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市场调查报告书
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1994598

2026年全球电网边缘相位辨识分析市场报告

Grid-Edge Phase Identification Analytics Global Market Report 2026
出版日期: | 出版商: The Business Research Company | 英文 250 Pages | 商品交期: 2-10个工作天内

价格
简介目录

近年来，电网边缘相位辨识分析市场发展迅速。预计该市场规模将从2025年的11亿美元成长到2026年的12.8亿美元，复合年增长率（CAGR）为16.1%。成长要素包括智慧电錶的广泛部署、配电网路的早期数位化、电网边缘数据可用性的提高、配电分析工具的早期应用，以及对提高停电管理准确性的日益重视。

预计未来几年电网边缘相位辨识分析市场将快速成长，到2030年市场规模将达到23.4亿美元，复合年增长率（CAGR）为16.4%。预测期内的成长预计将受到以下因素的推动：电网现代化投资的增加、分散式能源的日益普及、对电网自动化检验需求的成长、电力公司对云端分析技术的日益重视，以及对电网韧性和可靠性的日益关注。预测期内的关键趋势包括：基于机器学习的相位检测技术得到更广泛的应用、智慧电錶资料分析的日益普及、即时拓扑检验工具的整合度不断提高、基于云端的电网边缘分析平台得到增强，以及对电网精度的日益关注。

分散式能源（DER）的日益普及预计将在未来几年推动电网边缘相位识别分析市场的成长。分散式能源是指在用电点或附近接入电网的小规模发电和储能係统，例如屋顶太阳能电站、电池储能係统和电动车充电基础设施。分散式能源（DER）的日益普及源自于消费者层面向分散式可再生能源发电的转变。电网边缘相位识别分析透过精确映射分散式能源与配电相位的连接，为分散式能源提供支持，使电力运营商能够优化负载分配、减少相位不平衡，并确保分散式发电在电网边缘的安全接入。例如，根据总部位于阿联酋的政府间机构－国际可再生能源机构（IRENA）预测，到2024年，全球可再生能源发电装置容量将达到585吉瓦，占总发电容量成长的90%以上，并且逐年成长。因此，分散式能源的日益普及正在推动电网边缘相位识别分析市场的成长。

电网边缘相位识别分析市场的主要企业正致力于开发创新解决方案，例如集成先进实时相位映射和运行智能的AI驱动型电网边缘分析平台，以满足日益增长的电网可视性提升、分布式能源（DER）快速併网以及故障和负载管理改进的需求。这项需求源自于电网现代化进程和配电网路日益复杂的现状。基于AI的电网边缘相位识别分析平台利用机器学习和人工智慧技术，持续处理来自智慧电錶、物联网感测器和其他边缘设备的大量电网数据，自动识别相位不平衡和连接模式。这使得电力公司能够优化负载平衡和电网可靠性，而传统的相位识别方法依赖于人工调查和有限的数据采样，无法大规模、即时地实现这一目标。例如，2025年11月，总部位于法国的能源管理和自动化技术公司Schneider Electric推出了其「一体化数位电网平台」。这是一个模组化、人工智慧驱动的软体平台，旨在透过将规划、营运和资产管理与即时分析和预测洞察相结合，帮助电力公司实现电网营运现代化，从而提升整个电网的停电恢復能力、韧性和成本效益。 「一体化数位电网平台」利用人工智慧演算法整合各种电网资料流，估算停电恢復时间，并在无需昂贵的基础设施改造的情况下增强决策能力。与缺乏一致的人工智慧驱动型营运工具的传统电网管理系统相比，这是一个显着的进步。

目录

第一章执行摘要

第二章 市场特征

  • 市场定义和范围
  • 市场区隔
  • 主要产品和服务概述
  • 全球电网边缘相位辨识分析市场：吸引力评分及分析
  • 成长潜力分析、竞争评估、策略适宜性评估、风险状况评估

