Overview and Scope
AI in energy refers to the application of artificial intelligence (AI) technologies and techniques in the energy sector to improve efficiency, optimize operations, and enhance decision-making. AI in energy includes data analysis, grid management and security, and demand response. AI in energy is used to maximize the recycling of materials used in renewable energy systems, such as solar panels, wind turbines, and hydroelectric dams.
Sizing and Forecast
The ai in energy market size has grown exponentially in recent years. It will grow from $5.23 billion in 2023 to $6.39 billion in 2024 at a compound annual growth rate (CAGR) of 22.2%. The growth in the historic period can be attributed to data analytics for efficiency, demand response management, predictive maintenance, grid optimization, renewable energy integration..
The ai in energy market size is expected to see exponential growth in the next few years. It will grow to $13.36 billion in 2028 at a compound annual growth rate (CAGR) of 20.2%. The growth in the forecast period can be attributed to decentralized energy systems, energy storage management, smart cities and infrastructure, electrification of transportation, integration of edge computing.. Major trends in the forecast period include energy efficiency analytics, autonomous energy infrastructure, cybersecurity solutions, virtual power plants, edge ai for energy management..
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The ai in energy market covered in this report is segmented –
1) By Offering: Support Services, Hardware, AI-As-A-Service, Software
2) By Deployment: On-Premise, Cloud
3) By Application: Demand Response Management, Fleet And Asset Management, Renewable Energy Management, Precision Drilling, Demand forecasting, Infrastructure Management, Other Applications
4) By End User: Energy Transmission, Energy Generation, Energy Distribution, Utilities, Other End Users
North America was the largest region in AI in the energy market in 2023. Asia-pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the ai in energy market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
The increasing use of microgrids is expected to propel the growth of AI in the energy market going forward. A microgrid is a localized energy system operating independently or in conjunction with the primary power grid. Microgrids play a significant role in integrating and optimizing AI technology within the energy sector, enabling intelligent energy management, grid optimization, and the integration of renewable energy sources. These help in AI energy applications like demand response, load balancing, and the integration of renewable energy. AI in the energy market is seeing significant growth as there is an increase in the use of microgrids. For instance, according to a November 2021, according to the Guidehouse, a US-based consulting firm, in the US around 979 megawatt of renewable microgird capacity was installated in 2021 and it is expected to reach 32,470 MW by 2030. Therefore, the increasing use of microgrids is expected to drive the growth of AI in the energy market going forward.
Key Industry Players
Major companies operating in the ai in energy market report are Google, Microsoft Corporation, Engie SA, Huawei Technologies Co Ltd., Siemens AG, General Electric Company, Intel Corporation, International Business Machines Corporation, Iberdrola, Cisco Systems Inc., Schneider Electric SE, Honeywell International Inc., Flex Ltd., ABB Ltd, Duke Energy Corporation, Nvidia Corporation, Alpiq Holding AG, ATOS SE, Enel Green Power S.p.A., Databricks Inc., C3 AI, Uptake Technologies, Sentient Energy Inc., AutoGrid Systems Inc., Arundo Analytics Inc., Bidgely Inc., Verdigris Technologies, Greenbird Integration Technology AS, AppOrchid Inc., Ecube Labs Co. Ltd
The ai in energy market report table of contents includes:
1. Executive Summary
2. AI In Energy Characteristics
3. AI In Energy Trends And Strategies
4. AI In Energy – Macro Economic Scenario
5. Global AI In Energy Size and Growth
…..
32. Global AI In Energy Competitive Benchmarking
33. Global AI In Energy Competitive Dashboard
34. Key Mergers And Acquisitions In The AI In Energy
35. AI In Energy Future Outlook and Potential Analysis
36. Appendix
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