Artificial Intelligence Ai In Renewable Energy Market
Artificial Intelligence (AI) in Renewable Energy Market Forecasts to 2030 - Global Analysis By Source (Wind Energy, Hydropower, Solar Energy, Geothermal Energy, Bioenergy, and Other Sources), Deployment Mode, Technology, Application, End User and By Geography
|
Years Covered |
2022-2030 |
|
Estimated Year Value (2024) |
US $940.50 MN |
|
Projected Year Value (2030) |
US $3622.31 MN |
|
CAGR (2024- 2030) |
25.2% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
Asia Pacific |
|
Highest Growing Market |
North America |
According to Stratistics MRC, the Global Artificial Intelligence (AI) in Renewable Energy Market is accounted for $940.50 million in 2024 and is expected to reach $3622.31 million by 2030 growing at a CAGR of 25.2% during the forecast period. Advanced algorithms, machine learning, and data analytics are used in renewable energy to maximize energy production, distribution, and consumption from renewable sources such as solar, wind, and hydro. AI enhances grid management, predicts energy demand, improves efficiency, and enables predictive maintenance of renewable energy infrastructure. By integrating AI, energy providers can minimize costs, reduce carbon emissions, and enhance reliability, making renewable energy more sustainable and scalable in the transition toward a cleaner global energy system.
_in_Renewable_Energy_Market-FIG.png)
Market Dynamics:
Driver:
Rising need for grid optimization
The increasing complexity of power systems and the integration of renewable energy sources necessitate advanced AI solutions for efficient grid management. AI can help in predicting energy demand, managing supply, and ensuring the stability of the grid. It can also optimize energy storage and distribution, reducing losses and improving efficiency. Moreover, AI can facilitate the integration of distributed energy resources like solar and wind, enhancing grid flexibility. As renewable energy adoption grows, so does the need for sophisticated grid optimization tools. Hence, AI is becoming indispensable in modern energy grids.
Restraint:
Energy consumption of AI models
The high computational power required for AI models can lead to significant energy consumption. This energy consumption can sometimes offset the efficiency gains achieved in renewable energy systems. Training large AI models requires substantial computational resources, which translates to increased energy use. Additionally, the continuous operation of AI systems for real-time data analysis and decision-making further adds to energy consumption. This poses a challenge for the sustainability of AI in the renewable energy sector. Balancing the benefits of AI with its energy footprint remains a critical concern.
Opportunity:
Increased investments in smart grids
Smart grids incorporate advanced sensors, communication networks, and AI algorithms to improve energy management. These investments aim to enhance grid reliability, reduce outages, and increase efficiency. AI plays a pivotal role in smart grids by enabling predictive maintenance, demand forecasting, and dynamic grid balancing. As governments and private sectors invest in smart grid infrastructure, the demand for AI-based solutions is set to rise. This presents a significant growth opportunity for AI in the renewable energy market.
Threat:
Data security and privacy concerns
The extensive data generated by AI applications in renewable energy raises concerns about data security and privacy. Unauthorized access to sensitive data can lead to significant security breaches and financial losses. Additionally, the integration of AI with grid infrastructure makes it a potential target for cyber-attacks. Ensuring robust cyber-security measures is crucial to protect against these threats. Compliance with data protection regulations further adds to the complexity of managing AI systems in renewable energy. Addressing these security challenges is vital for the widespread adoption of AI in this sector.
Covid-19 Impact
The pandemic has accelerated the adoption of digital technologies, including AI, in the renewable energy sector. AI has been leveraged for remote monitoring, predictive maintenance, and optimizing energy usage during lockdowns. The need for resilient and flexible energy systems has become more apparent, driving investments in AI solutions. However, the pandemic has also highlighted the vulnerability of energy infrastructure to disruptions. Ensuring the reliability and stability of energy systems during such crises is crucial.
The hydropower segment is expected to be the largest during the forecast period
The hydropower segment is expected to account for the largest market share during the forecast period, due to the established infrastructure and the potential for integrating AI to optimize operations and enhance efficiency. AI can improve water flow management, predict equipment failures, and optimize energy production. The ability to generate large amounts of renewable energy with minimal environmental impact makes hydropower an attractive option. Additionally, the integration of AI can further enhance the sustainability and reliability of hydropower systems.
The residential segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the residential segment is predicted to witness the highest growth rate. AI-enabled energy management systems can optimize energy usage, reducing costs and enhancing convenience for homeowners. The rise of distributed renewable energy generation, such as rooftop solar, further drives the adoption of AI solutions in residential settings. Additionally, government incentives and subsidies for residential renewable energy systems contribute to this growth.
Region with largest share:
During the forecast period, Asia Pacific region is expected to hold the largest market share, due to significant investments in renewable energy infrastructure. Countries like China and India are leading the charge in renewable energy adoption, supported by government initiatives and favourable policies. The region's focus on sustainable development and reducing carbon emissions drives the demand for AI solutions in energy management. Additionally, the presence of major AI technology providers in the region further boosts market growth.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to strong government support, technological advancements, and a robust market for renewable energy solutions. The United States and Canada are investing heavily in AI and renewable energy projects, driven by the need to reduce carbon emissions and enhance energy efficiency. Additionally, the presence of leading AI and renewable energy companies in North America contributes to this high growth rate.
Key players in the market
Some of the key players profiled in the Artificial Intelligence (AI) in Renewable Energy Market include Google, Microsoft, IBM, Siemens, General Electric (GE), Schneider Electric, ABB Ltd., Tesla, Enel Group, NextEra Energy, Shell AI, GridBeyond, Kayrros, Open Energi, Autogrid Systems, Verdigris Technologies, Innowatts, Uptake Technologies, Xcel Energy, and UrbanChain.
Key Developments:
In January 2025, General Electric (GE) America’s leading energy manufacturing company, is planning to invest nearly $600 million in its U.S. factories and facilities over the next two years to help meet the surging electricity demands around the world.
In July 2024, Siemens consortium partners with Bengaluru Metro Rail Corporation Limited for Rail Electrification technologies. Siemens Limited, as part of a consortium along with Rail Vikas Nigam Limited (RVNL), has secured an order from Bangalore Metro Rail Corporation Limited (BMRCL) for electrification of Bengaluru Metro Phase 2 project contributing to sustainable public transport in the city.
Sources Covered:
• Wind Energy
• Hydropower
• Solar Energy
• Geothermal Energy
• Bioenergy
• Other Sources
Deployment Modes Covered:
• On-Premises
• Cloud-Based
Technologies Covered:
• Machine Learning (ML)
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Other Technologies
Applications Covered:
• Energy Forecasting
• Energy Storage Management
• Grid Management & Optimization
• Predictive Maintenance
• Demand Response Management
• Energy Trading
• Other Applications
End Users Covered:
• Utilities & Power Generation Companies
• Renewable Energy Companies
• Government & Public Sector
• Commercial & Industrial Sector
• Residential
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 End User Analysis
3.9 Emerging Markets
3.10 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Artificial Intelligence (AI) in Renewable Energy Market, By Source
