The Global Smart Grid Data Analytics Market was valued at USD 1,451.6 million in 2019 and is expected to reach USD 2,943.9 million by 2025, registering a CAGR of 12.76%, during the period of 2020-2025.
With the advent of advanced technology such as IoT, players are focusing on integrating smart grid solutions in a wider aspect. As data generation has been continuously experiencing an upward trend, power utility companies are 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 behaviour, and hence, facilitate customer segmentation.
Key Highlights
Growing investment in smart grid projects drives the market. 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 is 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 drives the market growth. According to the Institute of Electrical and Electronics Engineers (IEEE), to enable being smart, a massive amount of data is 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 are 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 are 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 restraints 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. Further, different smart meters are 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.
Major Market Trends
Metering Solution 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 are increasing the rate of installations in the residential, commercial, and industrial sectors. Countries, such as China and the United States have witnessed a high-scale 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 US-based utility companies, such as ConEd and Duke, are 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 will 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.
Asia-Pacific to Witness the Fastest Growth
The Asia-Pacific region is being dominated by two highly populated country 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, therefore accelerating the demand for electricity in the nations are backing the usage of smart grids which in return will 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 IoT-based infrastructure for renewable energy.
Further, one of Thailand's major utilities is planning to use data from smart grids and smart meters to track and predict electricity outages in the future. This will help improve the distribution of power to customers
Moreover, in July 2019, a Switzerland-based 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 Asia-Pacific by contributing to the digitization of grids.
Also, in August 2019, Itron partnered with the government-owned utility, Western Power, in Australia to connect around 240,000 electricity meters. This partnership will 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 will fuel the smart grid market which in return will boost the smart grid data analytics market in the Asia-Pacific region during the forecasted 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 is witnessing intensifying competitive rivalry. Also as the major players are considered to be synonymous with good performance, they are expected to have a competitive edge. Key players are Siemens, Itron, IBM Corporation, etc.
Some recent developments in this market are:
Oct 2019 - Uptake partnered with Symboticware to provide mining companies with an end-to-end, 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 will deploy Itron's Industrial IoT network and Distribution Automation (DA) solution with the aim of modernizing its grid.
Key Topics Covered
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 Force 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 and 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.)
