Artificial intelligence and machine learning can help the renewable energy industry control the increasing demand for reliable, clean, and cost-efficient energy.
FREMONT, CA: Currently, humanity is facing one of its biggest threats, and it is the climate change. It has become important for the government and energy solution providers to offer a sustainable model of renewable energy various challenges for climate change. It has also made renewable energy one of the best alternative energy sources than fossil fuel because it is much safer and cleaner than the traditional sources.
Technology solutions like artificial intelligence (AI) and machine learning (ML) have become necessary because the industry is continuously searching for ways to supply energy to the increasing demand for clean, reliable, and cost-efficient energy. The innovative technologies can analyze the past, optimize the present, and even predict the future. AI and ML have the ability to solve the maximum of the difficulties related to energy.
Today, technologies are also making immense advancement due to which the renewable energy sector has also successfully progressed in the last few years. The electric grid can be one of the most complicated machines in renewable energy. The presently available grids have to deal with various challenges in cooperating with the diversity of renewable energy due to the critical variability of solar and wind. It has become necessary to have smart systems, expanding the renewables’ integration in the current grids and renewable energy. Here are some ways through which AI can enhance renewable energy sources.
Smart and Centralized Control Centers
Most of the time, the devices and sensors of a grid are interconnected to gather vast amounts of data. When AI is installed into the system, the data can provide new information to the grid operators. The technology will also offer flexibility to the energy suppliers to adjust the supply with demand. The innovative load control systems can also be connected with equipment like large AC units or industrial furnaces that can automatically turn off when the power supply is less.
Improved Integration of Microgrids
The method of managing distributed energy goes through an extensive acceptance of microgrids. AI-based control optimization can solve the issues related to bottlenecks and power quality. Intelligent algorithms can even offer real-time control over the grid’s dynamic nature below the substation autonomous controls. The algorithms available for AI can even enhance system optimization when new devices and new generation sources are implemented.