The rising requirement for improved grid stability is driving the demand for the incorporation of artificial intelligence (AI) in energy management solutions and systems across the world. A grid system is basically an interconnected network that stores energy and defines its flow. It stores energy from various sources, such as wind power stations, solar power plants, and several other electricity production plants. By utilizing AI to analyze massive data sets, grid systems become stable and highly energy efficient in managing multiple energy sources at a time.
Besides, AI-enabled robots can revolutionize the operations and cost structure of energy firms and massively reduce the risks associated with energy production and management. These robots have the ability to certify, maintain, inspect, and repair energy installation units. Furthermore, these robots can be utilized in the decommissioning and cleaning up of nuclear waste. The integration of AI in energy management operations also assists in generating low-carbon electricity, thereby aiding energy companies in mitigating air pollution levels.
Because of the aforementioned factors, the demand for AI-powered energy management operations is rising sharply, thereby fueling the expansion of the global AI in energy management market. According to the estimates of the market research firm, P&S Intelligence, the value of the market will rise from $4,439.1 million in 2018 to $12,200.9 million by 2024, while the industry will grow at a CAGR of 19.8% from 2019 to 2024. AI is integrated in energy management systems via cloud and on-premises.
Between these two, the popularity of the cloud-based deployment mode was found to be higher in 2018. This was because of the fact that nearly 70% of the total number of companies in the U.S. made considerable investments in cloud-based solutions. AI-enabled energy management systems are used in various applications, such as energy output forecasting, energy transmission, energy distribution, and energy generation. Amongst these, the requirement for these systems was found to be the highest in energy output forecasting applications in the years gone by.
Hence, the demand for AI-powered energy management systems will soar in the coming years, primarily because of the growing need for improved grid stability.
Besides, AI-enabled robots can revolutionize the operations and cost structure of energy firms and massively reduce the risks associated with energy production and management. These robots have the ability to certify, maintain, inspect, and repair energy installation units. Furthermore, these robots can be utilized in the decommissioning and cleaning up of nuclear waste. The integration of AI in energy management operations also assists in generating low-carbon electricity, thereby aiding energy companies in mitigating air pollution levels.
Because of the aforementioned factors, the demand for AI-powered energy management operations is rising sharply, thereby fueling the expansion of the global AI in energy management market. According to the estimates of the market research firm, P&S Intelligence, the value of the market will rise from $4,439.1 million in 2018 to $12,200.9 million by 2024, while the industry will grow at a CAGR of 19.8% from 2019 to 2024. AI is integrated in energy management systems via cloud and on-premises.
Between these two, the popularity of the cloud-based deployment mode was found to be higher in 2018. This was because of the fact that nearly 70% of the total number of companies in the U.S. made considerable investments in cloud-based solutions. AI-enabled energy management systems are used in various applications, such as energy output forecasting, energy transmission, energy distribution, and energy generation. Amongst these, the requirement for these systems was found to be the highest in energy output forecasting applications in the years gone by.
Hence, the demand for AI-powered energy management systems will soar in the coming years, primarily because of the growing need for improved grid stability.
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