第三章 市场供应链分析

  • 供应链与生态系概述
  • 清单：主要原料、资源和供应商
  • 主要经销商和通路合作伙伴名单
  • 主要最终用户列表

第四章：全球市场趋势与策略

  • 关键科技与未来趋势
    • 人工智慧（AI）和自主人工智慧
    • 物联网、智慧基础设施、互联生态系统
    • 数位化、云端运算、巨量资料、网路安全
    • 工业4.0和智慧製造
    • 电动交通和交通运输电气化
  • 主要趋势
    • 机器学习相位检测技术的广泛应用
    • 扩大智慧电錶资料分析的应用
    • 即时拓扑检验工具的整合工作正在推进中。
    • 扩展基于云端的电网边缘分析平台
    • 人们越来越关注配电网路的精确性

第五章 终端用户产业市场分析

  • 公共产业
  • 配电网路营运商
  • 智慧电网解决方案供应商
  • 能源服务公司
  • 工业能源用户

第六章 市场：宏观经济情景，包括利率、通货膨胀、地缘政治、贸易战和关税的影响、关税战和贸易保护主义对供应链的影响，以及 COVID-19 疫情对市场的影响。

第七章：全球策略分析架构、目前市场规模、市场对比及成长率分析

  • 全球电网边缘相位识别分析市场：PESTEL 分析（政治、社会、技术、环境、法律因素、驱动因素和限制因素）
  • 全球电网边缘相位辨识分析市场规模、对比及成长率分析
  • 全球电网边缘相位辨识分析市场表现：规模与成长，2020-2025年
  • 全球电网边缘相位辨识分析市场预测：规模与成长，2025-2030年，2035年

第八章：全球市场总规模（TAM）

第九章 市场细分

  • 按组件
  • 软体、硬体和服务
  • 部署模式
  • 本地部署、云端
  • 透过使用
  • 电网优化、停电管理、资产管理、负载预测及其他应用。
  • 按销售管道
  • 直销、经销商、线上销售
  • 最终用户
  • 公共产业、工业、商业、住宅和其他最终用户
  • 按类型细分：软体
  • 相位辨识软体、数据分析软体、视觉化软体、整合软体、报告产生软体
  • 按类型细分：硬体
  • 感测器模组、测量仪器、通讯介面、资料撷取单元、讯号处理单元
  • 按类型细分：服务
  • 咨询服务、实施服务、维修服务、训练服务、技术支援服务

第十章 区域与国别分析

  • 全球电网边缘相位识别分析市场：按地区划分，实际数据和预测数据，2020-2025年、2025-2030年、2035年
  • 全球电网边缘相位识别分析市场：按国家/地区划分，实际数据和预测数据，2020-2025 年、2025-2030 年、2035 年

第十一章 亚太市场

第十二章：中国市场

第十三章：印度市场

第十四章：日本市场

第十五章：澳洲市场

第十六章：印尼市场

第十七章：韩国市场

第十八章 台湾市场

第十九章 东南亚市场

第20章 西欧市场

第21章英国市场

第22章：德国市场

第23章：法国市场

第24章：义大利市场

第25章：西班牙市场

第26章：东欧市场

第27章：俄罗斯市场

第28章 北美市场

第29章：美国市场

第三十章：加拿大市场

第31章：南美市场

第32章：巴西市场

第33章 中东市场

第34章：非洲市场

第三十五章 市场监理与投资环境

第三十六章：竞争格局与公司概况

  • 电网边缘相位辨识分析市场：竞争格局与市场份额，2024 年
  • 电网边缘相位辨识分析市场：公司估值矩阵
  • 电网边缘相位辨识分析市场：公司简介
    • Siemens AG
    • Hitachi Energy Ltd.
    • International Business Machines Corporation（IBM）
    • Cisco Systems, Inc.
    • Oracle Corporation

第37章 其他大型企业和创新企业

  • Schneider Electric SE, Honeywell International Inc., ABB Ltd., Capgemini SE, Eaton Corporation plc, Itron, Inc., Landis+Gyr Group AG, Schweitzer Engineering Laboratories, Inc.（SEL）, S&C Electric Company, Aclara Technologies LLC（a Hubbell Company）, Enel X Srl, Kamstrup A/S, C3.ai, Inc., Uplight, Inc., Trilliant Holdings Inc.

