▶ 調査レポート

スマートグリッドデータ分析の世界市場2020-2025

• 英文タイトル:Smart Grid Data Analytics Market - Growth, Trends, and Forecast (2020-2025)

Mordor Intelligenceが調査・発行した産業分析レポートです。スマートグリッドデータ分析の世界市場2020-2025 / Smart Grid Data Analytics Market - Growth, Trends, and Forecast (2020-2025) / D0MOR-NV183資料のイメージです。• レポートコード:D0MOR-NV183
• 出版社/出版日:Mordor Intelligence / 2020年8月
• レポート形態:英文、PDF、158ページ
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レポート概要
本調査レポートでは、スマートグリッドデータ分析の世界市場について調査し、イントロダクション、調査手法、エグゼクティブサマリー、市場動向、展開方式別(クラウドベース、オンプレミス)分析、ソリューション別(送配電(T&D)ネットワーク、メータリング、顧客分析)分析、用途別(高度型メータリングインフラストラクチャ分析、デマンドレスポンス分析、グリッド最適化分析)分析、エンドユース産業別(民間、公共)分析、地域別分析、競争状況、投資分析、市場機会・将来動向などを整理しました。
・イントロダクション
・調査手法
・エグゼクティブサマリー
・市場動向
・スマートグリッドデータ分析の世界市場規模:展開方式別(クラウドベース、オンプレミス)
・スマートグリッドデータ分析の世界市場規模:ソリューション別(送配電(T&D)ネットワーク、メータリング、顧客分析)
・スマートグリッドデータ分析の世界市場規模:用途別(高度型メータリングインフラストラクチャ分析、デマンドレスポンス分析、グリッド最適化分析)
・スマートグリッドデータ分析の世界市場規模:エンドユース産業別(民間、公共)
・スマートグリッドデータ分析の世界市場規模:地域別
・競争状況
・投資分析
・市場機会・将来動向

The smart grid data analytics market was valued at USD 1451.6 million in 2019, and it is expected to reach USD 2943.9 million by 2025, registering a CAGR of 12.76%, during the period of 20202025. With the advent of advanced technology, such as IoT, players have been focusing on integrating smart grid solutions in a wider aspect. As data generation has been continuously experiencing an upward trend, power utility companies have been combining Big Data with billions of more rows of additional IoT and smart sensor data. The data gathered from smart meters can provide a better understanding of customer behavior, and hence, facilitate customer segmentation.

Growing investment in smart grid projects has been driving the market studied. According to the IEA (International Energy Agency), the world electricity demand is anticipated to increase by nearly 80% between 2012 and 2040. Expansion, modernization, and decentralization of the electricity infrastructure for improved resiliency are the planned investments from organizations. The power grid infrastructure has been progressively becoming more digitized and connected, thereby, ensuring the reliable and secure flow of critical digital communications. Moreover, various projects have begun to take place across the Indian subcontinent, aimed at removing issues faced by the population regarding electricity.
Enormous influx of data has been driving the market growth. According to the Institute of Electrical and Electronics Engineers (IEEE), to enable being smart, a massive amount of data has been exchanged between grid components and the enterprise systems that manage these components. Based on the application, information exchanged helps economically optimized bidirectional power flow between a utility and its customers.
Also, according to a survey published by Bridge Energy, in 2019, 93% of utility vendors have been expecting the availability of solutions to analyze and process data within their company. Furthermore, smart grids collect much more data than the manual energy meter reading system. This permits the use of data analysis techniques and the preparation of highly realistic consumption forecast, as many more variables are taken into account. Therefore, the opportunities for smart grid analytics have been expanding because there is an exponential increase in the amount of data available, in order to develop analytical models.
High costs of smart grid systems and lack of skilled professionals have been restraining the growth of the market. The most prominent limitation in smart metering is the availability of capital funding. Smart systems are comparatively expensive than the regular metering equipment that is employed by most of the service providers and users. Furthermore, different smart meters have been designed with various parameters, based on the operational requirements and consumer requirements, which inhibits as a complicated equipment that needs skilled labor for handling and installation.

[Key Market Trends]
Metering Solution is Expected to Hold Significant Market Growth
The increasing smart grid investments and the surge in the rate of integration of renewable sources of power generation to the existing grids, along with increasing R&D refurbishment activities in developed economies, are expected to support the growth of the global smart metering analytics market.
The continually evolving government framework and policies have been increasing the rate of installations in the residential, commercial, and industrial sectors. Countries, such as China and the United States, have witnessed a highscale deployment of smart meters, mainly due to the continuous support from the respective governments. The aforementioned factors are expected to drive the demand for analytic solutions to handle the vast data from these smart meters.
The Private USbased utility companies, such as ConEd and Duke, have been witnessing significant growth in smart meter deployments. This is evident by the fact that smart meters deployed by utilities in the United States reached about 98 million at the end of 2019 and will reach 107 million by the end of 2020 (Edison Foundation Institute for Electric Innovation Estimates).
Furthermore, in 2019, Energy Efficiency Services Ltd, the energy services company under the Union Ministry of Power, replaced about 50,000 conventional electricity meters with smart meters in the New Delhi Municipal Council area, India. This may result in the generation of more data per year. The Chinese State Grid Corporation also planned to install 380 million smart meters in the country by 2020. Owing to these factors, the market studied is expected to witness growth during the forecast period.

