details AI-supported applications and explores the global market forecasts for these solutions by region and application.

KEY QUESTIONS ADDRESSED:

  • In what applications can AI technology enhance the operation of a T&D network?
  • What are the options for acquiring AI-based technology for T&D networks?
  • What are the benefits of implementing AI-based technology?
  • What OT systems are involved in leveraging AI-based technology?
  • What challenges are associated with implementing these applications?

WHO NEEDS THIS REPORT:

  • OT providers
  • Service providers
  • Providers of general purpose analytics platforms
  • Utilities
  • Equipment vendors
  • Systems integrators
  • Utility regulators
  • Investor community

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Forecast

2. Market Issues

  • 2.1. Introduction
  • 2.2. AI-Based Applications for T&D Network Management
    • 2.2.1. Power Quality Management
    • 2.2.2. Conservation Voltage Reduction
    • 2.2.3. DR
    • 2.2.4. DER Performance Management
    • 2.2.5. State Estimation/Switch Order Management
    • 2.2.6. Drone Video Monitoring
    • 2.2.7. Weather Analysis
    • 2.2.8. Predictive Asset Outages
    • 2.2.9. Non-Asset Failure Predictions
    • 2.2.10. OMSs
    • 2.2.11. Work Scheduling
    • 2.2.12. Vehicle Crash Response
    • 2.2.13. Theft of Service
    • 2.2.14. Grid Optimization and Network Planning
    • 2.2.15. Skills Planning
  • 2.3. Deployment Models for AI-Based Solutions
    • 2.3.1. OT Vendor Solutions
    • 2.3.2. Utility-Focused Data Analytics Providers
    • 2.3.3. General Purpose Analytics Tools
  • 2.4. Market Drivers
    • 2.4.1. Outage Mitigation and Restoration
    • 2.4.2. Workforce Planning
    • 2.4.3. Load Planning and DER Integration
  • 2.5. Market Barriers
    • 2.5.1. Data Collection, Poor Data Quality, and Multiple Source Datasets
    • 2.5.2. Cost
    • 2.5.3. Complexity
    • 2.5.4. Employee Impact
    • 2.5.5. Non-Traditional Procurement Models
  • 2.6. Market Trends
    • 2.6.1. Burgeoning DER
    • 2.6.2. Increased Penetration of ADMS and DER Management Systems
    • 2.6.3. New Market Entrants and Mergers
    • 2.6.4. Utilities Creating R-Based Solutions and Using Data Lakes
  • 2.7. Supporting Technologies
    • 2.7.1. AMSs/APM Systems
    • 2.7.2. GIS Solutions
    • 2.7.3. Load Forecasting Solutions
    • 2.7.4. C&I DR/DERMSs
    • 2.7.5. Grid Optimization Systems
    • 2.7.6. Weather Forecast Systems
    • 2.7.7. Traffic Forecast Systems

3. Key Industry Players

  • 3.1. Hitachi ABB Power Grids
  • 3.2. C3.ai
  • 3.3. Clevest Solutions
  • 3.4. General Electric
  • 3.5. Grid4C
  • 3.6. Open Systems International
  • 3.7. OSIsoft
  • 3.8. SAS Institute
  • 3.9. Schneider Electric
  • 3.10. Siemens

4. Market Forecasts

  • 4.1. Introduction
  • 4.2. Global Forecasts
    • 4.2.1. Regional Forecasts
      • 4.2.1.1. North America
      • 4.2.1.2. Europe
      • 4.2.1.3. Asia Pacific
      • 4.2.1.4. Latin America
      • 4.2.1.5. Middle East & Africa
    • 4.2.2. Forecast by Procurement Source
    • 4.2.3. Forecast by Functional Category
  • 4.3. Conclusions and Recommendations

5. Acronym and Abbreviation List

6. Table of Contents

7. Table of Charts and Figures

8. Scope of Study, Sources and Methodology, Notes

LIST OF CHARTS AND FIGURES

  • AI-Based Applications and Services Revenue by Region, World Markets: 2020-2029
  • AI-Based Applications and Services Revenue by Procurement Source, World Markets: 2020-2029
  • AI-Based Applications and Services Revenue by Functional Category, World Markets: 2020-2029

LIST OF TABLES

  • AI-Based Applications and Services Revenue by Region, World Markets: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, World Markets: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, North America: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, Europe: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, Asia Pacific: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, Latin America: 2020-2029
  • AI-Based Applications Revenue by Procurement Source, Middle East & Africa: 2020-2029
  • AI-Based Applications Revenue by Functional Category, World Markets: 2020-2029
  • AI-Based Applications Revenue by Functional Category, North America: 2020-2029
  • AI-Based Applications Revenue by Functional Category, Europe: 2020-2029
  • AI-Based Applications Revenue by Functional Category, Asia Pacific: 2020-2029
  • AI-Based Applications Revenue by Functional Category, Latin America: 2020-2029
  • AI-Based Applications Revenue by Functional Category, Middle East & Africa: 2020-2029
  • Overlap of AI-Based Applications for T&D Networks
  • Benefits Associated with AI Applications
  • Dataset Requirements for AI-Based T&D Management Applications