Climate Energy

Artificial intelligence and machine learning have the potential to revolutionize the renewable energy market

Machine learning (ML) and Artificial intelligence (AI) have the potential to revolutionize the renewable energy sector, and power companies may use them to improve forecasting, grid management, and maintenance scheduling. Clients can also enjoy constant green energy and receive advance notice about grid maintenance work that may result in power disruptions.

In the next 10-15 years, the adoption of electric vehicles and the electrification of heating systems will pose challenges to energy grids all around the world. Other sources of energy will begin to produce energy via solar panels, be able to store it in batteries and send it back to the grid, reducing reliance on a dominant utility to generate and transmit electricity. Millions of individual gadgets uploading and downloading electricity could put a strain on the electric system.


The use of artificial intelligence in grid management

Decentralized energy sources can employ AI and machine learning to estimate household energy usage by comparing data from a certain time of year to previous years. They can then be able to send the surplus power they generate to the grid, where it will be directed to where it is required by power companies. The information also aids utilities in staying informed about the amount of energy they will demand in the next few days and managing their systems to avoid outages.

In an article at the World Economic Forum, Emmanuel Lagarrigue, who is an ex-chief innovation officer at the Schneider Electric firm, wrote, “If you take some time and think of the distributed energy resources as individual performers, a provider is a conductor maintaining the orchestra in harmony as AI composes the symphony in real-time.”

Allowing AI to be used in grid management will need a change away from the infrastructure-heavy legacy models and toward a more resilient and flexible grid. These assets must also ensure that client data, privacy, and cybersecurity are all protected at all times.

Policymakers will have to shift their attention to renewable energy production and incentivize distributed energy generation in households and businesses. Experts say that global AI software governance is essential to assure interoperability, transparency, and equal access to energy.


The use of artificial intelligence in predicting

One of the key issues for renewable power is the volatility as it is reliant on factors like sunshine, airflow, and water. AI aids in addressing this difficulty by forecasting the weather. To forecast weather conditions, machine learning technology can be used to analyze current weather as well as historical data. This forecast data is used by utilities to better manage their energy systems.

“They plan for the issue and rely on fossil fuels to maintain the electricity supply running,” Hadi Ganjineh, Super Energy Corporation’s head of Information Technology, integrated technology, and innovation, wrote in Forbes. If the data indicates that the weather will be good, power providers will store the renewable energy produced and control the load if the prediction is adverse.



To manage power grids efficiently, utilities can utilize AI and machine learning to forecast which areas of the system require maintenance and to notify customers about grid maintenance. Consumers will be advised of the scheduled power outages in this manner.

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