[AsiaPacific to Witness the Fastest Growth]
The AsiaPacific region is being dominated by two highly populated countries, i.e., India and China. The rising population in countries, like China, Japan, and India, has stimulated the demand for residential infrastructure and electricity consumption, thereby, accelerating the demand for electricity in the nations are backing the usage of smart grids, which, in return, may create a market for smart grid data analytics.
The emergence of smart cities is expected to add to the region’s competencies in the market. South Korea decided to invest USD 350 million in 300 companies to help develop an IoT ecosystem within the country. A pilot is being launched in a town southeast of Seoul, in partnership with Samsung Electronics and SK Telecom, to setup IoTbased infrastructure for renewable energy.
Furthermore, one of Thailand’s major utilities has been planning to use data from smart grids and smart meters to track and predict electricity outages in the future. This may help in improving the distribution of power to customers
Moreover, in July 2019, a Switzerlandbased smart grid company, DEPsys opened its second subsidiary, DEPsys Ptd Ltd, in Singapore. This subsidiary is expected to meet the needs of distribution system operators (DSOs) in AsiaPacific, by contributing to the digitization of grids.
Also, in August 2019, Itron partnered with the governmentowned utility, Western Power, in Australia to connect around 240,000 electricity meters. This partnership may help the utility provider gain visibility into the operation of its electricity distribution network, enabling automated data collection, new remote services, and the ability to proactively monitor faults and outages.
Therefore, all the above factors combined mayfuel the smart grid market, which, in return, may boost the smart grid data analytics market in the AsiaPacific region, during the forecast period.

[Competitive Landscape]
The smart grid data analytics market is fragmented and highly competitive in nature. Owing to the emergence of new startups offering a broad range of innovative solutions catering to diverse industry requirements, the market has been witnessing intensifying competitive rivalry. Also as the major players have been considered to be synonymous with good performance, they are expected to have a competitive edge. Key players include Siemens AG, Itron Inc., and IBM Corporation, among others. Recent developments in this market are:

Oct 2019 Uptake partnered with Symboticware to provide mining companies with an endtoend, integrated AI, and data science solution to increase the productivity of mobile mining equipment. The joint solution combines Symboticware’s SymBot device, which provides comprehensive data capture from mining fleets, and Uptake’s Asset Performance Management (APM) software, Asset IO, which applies AI to surface predictive insights from the data.
Jan 2020 Itron Inc. signed a contract with the Los Angeles Department of Water and Power (LADWP) to improve grid awareness and reduce operating costs. Through this partnership, LADWP may deploy Itron’s Industrial IoT network and Distribution Automation (DA) solution, with the aim of modernizing its grid.

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レポート目次

1 INTRODUCTION
1.1 Study Assumptions
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Growing Investments in Smart Grid Projects
4.2.2 Enormous Influx of Data
4.3 Market Challenges
4.3.1 High Costs of Smart Grid Systems and Lack of Skilled Professionals
4.4 Industry Value Chain Analysis
4.5 Industry Attractiveness – Porter’s Five Forces Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Deployment
5.1.1 Cloud-based
5.1.2 On-premise
5.2 By Solution
5.2.1 Transmission and Distribution (T&D) Network
5.2.2 Metering
5.2.3 Customer Analytics
5.3 By Application
5.3.1 Advanced Metering Infrastructure Analysis
5.3.2 Demand Response Analysis
5.3.3 Grid Optimization Analysis
5.4 By End-user Vertical
5.4.1 Private Sector (SMEs and Large Enterprises)
5.4.2 Public Sector
5.5 Geography
5.5.1 North America
5.5.2 Europe
5.5.3 Asia-Pacific
5.5.4 Latin America
5.5.5 Middle East & Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Siemens AG
6.1.2 Itron Inc.
6.1.3 AutoGrid Systems Inc.
6.1.4 General Electric Company
6.1.5 IBM Corporation
6.1.6 SAP SE
6.1.7 Tantalus System Corporation
6.1.8 SAS Institute Inc.
6.1.9 Hitachi Ltd
6.1.10 Uplight Inc.
6.1.11 Landis & Gyr Group AG
6.1.12 Uptake Technologies Inc.
6.1.13 Schneider Electric SE
6.1.14 Oracle Corporation
6.1.15 Amdocs Corporation
6.1.16 Sensus USA Inc. (Xylem Inc.)
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS