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A service for energy industry professionals · Thursday, March 28, 2024 · 699,539,333 Articles · 3+ Million Readers

AI in Energy Management Market

Research Report: By Type (Cloud, On-Premises), Solution (Renewable Management, Demand Management, Infrastructure Management), Application (Energy Generation, Energy Transmission, Energy Distribution, Energy Output Forecasting), Technology (Machine Learning, NLP, Computer Vision), End User (Manufacturing, Utility, Residential, Government, Retail, Healthcare, Education) - Industry Opportunity Analysis and Growth Forecast to 2024.

/EIN News/ -- New York, Jan. 29, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "AI in Energy Management Market" - https://www.reportlinker.com/p05842955/?utm_source=GNW

From $4,439.1 million in 2018, the artificial intelligence (AI) in energy management market is projected to grow to $12,200.9 million in 2024, at a 19.8% CAGR during 2019–2024 (forecast period). Based on end user, the market was dominated by the utility category, in 2018, as AI solutions are being deployed by numerous companies, including Dominion Energy Inc. and Duke Energy Corporation, to bridge the gap between the demand and supply of electricity.

The most significant trend being observed in the AI in energy management market is the integration of internet of things (IoT) in energy management systems (EMS). IoT provides remote control, software automation, data insights, and proactive monitoring, in EMSs. It uses smart sensors and meters, installed in production lines as well as machines, to alert users about the amount of energy being consumed. Additionally, with the complete package of services and software IoT offers, energy costs can be reduced substantially.

The use of AI to make the grid more efficient is a major AI in energy management market growth driver. A grid is a complex system of wires, transformers, and other infrastructure components, through which electricity is transported over long distance. Such infrastructure differs vastly in complexity and size; it can be for a single building, an entire nation, or one which distributes energy across countries and continents, in which case it is called a transcontinental grid.

The power in the grid comes from a variety of sources, including fossil-fuel-based power plants, solar panel installations, wind power plants, hydroelectricity plants, as well as nuclear power stations, which makes their operation a cumbersome process. With AI analyzing the massive volumes of data generated from their operations on a daily basis, they become stable and energy-efficient, thereby driving the AI in energy management market growth.
Read the full report: https://www.reportlinker.com/p05842955/?utm_source=GNW

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