第38章：全球市场竞争基准分析与仪錶板

第39章：预计进入市场的Start-Ups

第四十章 重大併购

第41章 具有高市场潜力的国家、细分市场与策略

  • 2030年电网边缘相位辨识分析市场：提供新机会的国家
  • 2030年电网边缘相位辨识分析市场：提供新机会的细分市场
  • 2030年电网边缘相位辨识分析市场：成长策略
    • 基于市场趋势的策略
    • 竞争对手的策略

第42章附录

简介目录
Product Code: UT6MGPIA01_G26Q1

Grid-edge phase identification analytics is a data-driven software tool that determines the accurate phase connectivity of customers and devices at the distribution grid edge. It examines voltage, current, and time-series data from smart meters, sensors, and distributed energy resources (DERs) to identify phase errors and mismatches. It enhances load balancing, outage management, and DER integration by ensuring correct phase identification throughout the grid.

The main components of grid-edge phase identification analytics include software, hardware, and services. Software encompasses analytics solutions that collect, process, and interpret grid-edge data to identify phase connections, optimize performance, and support decision-making. These solutions are deployed through on-premises and cloud modes. They are applied across grid optimization, outage management, asset management, load forecasting, and other applications, and are distributed via direct sales, distributors, and online channels. The solutions serve multiple end-users, including utilities, industrial, commercial, residential, and other stakeholders.

Tariffs are impacting the grid-edge phase identification analytics market by increasing costs of imported sensors, metering hardware, communication modules, and data acquisition devices used alongside analytics platforms. Utilities in North America and Europe are most affected due to reliance on imported grid-edge hardware, while Asia-Pacific faces cost pressures on large-scale smart grid rollouts. These tariffs are raising deployment costs and slowing some grid modernization programs. However, they are also encouraging software-centric analytics adoption, domestic hardware sourcing, and greater reliance on cloud-based phase identification solutions that reduce physical infrastructure dependency.

The grid-edge phase identification analytics market research report is one of a series of new reports from The Business Research Company that provides grid-edge phase identification analytics market statistics, including grid-edge phase identification analytics industry global market size, regional shares, competitors with a grid-edge phase identification analytics market share, detailed grid-edge phase identification analytics market segments, market trends and opportunities, and any further data you may need to thrive in the grid-edge phase identification analytics industry. This grid-edge phase identification analytics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The grid-edge phase identification analytics market size has grown rapidly in recent years. It will grow from $1.1 billion in 2025 to $1.28 billion in 2026 at a compound annual growth rate (CAGR) of 16.1%. The growth in the historic period can be attributed to expansion of smart meter deployments, early digitization of distribution networks, growing data availability at grid edge, initial adoption of distribution analytics tools, increasing focus on outage management accuracy.

The grid-edge phase identification analytics market size is expected to see rapid growth in the next few years. It will grow to $2.34 billion in 2030 at a compound annual growth rate (CAGR) of 16.4%. The growth in the forecast period can be attributed to increasing investments in distribution grid modernization, rising penetration of distributed energy resources, growing demand for automated grid validation, expansion of utility cloud analytics adoption, increasing focus on grid resilience and reliability. Major trends in the forecast period include increasing adoption of machine learning-based phase detection, rising use of smart meter data analytics, growing integration of real-time topology validation tools, expansion of cloud-based grid-edge analytics platforms, enhanced focus on distribution grid accuracy.

The rising penetration of distributed energy resources (DERs) is expected to drive the growth of the grid-edge phase identification analytics market in the coming years. Distributed energy resources refer to small-scale electricity generation and storage systems connected to the power grid at or near the point of use, including rooftop solar installations, battery energy storage systems, and electric vehicle charging infrastructure. The growing penetration of distributed energy resources (DERs) is driven by the increasing shift toward decentralized renewable energy generation at the consumer level. Grid-edge phase identification analytics supports distributed energy resources (DERs) by precisely mapping DER connections to distribution phases, allowing utilities to optimize load distribution, reduce phase imbalances, and ensure dependable integration of distributed generation at the grid edge. For instance, in March 2025, according to the International Renewable Energy Agency, a UAE-based intergovernmental organization, global renewable power capacity additions reached 585 GW in 2024, representing more than 90% of total power capacity expansion, an increase compared to previous years. Therefore, the growing adoption of distributed energy resources is driving the growth of the grid-edge phase identification analytics market.

