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A12587 | Pages: 300 | Charts: 65 | Tables: 189 |
AI In Energy Market Research, 2029
The global AI in energy market was valued at $5.4 billion in 2023, and is projected to reach $14.0 billion by 2029, growing at a CAGR of 17.2% from 2024 to 2029.
Market Introduction and Definition
Artificial Intelligence (AI) is revolutionizing electricity technology by enhancing the efficiency of renewable power sources like wind, solar, and hydroelectric power. In wind energy, AI algorithms predict weather patterns and wind speeds to optimize turbine operations. For example, computer learning models can adjust the perspective of wind turbine blades in real time to maximize power capture. In photo voltaic power, AI systems forecast sunlight availability and manipulate the positioning of photo voltaic panels to ensure optimal exposure, thus improving the efficiency of photovoltaic cells. AI enhances the functionality and upkeep procedures in photovoltaic (PV) power stations by identifying, sorting, and forecasting abnormalities while planning scheduled maintenance events. In doing so, productivity levels are raised to achieve efficient energy delivery with minimal interruptions.
Artificial intelligence and machine learning solutions are being developed for launch vehicles, spacecraft operations, big data analytics, space robotics, and space traffic management. One of the primary advantages of integrating AI into the energy industry lies in the optimization of energy production and distribution. AI technologies, such as machine learning algorithms, enable the analysis of vast datasets related to energy production, consumption patterns, and environmental factors. This data-driven approach allows for more accurate prediction of energy demand, facilitating the efficient planning and operation of power plants. By optimizing production schedules and distribution networks, AI helps minimize energy wastage, leading to increased overall efficiency.
Predictive maintenance is another significant advantage offered by AI in the energy sector. Through the analysis of sensor data and performance metrics, AI algorithms may predict equipment failures before they occur. This proactive approach to maintenance helps prevent unexpected downtime, reduces repair costs, and prolongs the lifespan of critical infrastructure. By optimizing maintenance schedules based on actual equipment conditions, AI enhances operational efficiency and minimizes disruptions.
Key Takeaways
The AI in energy industry covers 20 countries. The research includes a segment analysis of each country in terms of value ($billion) for the projected period (2024-2029) .
The study integrated high-quality data, professional opinions and analysis, and critical independent perspectives. The research approach is intended to provide a balanced view of the global AI in energy market overview and to assist stakeholders in making educated decisions to achieve their growth objectives.
Over 3,700 product literature, annual reports, industry statements, and other comparable materials from major industry participants were reviewed to gain a better understanding of the AI in energy market size.
The AI in energy market share is highly fragmented, with several players including Atos SE, Siemens Energy, Schneider Electric, GE Vernova, Terex Corporation, Vestas, Iberdrola, S.A., JinkoSolar Holding Co., Ltd., AutoGrid Systems, Inc, Constellation. Also tracked key strategies such as acquisitions, product launches, mergers, and expansion of the players operating in the AI in energy market growth.
Key Market Segments
Key Market Players