The AI in Energy and Utilities Market is forecast to reach $4.5 billion by 2026, growing at a CAGR of 32.75% from 2021 to 2026. The market is driven by the rapid demand for power and dearth of information grid in power generation. Artificial intelligence (AI) is an extent of computer technology that highlights the formation of intelligent machines that work and react like humans. The energy and utility sector involves in production and distribution of energy constitutes of oil and gas, power generation and others. As technologies are getting advanced, the energy and utility sector is experiencing a rapid change in price collision and energy storing technologies. Artificial intelligence creates drastic changes in the energy and utility sectors. The effects of AI technology can be seen in their applications such as smart autonomous grid, energy distribution system and so on. Heavy investment is one of the biggest challenge hindering the growth of this technology in energy and utilities sector.
AI in Energy and Utilities Market Segment Analysis – By Application
Demand Forecasting has dominated the AI in Energy and Utilities Market as compared to the other applications due to rising demand for efficiency improvements drive the adoption of AI technology for this application. Artificial intelligence are now deployed in energy and utilities too. Some applications are storage, autonomous grid, failure management, upstream exploration, energy consumption, load forecasting, yield optimizing, predictive maintenance, device management, energy theft. A significant share of companies involved in Energy and Utilities already bestowed training to their employees on AI related and other big data frameworks while the remaining are showing signs of interest to move towards AI.
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AI in Energy and Utilities Market Segment Analysis – By End Use Industry
The Utilities sector has been witnessing significant growth among End Use Industries. AI can be integrated with all the cycles of electricity i.e. from generation to transmission and energy distribution to the end users. The autonomous energy grid is the new technology which is self-organized and can control itself by employing advanced AI machine learning techniques, and simulate to create resilient, useful, and affordable optimizing energy systems. NREL (National Renewable Energy Laboratories) is working to develop these energy grids that can be optimized for secure, resilient, and economic operations. This technology will change the whole scenario in which the energy is generated and distributed. AI will mark the paradigm shift in energy and utilities market.
AI in Energy and Utilities Market Segment Analysis – By Geography
North America dominates the AI in Energy and Utilities Market at a share of 42% due to the increasing adoption of technological advancements in the region. However, APAC witnesses highest growth during the forecast period. Artificial Intelligence in Energy and Utilities Market is driven by vast range of energy production in nations like the U.S and Brazil. The key applications in the region include Robotics and Demand forecasting among others.
AI in Energy and Utilities Market Drivers
Technological Advancement driving new applications
Energy and utilities sectors are innovating their products with the help of AI technology. NextEra Energy invested in machine learning based wind projects in U.S. The project is initiated to avoid any power fluctuations in nearby areas. Duke Energy implemented power plants over some areas in the U.S by converging the Industrial IOT and AI system to predict and analyze power failure. There are some other key players, such as Southern Company and Dominion Resources. Southern Company started its project to save energy consumption as they implemented AI system to predict and provide the amount of energy required in specific areas. Dominion Resources are focused towards grid analytics and control with the help of machine learning. These advancements are developing new applications in the energy sector thereby driving the market.
Rise of Microgrid Adoption
The rise of Microgrid adoption, especially due to implementation of smart cities will drive the market. The microgrid market is evolving and growing rapidly. Many governmental organizations are investigating the viability of microgrids to enable continuation of service during an emergency or power outage. Emerging with different technologies such as distributed energy resources and blockchain, AI has potential to deliver the active management which is the requirement of the future. Powerful AI will have that much capability to balance grids, demands, negotiate actions, self-healing and facilitating the host of new products and services. Siemens is designing self-sufficient smart autonomous microgrid system in Finland. Currently, the investment on this project is not predicted, but concerning about renewable energy and new technology, the Ministry of Economic Affairs and Employment (MEAE) gone through their projects and taken their investments in granted. This rise of microgrid and smart grid will drive the adoption of AI in Energy sector.
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AI in Energy and Utilities Market Challenges
Concerns Regarding Data Privacy
Privacy concerns are cropping up as companies feed more and more consumer and vendor data into advanced, AI-fuelled algorithms to create new bits of sensitive information, unbeknownst to affected consumers and employees. This is especially prevalent in the utilities sector, where consumer data collection has been at the forefront in terms of big data challenges. These data privacy concerns will hinder the adoption of AI especially in utilities sector.
Product launches, acquisitions, and R&D activities are key strategies adopted by players in the AI in Energy and Utilities Market. The AI in Energy and Utilities Market is dominated by major companies such as Alpiq (Switzerland), SmartCloud Inc. (U.S.), General Electric (U.S.), Siemens AG (Germany), Hazama Ando Corporation (Japan), ATOS SE (France), AppOrchid Inc. (U.S), Zen Robotics Ltd. (Finland) and others.
DeepMind, a startup acquired by Google, will add artificial intelligence to the electricity system of UK, based on plans of the UK’s National Grid. The project will process information from various parameters such as weather forecasts, internet searches for incidents that may affect demand and so on and predict electricity demand. For example, heat waves would raise the demand for using air conditioning, and raise the consumption.
Siemens released new software known as active network management (ANM) to predict interaction of grids with different energy loads and track changes. The tracking should remove the need for manual adjustments and may open up new avenues such as charging of electric vehicles.
Deployment of AI into energy sector resulted in drastic changes in the transmogrification of energy in energy sources distribution. AI has brought advancement in the devices for auto detection and other energy infrastructure.
Both Energy & Utility sectors have proven to be the most innovative in the application of Artificial Intelligence.
Energy production has been influenced by Artificial Intelligence in more ways than one. For example it helped in optimizing drilling by identifying the right spots of energy resources for drilling.
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