Key companies operating in the grid-edge phase identification analytics market are focusing on developing innovative solutions, such as AI-enabled grid-edge analytics platforms that integrate advanced real-time phase mapping and operational intelligence, to meet the rising demand for enhanced grid visibility, rapid distributed energy resource (DER) integration, and improved outage and load management driven by grid modernization initiatives and the increasing complexity of distribution networks. AI-based grid-edge phase identification analytics platforms leverage machine learning and artificial intelligence to continuously process high-volume grid data from smart meters, IoT sensors, and other edge devices, automatically identify phase imbalances and connectivity patterns, and enable utilities to optimize load balancing and grid reliability capabilities that traditional phase identification methods, which relied on manual surveys and limited data sampling, could not deliver at scale or in real time. For example, in November 2025, Schneider Electric, a France-based energy management and automation technology company, launched its One Digital Grid Platform, a modular, AI-enabled software platform designed to help utilities modernize grid operations by combining planning, operations, and asset management with real-time analytics and predictive insights to improve outage restoration, resilience, and cost efficiency across distribution networks. The One Digital Grid Platform leverages AI algorithms to integrate diverse grid data streams, estimate restoration times during outages, and enhance decision-making without requiring costly infrastructure overhauls, making it a significant advancement over traditional grid management systems that lacked cohesive, AI-driven operational tools.

In December 2023, Uplight, a US-based provider of energy management and utility software solutions focused on customer engagement, load flexibility, and decarbonization platforms, acquired AutoGrid from Schneider Electric for an undisclosed amount. With this acquisition, Uplight aimed to broaden its capabilities by incorporating AutoGrid's advanced virtual power plant (VPP) and distributed energy resource management system (DERMS) technologies into a unified platform to better support utilities and energy stakeholders with improved grid flexibility and DER orchestration solutions. AutoGrid is a US-based provider of AI-driven software for managing distributed energy resources (DERs), including VPP, DERMS, and real-time optimization tools supporting renewable energy, electric vehicles, storage, and other grid assets.

Major companies operating in the grid-edge phase identification analytics market are Siemens AG, Hitachi Energy Ltd., International Business Machines Corporation (IBM), Cisco Systems, Inc., Oracle Corporation, Schneider Electric SE, Honeywell International Inc., ABB Ltd., Capgemini SE, Eaton Corporation plc, Itron, Inc., Landis+Gyr Group AG, Schweitzer Engineering Laboratories, Inc. (SEL), S&C Electric Company, Aclara Technologies LLC (a Hubbell Company), Enel X S.r.l., Kamstrup A/S, C3.ai, Inc., Uplight, Inc., Trilliant Holdings Inc.

North America was the largest region in the grid-edge phase identification analytics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the grid-edge phase identification analytics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the grid-edge phase identification analytics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The grid-edge phase identification analytics market consists of revenues earned by entities by providing services such as grid-edge data collection and processing, advanced analytics and machine learning-based phase detection, real-time and periodic network topology validation, data visualization and reporting, and utility workflow automation support. The market value includes the value of related goods sold by the service provider or included within the service offering. The grid-edge phase identification analytics market includes sales of machine learning-based phase detection tools, data processing and visualization modules, application programming interfaces (APIs), cloud-based analytics products and subscriptions, and associated digital platforms. Values in this market are 'factory gate' values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Grid-Edge Phase Identification Analytics Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses grid-edge phase identification analytics market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for grid-edge phase identification analytics ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The grid-edge phase identification analytics market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

  • The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
  • The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
  • The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
  • The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
  • The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
  • The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
  • The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
  • The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
  • Market segmentations break down the market into sub markets.
  • The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
  • Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
  • The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
  • The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

