Artificial intelligence (AI) and machine learning (ML) are two of the most popular emerging technologies. Many industries benefit from them because they help improve and automate their core processes. One of the sectors that have benefited is the energy sector, which has gained a valuable asset in growth and management. Indeed, AI has already helped energy companies analyze large amounts of data. To analyze the massive data on energy consumption, etc., and derive insights, AI & ML algorithms enable us to convert the unstructured data to a structured format, store it, and then uncover correlations.
On the one hand, applying AI & ML to the energy sector is not a simple task and requires great exertion. On the other hand, the results are worth the effort since they enable us to analyze and manage the current and future cases in the most powerful way. Therefore, this upward trend in using these emerging technologies in the energy industries will accelerate. AI can be used in various ways to develop the energy sector. Here, a few of the most popular applications in development today will be given.
1- Forecasting: Renewable energy is undoubtedly the way of the future to reach the target of reducing air pollution and carbon emissions. However, it also risks unpredictability since it relies on natural resources such as sunlight, airflow, and water. These resources are linked to the weather, which is beyond human control. AI has helped resolve this problem because it could be used as a reliable tool for weather forecasting. It analyses current and historical weather data using machine learning to provide accurate forecasting. The power companies use the forecast data to manage the energy systems. Companies produce renewable energy and store it if the weather forecast is favorable. If the weather forecast is bad, power companies adjust their load accordingly. They prepare for the problem and rely on fossil fuels to keep the power supply running. The power of forecasting through AI has taken great attention and benefited renewable energy companies greatly over the years.
2- Grid management: One of the fascinating applications of AI in the energy sector is grid management. The electricity is transmitted to users through a complex network or, in other words, a power grid. The power grid is a complicated structure because the power generation and demand-supply must always be in equilibrium. Otherwise, system failures and blackouts may occur. When the system works with renewable energy, it is difficult to forecast the grid's electricity production capacity since it is affected by various factors such as wind and sunlight. Thanks to AI algorithms, measuring the voltage, current, and frequency at specific points on the grid in real-time is possible. They also enable us to reach the information about the required energy needed in the coming days by considering data from previous years. In this way, identifying these tracking data brings conveniences in communicating with the grid and altering electricity flow during off-peak times, lowering customer prices and easing grid load. Google recently used this AI technology to reduce the total amount of power consumed by its data centers, saving millions of dollars.
3- Predictive Maintenance: The specific parts of the energy systems that require maintenance can be easily predicted using AI & ML algorithms. In essence, sensors are installed on power lines, machinery, and stations to collect operational time series data. Machine learning algorithms can then predict whether a component will fail in a certain amount of time or steps. It can also forecast how long a piece of equipment will last or when the next failure will happen. These algorithms aim to predict machine failure accurately, avoid blackouts or downtimes, and optimize maintenance activities and frequency, lowering maintenance costs. Furthermore, when power companies are informed about upcoming maintenance, consumers could be notified about grid maintenance. Scheduled maintenance allows customers to be aware of impending power outages. Power outages are experienced with no prior notice in many places in Turkey. In this sense, it is important to implement AI techniques for predictive maintenance.
Additional to the applications of AI technology that are transforming the future energy, their comprehension could be enlarged by finding solutions to other curios subjects such as anomaly detection in energy consumption, accurately predicting energy prices, etc. The energy sector has a long way to go when it comes to artificial intelligence and machine learning since these technologies have the potential to completely transform the renewable energy industry and green economy. These technologies will impact both power companies and consumers in the coming years and benefit the management of the green energy industry in a variety of ways in the near future. Bill Gates expresses the first two areas he would focus on to make a significant impact in the world if he started life again: "One is artificial intelligence: We've only scratched the surface of how it can make people's lives more productive and creative. The second is energy, which must be made clean, affordable, and dependable to combat poverty and climate change." Imagine the beautiful world that can be created when these two important areas are worked together.