5.1 Introduction
5.2 Wind Energy
5.3 Hydropower
5.4 Solar Energy
5.5 Geothermal Energy
5.6 Bioenergy
5.7 Other Sources
6 Global Artificial Intelligence (AI) in Renewable Energy Market, By Deployment Mode
6.1 Introduction
6.2 On-Premises
6.3 Cloud-Based
7 Global Artificial Intelligence (AI) in Renewable Energy Market, By Technology
7.1 Introduction
7.2 Machine Learning (ML)
7.3 Deep Learning
7.4 Natural Language Processing (NLP)
7.5 Computer Vision
7.6 Other Technologies
8 Global Artificial Intelligence (AI) in Renewable Energy Market, By Application
8.1 Introduction
8.2 Energy Forecasting
8.3 Energy Storage Management
8.4 Grid Management & Optimization
8.5 Predictive Maintenance
8.6 Demand Response Management
8.7 Energy Trading
8.8 Other Applications
9 Global Artificial Intelligence (AI) in Renewable Energy Market, By End User
9.1 Introduction
9.2 Utilities & Power Generation Companies
9.3 Renewable Energy Companies
9.4 Government & Public Sector
9.5 Commercial & Industrial Sector
9.6 Residential
9.7 Other End Users
10 Global Artificial Intelligence (AI) in Renewable Energy Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa
11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies
12 Company Profiling
12.1 Google
12.2 Microsoft
12.3 IBM
12.4 Siemens
12.5 General Electric (GE)
12.6 Schneider Electric
12.7 ABB Ltd.
12.8 Tesla
12.9 Enel Group
12.10 NextEra Energy
12.11 Shell AI
12.12 GridBeyond
1213 Kayrros
12.14 Open Energi
12.15 Autogrid Systems
12.16 Verdigris Technologies
12.17 Innowatts
12.18 Uptake Technologies
12.19 Xcel Energy
12.20 UrbanChain
List of Tables
1 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Region (2022-2030) ($MN)
2 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Source (2022-2030) ($MN)
3 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Wind Energy (2022-2030) ($MN)
4 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Hydropower (2022-2030) ($MN)
5 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Solar Energy (2022-2030) ($MN)
6 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Geothermal Energy (2022-2030) ($MN)
7 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Bioenergy (2022-2030) ($MN)
8 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Other Sources (2022-2030) ($MN)
9 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Deployment Mode (2022-2030) ($MN)
10 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By On-Premises (2022-2030) ($MN)
11 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Cloud-Based (2022-2030) ($MN)
12 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Technology (2022-2030) ($MN)
13 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Machine Learning (ML) (2022-2030) ($MN)
14 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Deep Learning (2022-2030) ($MN)
15 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Natural Language Processing (NLP) (2022-2030) ($MN)
16 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Computer Vision (2022-2030) ($MN)
17 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Other Technologies (2022-2030) ($MN)
18 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Application (2022-2030) ($MN)
19 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Energy Forecasting (2022-2030) ($MN)
20 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Energy Storage Management (2022-2030) ($MN)
21 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Grid Management & Optimization (2022-2030) ($MN)
22 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
23 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Demand Response Management (2022-2030) ($MN)
24 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Energy Trading (2022-2030) ($MN)
25 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Other Applications (2022-2030) ($MN)
26 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By End User (2022-2030) ($MN)
27 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Utilities & Power Generation Companies (2022-2030) ($MN)
28 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Renewable Energy Companies (2022-2030) ($MN)
29 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Government & Public Sector (2022-2030) ($MN)
30 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Commercial & Industrial Sector (2022-2030) ($MN)
31 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Residential (2022-2030) ($MN)
32 Global Artificial Intelligence (AI) in Renewable Energy Market Outlook, By Other End Users (2022-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
Frequently Asked Questions
In case of any queries regarding this report, you can contact the customer service by filing the “Inquiry Before Buy” form available on the right hand side. You may also contact us through email: info@strategymrc.com or phone: +1-301-202-5929
Yes, the samples are available for all the published reports. You can request them by filling the “Request Sample” option available in this page.
Yes, you can request a sample with your specific requirements. All the customized samples will be provided as per the requirement with the real data masked.
All our reports are available in Digital PDF format. In case if you require them in any other formats, such as PPT, Excel etc you can submit a request through “Inquiry Before Buy” form available on the right hand side. You may also contact us through email: info@strategymrc.com or phone: +1-301-202-5929
We offer a free 15% customization with every purchase. This requirement can be fulfilled for both pre and post sale. You may send your customization requirements through email at info@strategymrc.com or call us on +1-301-202-5929.
We have 3 different licensing options available in electronic format.
- Single User Licence: Allows one person, typically the buyer, to have access to the ordered product. The ordered product cannot be distributed to anyone else.
- 2-5 User Licence: Allows the ordered product to be shared among a maximum of 5 people within your organisation.
- Corporate License: Allows the product to be shared among all employees of your organisation regardless of their geographical location.
All our reports are typically be emailed to you as an attachment.
To order any available report you need to register on our website. The payment can be made either through CCAvenue or PayPal payments gateways which accept all international cards.
We extend our support to 6 months post sale. A post sale customization is also provided to cover your unmet needs in the report.
Request Customization
We provide a free 15% customization on every purchase. This requirement can be fulfilled for both pre and post sale. You may send your customization requirements through email at info@strategymrc.com or call us on +1-301-202-5929.
Note: This customization is absolutely free until it falls under the 15% bracket. If your requirement exceeds this a feasibility check will be performed. Post that, a quote will be provided along with the timelines.
WHY CHOOSE US ?
Assured Quality
Best in class reports with high standard of research integrity
24X7 Research Support
Continuous support to ensure the best customer experience.
Free Customization
Adding more values to your product of interest.
Safe & Secure Access
Providing a secured environment for all online transactions.
Trusted by 600+ Brands
Serving the most reputed brands across the world.