  • Markets Covered:1) By Component: Software; Hardware; Services
  • 2) By Deployment Mode: On-Premises; Cloud
  • 3) By Application: Grid Optimization; Outage Management; Asset Management; Load Forecasting; Other Applications
  • 4) By Sales Channel: Direct Sales; Distributors; Online Sales
  • 5) By End-User: Utilities; Industrial; Commercial; Residential; Other End Users
  • Subsegments:
  • 1) By Software: Phase Identification Software; Data Analytics Software; Visualization Software; Integration Software; Reporting Software
  • 2) By Hardware: Sensor Modules; Metering Devices; Communication Interfaces; Data Acquisition Units; Signal Processing Units
  • 3) By Services: Consulting Services; Deployment Services; Maintenance Services; Training Services; Technical Support Services
  • Companies Mentioned: Siemens AG; Hitachi Energy Ltd.; International Business Machines Corporation (IBM); Cisco Systems; Inc.; Oracle Corporation; Schneider Electric SE; Honeywell International Inc.; ABB Ltd.; Capgemini SE; Eaton Corporation plc; Itron; Inc.; Landis+Gyr Group AG; Schweitzer Engineering Laboratories; Inc. (SEL); S&C Electric Company; Aclara Technologies LLC (a Hubbell Company); Enel X S.r.l.; Kamstrup A/S; C3.ai; Inc.; Uplight; Inc.; Trilliant Holdings Inc.
  • Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
  • Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
  • Time Series: Five years historic and ten years forecast.
  • Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
  • Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
  • Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
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Table of Contents

1. Executive Summary

  • 1.1. Key Market Insights (2020-2035)
  • 1.2. Visual Dashboard: Market Size, Growth Rate, Hotspots
  • 1.3. Major Factors Driving the Market
  • 1.4. Top Three Trends Shaping the Market

2. Grid-Edge Phase Identification Analytics Market Characteristics

  • 2.1. Market Definition & Scope
  • 2.2. Market Segmentations
  • 2.3. Overview of Key Products and Services
  • 2.4. Global Grid-Edge Phase Identification Analytics Market Attractiveness Scoring And Analysis
    • 2.4.1. Overview of Market Attractiveness Framework
    • 2.4.2. Quantitative Scoring Methodology
    • 2.4.3. Factor-Wise Evaluation
  • Growth Potential Analysis, Competitive Dynamics Assessment, Strategic Fit Assessment And Risk Profile Evaluation
    • 2.4.4. Market Attractiveness Scoring and Interpretation
    • 2.4.5. Strategic Implications and Recommendations

3. Grid-Edge Phase Identification Analytics Market Supply Chain Analysis

  • 3.1. Overview of the Supply Chain and Ecosystem
  • 3.2. List Of Key Raw Materials, Resources & Suppliers
  • 3.3. List Of Major Distributors and Channel Partners
  • 3.4. List Of Major End Users

4. Global Grid-Edge Phase Identification Analytics Market Trends And Strategies

  • 4.1. Key Technologies & Future Trends
    • 4.1.1 Artificial Intelligence & Autonomous Intelligence
    • 4.1.2 Internet Of Things (Iot), Smart Infrastructure & Connected Ecosystems
    • 4.1.3 Digitalization, Cloud, Big Data & Cybersecurity
    • 4.1.4 Industry 4.0 & Intelligent Manufacturing
    • 4.1.5 Electric Mobility & Transportation Electrification
  • 4.2. Major Trends
    • 4.2.1 Increasing Adoption Of Machine Learning-Based Phase Detection
    • 4.2.2 Rising Use Of Smart Meter Data Analytics
    • 4.2.3 Growing Integration Of Real-Time Topology Validation Tools
    • 4.2.4 Expansion Of Cloud-Based Grid-Edge Analytics Platforms
    • 4.2.5 Enhanced Focus On Distribution Grid Accuracy

5. Grid-Edge Phase Identification Analytics Market Analysis Of End Use Industries

  • 5.1 Utilities
  • 5.2 Distribution Network Operators
  • 5.3 Smart Grid Solution Providers
  • 5.4 Energy Service Companies
  • 5.5 Industrial Energy Users

6. Grid-Edge Phase Identification Analytics Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, Supply Chain Impact from Tariff War & Trade Protectionism, And Covid And Recovery On The Market

