Smart Grid Data Analytics Market Size

Smart Grid Data Analytics Market Analysis

During the time frame of the forecast, the smart grid data analytics market is expected to register a CAGR of 12.76%. The smart grid data analytics market is expected to develop at a faster rate during the projected period due to increased investment in smart grid initiatives. With the introduction of modern technologies such as IoT, players have been focusing on integrating smart grid solutions in a more significant way. Due to the continuing trend in data creation, power utility businesses are merging big data with billions more rows of new IoT and smart sensor data. Smart meter data can assist in more efficiently segmenting customers by providing a better understanding of their behavior.

• A big need for a smart grid data analytics market is likely to come from the growing need for electricity. According to the International Energy Agency (IEA), the world's electricity demand will rise by 5,900 terawatt-hours (TWh) in the Stated Policies Scenario (STEPS) and by over 7,000 TWh in the Announced Pledges Scenario (APS) by 2030. This is the same as adding the current demand in the United States and the European Union.
• Moreover, organizations plan to invest in the expansion, modernization, and decentralization of the electricity infrastructure for improved resiliency. The infrastructure of the power grid has been getting more digitalized and connected over time, making it possible for important digital communications to flow reliably and safely. Across the Indian subcontinent, there have also been the beginnings of a number of projects that will help people with their electricity problems.
• An enormous influx of data has been driving market growth. According to the 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, the information exchanged helps economically optimize the bidirectional power flow between a utility and its customers.
• 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 forecasts, as many more variables are taken into account. Therefore, the opportunities for smart grid analytics have been expanding because there has been an exponential increase in the amount of data available in order to develop analytical models.
• However, the high costs of smart grid systems and the need for more skilled professionals have been restraining the market's growth. The most prominent limitation of smart metering is the availability of capital funding. Smart systems are comparatively more expensive than the standard metering equipment that most service providers and users employ. Furthermore, different smart meters have been designed with various parameters based on operational and consumer requirements, inhibiting the use of complicated equipment that needs skilled labor for handling and installation.
• The COVID-19 epidemic hurt the world economy because it hurt a lot of businesses, especially in the electricity sector, and stopped work in a lot of other sectors. After COVID-19 broke out, the price of electricity went down, which hurt a lot of companies in the energy and power industries. Additionally, according to the US Department of Homeland Security (DHS), the utility sector was one of the 16 essential infrastructure sectors that the COVID-19 epidemic severely impacted.