AI in energy management market has reached a new level in utility and applications that are beyond the expectations owing to advanced engineering. AI is backed by advanced machine learning (AML) along with deep learning algorithms (DLA) and advanced neural network (ANN). AI linked with energy management can handle gigabyte and petabyte of structured, semi-structured, and unstructured data. AI in energy management has been capable enough to identify regular patterns of consumers, making predictions and also provide suitable recommendations based on the understanding of the data. This intelligence system is being harnessed to develop smart applications that not only identify the patterns of energy consumption, however, also take suitable actions using AI technology.
Browse the full report of “AI (Artificial Intelligence) in Energy Management Market by Deployment Type (Cloud and On-Premises) by Application (Renewable Management, Demand Management, and Infrastructure Management) by End-User (Manufacturing, Educational Facilities, Healthcare, and Others) – Global Trends, Size, Share, Growth, Industry Analysis and Forecast, 2019-2025” at https://www.omrglobal.com/industry-reports/ai-in-energy-management-market/
AI is one of the newest and innovative technological trends that is transforming almost every business segment across the globe. There is a burden on the government to reduce carbon emissions and to increase energy production by alternative sources such as solar energy, water energy, thermal energy, and wind energy. The increasing demand for energy is also a major concern not only for the consumers but also for industries as the sources of energy are limited owing to the increasing demand day by day. In short, there is a global demand for a cost-effective, reliable, and efficient source of energy. Thus, the use of AI to cater to the increasing demand for energy is significantly driving AI in energy management market.
Presently, the global energy market is driving toward an enormous shift for de-carbonization, green energy, efficient distribution channel, and new technology. Utilities, independent power producers (IPP), and various energy-producing and distributing companies have been discovering the effective ways to manage the disparity during demand and supply attributing to the increasing use of unpredictable renewable energy sources (RES) in the power generation industry. So, as a result, energy-producing and developing companies along with the grid operators have been exploring various ways in employing AI to improve the overall reach and accessibility of renewable energy technologies.
Furthermore, with technological advancement, AI in the energy management industry possesses remarkable potential in transforming the energy and utility segment. Along with the new technologies such as Big data, Internet of Things (IoT), AI has a lot of potentials to aid the active energy management market in balancing the growing demand for energy. The use of AI in energy management market is for the fault prediction and dynamic maintenance which enables the operator to make predictions regarding various equipment’s failures. Predictions can be made using various sensor data from various operating units; moreover, it reduces the downtime cost and maintenance charges.
Verv, a startup company has invented a metering device which can identify individual home appliance. It can also predict probable faults that may happen if the device is accidentally been left on. In the UK, Google has developed Deepmind, a leading AI-based system. Deepmind has been developed with the objective to balance the energy’s supply and demand in Britain’s National Grid Electricity management system. National Grid’s role in balancing power has become even more advanced in past years as the renewable source of electricity has been developing throughout the globe including solar power and wind energy as the bigger part in the non-conventional source of energy.
The Report Global AI in Energy Management Market Segmentation
By Deployment Type
By Application
By End-User
By region
North America
Europe
Asia-Pacific
Rest of the World