7. Global Grid-Edge Phase Identification Analytics Strategic Analysis Framework, Current Market Size, Market Comparisons And Growth Rate Analysis

  • 7.1. Global Grid-Edge Phase Identification Analytics PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
  • 7.2. Global Grid-Edge Phase Identification Analytics Market Size, Comparisons And Growth Rate Analysis
  • 7.3. Global Grid-Edge Phase Identification Analytics Historic Market Size and Growth, 2020 - 2025, Value ($ Billion)
  • 7.4. Global Grid-Edge Phase Identification Analytics Forecast Market Size and Growth, 2025 - 2030, 2035F, Value ($ Billion)

8. Global Grid-Edge Phase Identification Analytics Total Addressable Market (TAM) Analysis for the Market

  • 8.1. Definition and Scope of Total Addressable Market (TAM)
  • 8.2. Methodology and Assumptions
  • 8.3. Global Total Addressable Market (TAM) Estimation
  • 8.4. TAM vs. Current Market Size Analysis
  • 8.5. Strategic Insights and Growth Opportunities from TAM Analysis

9. Grid-Edge Phase Identification Analytics Market Segmentation

  • 9.1. Global Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Software, Hardware, Services
  • 9.2. Global Grid-Edge Phase Identification Analytics Market, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • On-Premises, Cloud
  • 9.3. Global Grid-Edge Phase Identification Analytics Market, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Grid Optimization, Outage Management, Asset Management, Load Forecasting, Other Applications
  • 9.4. Global Grid-Edge Phase Identification Analytics Market, Segmentation By Sales Channel, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Direct Sales, Distributors, Online Sales
  • 9.5. Global Grid-Edge Phase Identification Analytics Market, Segmentation By End-User, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Utilities, Industrial, Commercial, Residential, Other End Users
  • 9.6. Global Grid-Edge Phase Identification Analytics Market, Sub-Segmentation Of Software, By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Phase Identification Software, Data Analytics Software, Visualization Software, Integration Software, Reporting Software
  • 9.7. Global Grid-Edge Phase Identification Analytics Market, Sub-Segmentation Of Hardware, By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Sensor Modules, Metering Devices, Communication Interfaces, Data Acquisition Units, Signal Processing Units
  • 9.8. Global Grid-Edge Phase Identification Analytics Market, Sub-Segmentation Of Services, By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Consulting Services, Deployment Services, Maintenance Services, Training Services, Technical Support Services

10. Grid-Edge Phase Identification Analytics Market Regional And Country Analysis

  • 10.1. Global Grid-Edge Phase Identification Analytics Market, Split By Region, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • 10.2. Global Grid-Edge Phase Identification Analytics Market, Split By Country, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

11. Asia-Pacific Grid-Edge Phase Identification Analytics Market

  • 11.1. Asia-Pacific Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 11.2. Asia-Pacific Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

12. China Grid-Edge Phase Identification Analytics Market

  • 12.1. China Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 12.2. China Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

13. India Grid-Edge Phase Identification Analytics Market

  • 13.1. India Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

14. Japan Grid-Edge Phase Identification Analytics Market

  • 14.1. Japan Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 14.2. Japan Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

15. Australia Grid-Edge Phase Identification Analytics Market

  • 15.1. Australia Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

16. Indonesia Grid-Edge Phase Identification Analytics Market

  • 16.1. Indonesia Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

17. South Korea Grid-Edge Phase Identification Analytics Market

  • 17.1. South Korea Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 17.2. South Korea Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

18. Taiwan Grid-Edge Phase Identification Analytics Market

  • 18.1. Taiwan Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 18.2. Taiwan Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

19. South East Asia Grid-Edge Phase Identification Analytics Market

  • 19.1. South East Asia Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 19.2. South East Asia Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

20. Western Europe Grid-Edge Phase Identification Analytics Market

  • 20.1. Western Europe Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 20.2. Western Europe Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

21. UK Grid-Edge Phase Identification Analytics Market

  • 21.1. UK Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

22. Germany Grid-Edge Phase Identification Analytics Market

  • 22.1. Germany Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

23. France Grid-Edge Phase Identification Analytics Market

  • 23.1. France Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

24. Italy Grid-Edge Phase Identification Analytics Market

  • 24.1. Italy Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

25. Spain Grid-Edge Phase Identification Analytics Market

  • 25.1. Spain Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

26. Eastern Europe Grid-Edge Phase Identification Analytics Market

  • 26.1. Eastern Europe Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 26.2. Eastern Europe Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

