The global AI in energy management market was valued at $4,439.1 million in 2018, and is further expected to generate $12,200.9 million revenue in 2024, exhibiting a CAGR of 19.8% during the forecast period. This can be attributed to the use of AI to improve grid stability, forecast energy usage, and make energy-saving decisions, and the increasing adoption of AI for low-carbon electricity generation. Among all regions, the North American market is expected to witness the fastest growth during the forecast period, owing to the presence of a large number of AI solution providers in the U.S.
Factors Governing AI in Energy Management Market
Integration of IoT in energy management systems (EMSs) is one of the key trends ongoing in the AI in energy management market. IoT plays a vital role in delivering software automation, remote controls, proactive monitoring, and data insight services. It helps to display the energy consumption value with the help of smart meters and sensors at the machine and production line levels.
Leveraging AI to improve grid stability is one of the key factors driving the growth of the AI in energy management market across the globe. A grid system is an interconnected network that stores the energy and defines its flow. Grids store energy from multiple sources, such as solar power plants, wind power stations, and other electricity generation plants. By leveraging AI for analyzing massive data sets, grid systems become far more stable and energy efficient in managing more than one energy source at once.
AI-enabled robots have the potential to revolutionize the cost structure and operations of energy companies along with reducing risks and improving health of the energy personnel. AI-enabled robots are capable of inspecting, certifying, maintaining, and repairing energy installation units. The prospect of high speed and low processing costs makes the application of AI result oriented for oil companies that require a fast and cheap way to determine if there is any oil at the bottom of a drilled well .
AI in Energy Management Market Segmentation Analysis
When segmented on the basis of deployment type, the cloud category is projected to grow at a higher rate in the AI in energy management market during the forecast period. This can be attributed to the fact that a majority of companies are expected to shift to cloud-based deployment model.
Among all solutions, the demand management category held the largest share in the AI in energy management market in 2018. This is attributed to the focus of utilities for predicting the total energy demand with AI-based smart meters to provide apt energy across households.
In terms of application, the energy generation category is projected to grow fastest throughout the forecast period in the AI in energy management market. This can be owed to the increasing requirement for managing the total output of energy generated from multiple sources, such as thermal plants, wind power stations, and solar power plants, to match the spatial and temporal variations in real time.
Based on end user, the utility category is projected to exhibit the fastest growth during the forecast period. This can be attributed to the major focus of AI solution providers to manage the energy requirements for industrial buildings.
Based on technology, machine learning held the largest market in 2018, owing to the fact that machine learning systems are gaining traction in the market for energy management as these involve the study of algorithms and statistical models to provide systems the ability to automatically perform tasks with more accuracy.
Geographical Analysis of AI in Energy Management Market
Globally, North America held the largest market share in the 2018. The trend is further projected to continue throughout the forecast period. The U.S. is projected to lead the North American AI in energy management market as it is actively deploying AI in its energy sector for the integration of energy generated from renewable and non-renewable sources into the total energy supply.
Further, the APAC AI in energy management market is projected to register a considerable CAGR during the forecast period. This can be attributed to the strong initiatives taken by governments of developing countries, such as China and India, to increase the AI adoption.
Competitive Landscape of AI in Energy Management Market
The global AI in energy management market has a fragmented structure, due to the presence of a large number of key players, including General Electric Company, Schneider Electric SE, IBM Corporation, ABB Ltd., Eaton Corporation plc., and Mitsubishi Electric Corporation.
Recent Strategic Developments of AI in Energy Management Market Players
In recent years, major players in the AI in energy management market have taken several strategic measures, such as mergers & acquisitions, product launches, and geographical expansions, to gain a competitive edge in the industry. For instance, in May 2019, Eaton Corporation plc. launched Energy Aware, a frequency response energy solution, which enables grids stabilization in the energy industry and contributes more to power generation from renewable sources. The solution enables organizations to support electric grid stability while powering critical applications, as it uses reserve uninterruptible power supply (UPS).
Further, in December 2018, ABB Ltd., one of the top providers for power grids and electrification solutions, signed a deal with Japanese conglomerate Hitachi Ltd. to sell off its power grid division for $11 billion. With the acquisition of power grid business of ABB, Hitachi Ltd. will expand its global footprint as a leader in energy infrastructure solutions.
Key Questions Addressed/Answered in the Report
- What is the current scenario of the global AI in energy management market?
- What are the historical size and the present size of the market segments and their future potential?
- What are the major catalysts for the market and their impact during the short, medium, and long terms?
- What are the evolving opportunities for the players in the market?
- Which are the key geographies from the investment perspective?
- What are the key strategies adopted by the major players to expand their market share?
- What is the potential of AI in energy management in the global scenario?
