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redictive and prescriptive analytics to find higher application with the rise of 5G, finds Frost & Sullivan

Santa Clara, Calif. – September 10, 2019 – As data becomes central to new business models in the energy utility sector, the global grid analytics market is expected to accelerate from $1.15 billion in 2018 to $2.31 billion in 2025, at a compound annual growth rate (CAGR) of 10.4%. Energy utilities are generating massive volumes of data from smart meters, intelligent energy devices, and multi-sensing units but only 2% to 4% of data from the system is actually leveraged for analytics. This data, combined with a sophisticated analytics platform, can deliver valuable insights for utilities that can lead to improved customer service and operational metrics.

“The market will gradually switch to predictive and prescriptive analytics, especially as networks with low latency capabilities, such as 5G, are employed to minimize reaction times,” said Farah Saeed, Research Director, Energy & Environment at Frost & Sullivan. “Predictive and prescriptive analytics will incorporate statistical models that flag areas of inefficiency, evaluate and predict events in a timely manner, and eventually include Artificial Intelligence (AI) to deliver a holistic decision-making tool.”

Frost & Sullivan’s recent analysis, Global Smart Grid Analytics Market, Forecast to 2025, provides an in-depth analysis of key applications and opportunities in the market. This study segments data analytics into three main areas of the grid network: transmission and distribution (T&D) network, metering, and customer analytics. It covers the regions of North America, Europe, Asia-Pacific, and Rest of the World.

For further information on this analysis, please visit: http://frost.ly/3qp

“North America is currently the largest market for grid analytics but Asia is expected to register the fastest CAGR of 13.3% between 2018 and 2025. The emphasis is on improving energy access and minimizing financial losses including non-technical losses. India and China, in particular, have been leading the way when it comes to utility-scale renewable energy (RE) sources. ” noted Saeed. “Meanwhile, Australia and Singapore are looking to minimize power interruption by integrating geographic information system data analytics and forecast events, and Japan would be an ideal market for customer analytics as it is attempting to achieve 100% smart meter penetration by 2024.”

In the future, the areas with the greatest growth opportunities will include:

  • Service outcome-based business models instead of just power generation and transmission.
  • Internet of Things (IoT) devices and sensors that track and transmit data from and to the grid. IoT infrastructure spending by utilities is forecast to reach more than $2 billion by 2024, growing at a CAGR of 20.5%.
  • RE and electric vehicles. Utilities in Europe and North America are beginning to leverage these resources as baseload and back-up capacity.
  • Initiatives to strengthen the grid to minimize outage times, streamline billing operations, provide real-time energy information, and deliver new and relevant services.

Global Smart Grid Analytics Market, Forecast to 2025 is part of Frost & Sullivan’s global Energy & Environment Growth Partnership Service program.

About Frost & Sullivan

For over five decades, Frost & Sullivan has become world-renowned for its role in helping investors, corporate leaders and governments navigate economic changes and identify disruptive technologies, Mega Trends, new business models and companies to action, resulting in a continuous flow of growth opportunities to drive future success. Contact us: Start the discussion.

 

Global Smart Grid Analytics Market, Forecast to 2025

K30A-14

 

Contact:
Jaylon Brinkley
T: +1 210 247 2481
E: jaylon.brinkley@frost.com

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About Jaylon Brinkley

Jaylon BrinkleyJaylon Brinkley serves as a Corporate Communications Executive with 5+ years of marketing communications expertise. He covers key industries such as Energy and Environment, Manufacturing and Industrial Automation.

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