27. Russia Grid-Edge Phase Identification Analytics Market

  • 27.1. Russia Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

28. North America Grid-Edge Phase Identification Analytics Market

  • 28.1. North America Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 28.2. North America Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

29. USA Grid-Edge Phase Identification Analytics Market

  • 29.1. USA Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 29.2. USA Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

30. Canada Grid-Edge Phase Identification Analytics Market

  • 30.1. Canada Grid-Edge Phase Identification Analytics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 30.2. Canada Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

31. South America Grid-Edge Phase Identification Analytics Market

  • 31.1. South America Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 31.2. South America Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

32. Brazil Grid-Edge Phase Identification Analytics Market

  • 32.1. Brazil Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

33. Middle East Grid-Edge Phase Identification Analytics Market

  • 33.1. Middle East Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 33.2. Middle East Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

34. Africa Grid-Edge Phase Identification Analytics Market

  • 34.1. Africa Grid-Edge Phase Identification Analytics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 34.2. Africa Grid-Edge Phase Identification Analytics Market, Segmentation By Component, Segmentation By Deployment Mode, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

35. Grid-Edge Phase Identification Analytics Market Regulatory and Investment Landscape

36. Grid-Edge Phase Identification Analytics Market Competitive Landscape And Company Profiles

  • 36.1. Grid-Edge Phase Identification Analytics Market Competitive Landscape And Market Share 2024
    • 36.1.1. Top 10 Companies (Ranked by revenue/share)
  • 36.2. Grid-Edge Phase Identification Analytics Market - Company Scoring Matrix
    • 36.2.1. Market Revenues
    • 36.2.2. Product Innovation Score
    • 36.2.3. Brand Recognition
  • 36.3. Grid-Edge Phase Identification Analytics Market Company Profiles
    • 36.3.1. Siemens AG Overview, Products and Services, Strategy and Financial Analysis
    • 36.3.2. Hitachi Energy Ltd. Overview, Products and Services, Strategy and Financial Analysis
    • 36.3.3. International Business Machines Corporation (IBM) Overview, Products and Services, Strategy and Financial Analysis
    • 36.3.4. Cisco Systems, Inc. Overview, Products and Services, Strategy and Financial Analysis
    • 36.3.5. Oracle Corporation Overview, Products and Services, Strategy and Financial Analysis

37. Grid-Edge Phase Identification Analytics Market Other Major And Innovative Companies

  • Schneider Electric SE, Honeywell International Inc., ABB Ltd., Capgemini SE, Eaton Corporation plc, Itron, Inc., Landis+Gyr Group AG, Schweitzer Engineering Laboratories, Inc. (SEL), S&C Electric Company, Aclara Technologies LLC (a Hubbell Company), Enel X S.r.l., Kamstrup A/S, C3.ai, Inc., Uplight, Inc., Trilliant Holdings Inc.

38. Global Grid-Edge Phase Identification Analytics Market Competitive Benchmarking And Dashboard

39. Upcoming Startups in the Market

40. Key Mergers And Acquisitions In The Grid-Edge Phase Identification Analytics Market

41. Grid-Edge Phase Identification Analytics Market High Potential Countries, Segments and Strategies

  • 41.1 Grid-Edge Phase Identification Analytics Market In 2030 - Countries Offering Most New Opportunities
  • 41.2 Grid-Edge Phase Identification Analytics Market In 2030 - Segments Offering Most New Opportunities
  • 41.3 Grid-Edge Phase Identification Analytics Market In 2030 - Growth Strategies
    • 41.3.1 Market Trend Based Strategies
    • 41.3.2 Competitor Strategies

42. Appendix

  • 42.1. Abbreviations
  • 42.2. Currencies
  • 42.3. Historic And Forecast Inflation Rates
  • 42.4. Research Inquiries
  • 42.5. The Business Research Company
  • 42.6. Copyright And Disclaimer