Smart Grid Data Analytics Market size See Incredible Growth during 2030

The global smart grid data analytics market was valued at USD 2,951.6 million in 2021 and is expected to reach USD 7,681.5 million by 2030, registering a CAGR of 12.7% from 2022 to 2030. In the current era of the smart grid, massive amounts of data are being generated. Data analytics solutions (the process of analyzing data, primarily to identify significant, useful, and interesting trends and patterns) are expected to enable the utility to transform the vast volume of information generated into profitable business insights. Globally, electric power systems have been witnessing changes. These electric power systems depend on centralized fossil-fuel plants to generate electricity and extensive grids to deliver it to different end-users.

The demand for cost-effective power supplies for consumers in the utility sector led the global market for smart grid analytics. In an ever-growing power environment, a vast amount of data is generated by smart meters, sensors, automated dispensing systems, etc. Utility owners or suppliers utilize this huge amount of data to track demand and consumption, prevent power cuts, and reduce downtime. The organizations can collect thousands of data points and elements per month from the smart meters installed and various measurements. This technological shift was primarily enabled by the improvements in communications and metering technology, mostly supported by plummeting costs for storage and processing power.

The large-scale adoption of smart meters is a significant measure of future-ready technologies. Smart meters pave the way for the distribution and smart grid, enabling two-way real-time communication between DISCOMs and consumers through GPRS technology. This resulted in several ongoing projects for installing smart meters for enabling efficient management and utilization of gas, water, and electricity resources.

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Global Smart Grid Data Analytics Market Dynamics

DriversGrowing Investments in Smart Grid Projects

Growing investments in smart grid projects worldwide positively boost the market’s growth. According to the IEA, the world electricity demand is anticipated to increase by nearly 80 % between 2012 and 2040. Modernization, expansion, and decentralization of the electricity infrastructure for improved resiliency are the planned investments from organizations, such as the World Economic Forum (USD 7 . 6 trillion allocated for smart grids for the next 25 years) are expected to change several market dynamics in the global scenario.

The power grid infrastructure is progressively becoming more digitized and connected, ensuring the reliable and secure flow of critical digital communications. Thus, smart grid infrastructure, whether in a power substation or residential setting. Smart meters that enable real-time measurements to monitor equipment health, grid congestion, stability, and system control form the integral part of smart grids.

RestraintsHigh Costs of Smart Grid Systems and Lack of Skilled Professionals

The high cost of the initial investment in the smart grids system is challenging the market’s growth. The most prominent limitation in smart metering is the availability of capital funding. Smart systems are comparatively expensive than the regular metering equipment employed by most service providers and users.

These systems utilize digital components and connectivity systems to operate and transmit data. This increases the cost of metering equipment. Additionally, different smart meters are designed with various parameters based on operational and consumer requirements, thereby driving the costs. Furthermore, smart meters are complicated equipment that needs skilled labor for handling and installation.

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Scope of the Smart Grid Data Analytics Market Report

The study categorizes the smart grid data analytics market based on deployment, solution, application, and end-users at the regional and global levels.

By Deployment Outlook (Sales/Revenue, USD Million, 2017-2030)

  • Cloud-based
  • On-premise

By Solution Outlook (Sales/Revenue, USD Million, 2017-2030)

  • Transmission and Distribution (T&D) Network
  • Metering
  • Customer Analytics

By Application Outlook (Sales/Revenue, USD Million, 2017-2030)

  • Advanced Metering Infrastructure Analysis
  • Demand Response Analysis
  • Grid Optimization Analysis

By End-Users Outlook (Sales/Revenue, USD Million, 2017-2030)

  • Private Sector
  • Public Sector

By Region Outlook (Sales/Revenue, USD Million, 2017-2030)

  • North America (US, Canada, Mexico)
  • South America (Brazil, Argentina, Colombia, Peru, Rest of Latin America)
  • Europe (Germany, Italy, France, UK, Spain, Poland, Russia, Slovenia, Slovakia, Hungary, Czech Republic, Belgium, the Netherlands, Norway, Sweden, Denmark, Rest of Europe)
  • Asia Pacific (China, Japan, India, South Korea, Indonesia, Malaysia, Thailand, Vietnam, Myanmar, Cambodia, the Philippines, Singapore, Australia & New Zealand, Rest of Asia Pacific)
  • The Middle East & Africa (Saudi Arabia, UAE, South Africa, Northern Africa, Rest of MEA)

The transmission and distribution network segment is accounted for the largest market share by solution

The global smart grid data analytics market is distributed into transmission and distribution (T&D) network, metering, and customer analytics based on type. In 2021, the transmission and distribution network segment accounted for the largest market share of 53.7% in the global smart grid data analytics market. Analytic solutions pertaining to the management and optimization of the transmission and distribution assets are considered part of this segment's study scope. The power transmission and distribution network is experiencing significant changes from the traditional structure of a vertically integrated utility to several different models. The deployment of advanced analytics is helping the transmission and distribution operators to improve performance, reduce asset-management costs, and capture value.

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Furthermore, with the rapid technological advancement and the emergence of IoT, T&D operators can generate actionable insights, track and monitor disruptions in supply by analyzing relevant and real-time data from equipment, such as sensors, smart meters, and other communications devices. Thus, this approach, also called electric asset analytics, helps the operators improve productivity based on asset health, criticality, and maintenance schedule measures. TD's adoption has been higher due to faster realization of benefits that analytics bring and ease of integration, owing to reach factor and scalability.

Asia Pacific accounts for the highest CAGR during the forecast period

The global smart grid data analytics market has been segmented across North America, Asia-Pacific, Europe, South America, and the Middle East & Africa. Asia Pacific is projected to hold the highest CAGR of 14.4% in the global smart grid data analytics market during the forecast period. The region's growth is primarily due to strong economic growth in the domestic emerging countries such as China, Indonesia, Malaysia, and India.

In India, a major factor of the increase in deployments is the government-owned energy services company, Energy Efficiency Services Limited (EESL), whose demand aggregation and bulk procurement model is actively addressing the cost issue of smart metering investments. Moreover, The South Korean government aims to increase investment in Vietnam, especially in manufacturing electronic equipment and developing smart grids, as Vietnam faces major challenges in ensuring enough electricity.

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Key Market Players

The smart grid data analytics market is mildly concentrated in nature with few numbers global players operating in the market such as AutoGrid Systems Inc., General Electric Company, IBM Corporation, Siemens AG, Itron Inc., SAP SE, Tantalus System Corporation, SAS Institute Inc., Hitachi Ltd, Uplight Inc., Uptake Technologies Inc., Oracle Corporation, Amdocs Corporation, Landis & Gyr Group AG, Schneider Electric SE, and Sensus USA Inc. (Xylem Inc.). Every company follows its business strategy to attain the maximum market share.

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