It is better late than never to implement it. Suppose you are running a renewable energy-based power company and still not harnessing the power of AI and ML. In the near future, AI is expected to benefit the renewable energy industry in many more ways. For consumers, the impact will be in the form of interrupted green energy, as well as upfront updates about scheduled maintenance in the grid. Power companies will have a tool for better forecasting, management of grids and, most importantly, scheduling maintenance. In the upcoming years, these technologies are going to impact both power companies and consumers. We are already seeing the differences it has made. What we witness currently is power cuts without any early announcements.ĪI and machine learning have the potential to reshape the renewable energy industry completely. Scheduled maintenance means consumers can be aware of the forthcoming power cuts. When power companies are updated with upcoming maintenance work, they can notify consumers about maintenance in the grid. By leveraging the power of AI and machine learning, the specific part of the system that needs maintenance can be easily predicted. It is crucial to run the entire system efficiently. No matter how well power grids are managed, there are times when they need maintenance. Alternatively, in some parts of the year, when energy consumption is low, they can lower the production to avoid wastage. If the consumption is going to be high, they can ramp up energy production. Based on that, they can manage their grids without any outage. This helps power companies stay informed about how much energy will be required in the upcoming days.
The prediction is based on the specific part of a year and also considers previous years’ data. These technologies use data analytics to predict energy consumption in households. Artificial intelligence and machine learning are playing a pivotal role in this area as well. They plan for the problem and utilize the help of fossil fuels to keep the power supply uninterrupted.Īnother critical aspect of a renewable energy system is grid management. If the forecast is terrible, power companies manage their load based on that. If there is a good forecast, the companies produce renewable energy and store it. The power companies use that forecast data to manage the energy systems. With the use of machine learning, it analyzes the current weather and historical weather data to provide accurate forecasting.
Artificial intelligence has helped in overcoming this challenge because it is a reliable tool for forecasting the weather. All of these resources are tied up with the weather, which is something humans can’t control. Renewable energy is primarily dependent on resources like sunlight, airflow and water.
Undoubtedly, renewable energy will be the future, but one major challenge associated with it is unpredictability. Let’s see how AI and ML technologies are transforming future energy. Machine learning is an application of AI that gives machines the capability to improve, acquire knowledge and learn from experience via specific algorithms from data over time. Over the next couple of decades, as big data continues to expand and grow, the need for learning from those data to maximize the performance of the machine and predict the likelihood of a future outcome increased and shaped ML into what we know and love today, such as Netflix’s recommendation engine or self-driving cars. Machine learning is a new subset of AI that was coined in 1959 by Arthur Samuel, a computer scientist at IBM. In simple terms, artificial intelligence imitates human roles and allows the system to perform tasks in a nearly human-like way and mimic human intelligence.