How Artificial Intelligence And Machine Learning Are Transforming The Future Of Renewable Energy
We use energy in many different ways in our lives, be it for lighting up our houses, running electronic appliances or as fuel in our vehicles. There are mainly two types of energy: renewable energy and non-renewable energy. Non-renewable energy includes fossil fuels like natural gas, petroleum and coal. However, these energy sources come from nature itself; it is impossible to renew them quickly. This means that these resources will become entirely exhausted in the upcoming years.
In addition, fossil fuels emit greenhouse gases that are responsible for global warming. According to the report published by the Global Carbon Project, carbon dioxide emissions reached an all-time high in 2018. On the other hand, renewable energy includes energy sources that are available in infinite quantities, such as sunlight, air and water. These resources are renewable and release very few harmful gases.
Artificial Intelligence And Machine Learning In The Renewable Energy Industry
You might be confused about the difference between artificial intelligence and machine learning. Let me shed light on these technologies before diving into their importance in the renewable energy industry. Artificial intelligence is the main branch of prediction-based technologies. It includes domains like machine learning, neural networks and data science.
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. Machine learning is a new subset of AI that was coined in 1959 by Arthur Samuel, a computer scientist at IBM. 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 an application of AI that gives machines the capability to improve, acquire knowledge and learn from experience via specific algorithms from data over time. Let’s see how AI and ML technologies are transforming future energy.
Undoubtedly, renewable energy will be the future, but one major challenge associated with it is unpredictability. Renewable energy is primarily dependent on resources like sunlight, airflow and water. All of these resources are tied up with the weather, which is something humans can’t control. Artificial intelligence has helped in overcoming this challenge because it is a reliable tool for forecasting the weather.
With the use of machine learning, it analyzes the current weather and historical weather data to provide accurate forecasting. The power companies use that forecast data to manage the energy systems. If there is a good forecast, the companies produce renewable energy and store it. If the forecast is terrible, power companies manage their load based on that. They plan for the problem and utilize the help of fossil fuels to keep the power supply uninterrupted.
Another critical aspect of a renewable energy system is grid management. Artificial intelligence and machine learning are playing a pivotal role in this area as well. These technologies use data analytics to predict energy consumption in households. The prediction is based on the specific part of a year and also considers previous years’ data.
This helps power companies stay informed about how much energy will be required in the upcoming days. Based on that, they can manage their grids without any outage. If the consumption is going to be high, they can ramp up energy production. Alternatively, in some parts of the year, when energy consumption is low, they can lower the production to avoid wastage.
No matter how well power grids are managed, there are times when they need maintenance. It is crucial to run the entire system efficiently. By leveraging the power of AI and machine learning, the specific part of the system that needs maintenance can be easily predicted.
When power companies are updated with upcoming maintenance work, they can notify consumers about maintenance in the grid. Scheduled maintenance means consumers can be aware of the forthcoming power cuts. What we witness currently is power cuts without any early announcements.
AI and machine learning have the potential to reshape the renewable energy industry completely. We are already seeing the differences it has made. In the upcoming years, these technologies are going to impact both power companies and consumers. Power companies will have a tool for better forecasting, management of grids and, most importantly, scheduling maintenance. For consumers, the impact will be in the form of interrupted green energy, as well as upfront updates about scheduled maintenance in the grid.
In the near future, AI is expected to benefit the renewable energy industry in many more ways. Suppose you are running a renewable energy-based power company and still not harnessing the power of AI and ML. It is better late than never to implement it. There are some platforms, including Microsoft Azure, Google Cloud, AWS, DeepMind and IBM Watson, that provide AI and ML solutions to the utilities industry. You can schedule a demonstration with one of these companies to see how you can integrate AI and ML with your current system to bring the most benefit and productivity to your company.
In the last decade, many developed countries globally have shifted their focus to producing renewable energy. Governments are planning to be dependent on green energy. It is nice to see the developments in the renewable energy industry. Still, the industry has its own set of challenges since we are dependent on getting energy from sources that are not in our control. Also, these resources are not available in the same amount in all different parts of the Earth.
With advancements in technologies, domains like AI and machine learning have come into existence. They have the capability of transforming the renewable energy industry. By leveraging the power of AI, power companies can get better forecasts, manage their grids and schedule maintenance. I will explain all of these use cases in a bit more detail below.
This article originally appeared on forbes.com, to read the full article, click here.
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