Smart Grid Data Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

Market Overview

The smart grid data analytics market was valued at USD 1,615 million in 2020, and it is expected to reach USD 3,289.15 million by 2026, registering a CAGR of 12.76%, during the period of 2021-2026. 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.

Scope of the Report

The study characterizes the smart grid data analytics market based on the deployment, solution, applications, and end-user verticals.​ Moreover, at the end-user level, smart grids can enable demand flexibility and consumer participation in the energy system, including through demand response, electric vehicle (EV) charging, and self-produced distributed generation and storage.

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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 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, 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.

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