The use of energy management systems has risen significantly in recent years. This can be attributed to the surging demand for energy, rising energy crisis, declining rate of fossil fuels, and increasing pollution levels due to excessive use of traditional energy resources. With the rapidly increasing population, the need for energy has been growing as well, and as conventional sources cannot fulfill this demand, the focus has shifted to renewable energy sources. Owing to the variable output of such sources, energy management systems are utilized for managing supply and demand.

These days, advanced technologies, such as AI, are being integrated in these systems for improved outcomes. Ascribed to this, the global AI in energy management market is projected to generate a revenue of $12,200.9 million by 2024, increasing from $4,439.1 million in 2018, advancing at a 19.8% CAGR during the forecast period (2019–2024). The adoption of AI has also been increasing for improving the stability of the grid.

A grid system maintains and stores the flow of energy. Energy is stored from a number of sources in the grid system, such as wind power stations, solar power plants, and electricity generation plants. Owing to this, operating grid systems becomes a complex process, which is why, AI is now being utilized for effective management of grid systems. By integrating AI for analysis of massive sets, grid systems can become highly stable and energy efficient, when it comes to managing multiple sources simultaneously.

This market research report provides a comprehensive overview of the AI in energy management market

Historical and the present size of the AI in energy management market
Future potential of the market through its forecast for the period 2020– 2030
Major factors driving the market and their impact during the short, medium, and long terms
Market restraints and their impact during the short, medium, and long terms
Recent trends and evolving opportunities for the market participants
Historical and the present size of the market segments and understand their comparative future potential