Artificial intelligence (AI) is one of the most considerable technologies, playing diverse roles to elevate our personal and professional lives. Accordingly, modern enterprises across industries are constantly looking for proven strategies to leverage AI in their operations to automate processes, and the renewable energy sector is no exception.
Use Cases of AI in the Renewable Energy Sector
Well, we all know that renewable energy like wind, solar, and hydro are the need of the time. But how can AI help improve renewable energy supply? Let’s discover it. Here are a few proven methods AI can revolutionize the energy industry.
AI can play a significant role in grid energy management. The renewable energy grid can be interconnected with AI-powered devices to gather a vast amount of data. This data provides grid operators with deep insights to better control the operation and adjust the supply with demand. The same is applied to industrial energy management, which is again done by evaluating the vast amount of historical data. Therefore, AI can help manage the grid power requirements.
One of the most significant applications of artificial intelligence in the renewable energy sector is that it empowers companies to maintain their power plants. The technology helps organizations identify when is the best time to put their resources into maintenance and when they will consume the most minor energy consumption. Also, it allows energy organizations to notify their customers about scheduled care so that they can be prepared for power outages ahead of time.
Renewable energy is highly unpredictable as it depends on natural sources like sunlight, wind, and water. These sources are completely weather-dependent. Therefore, a prior predictive analysis is essential to gain the maximum output. For instance, if the weather is favorable to energy companies, they can produce more energy and use it later in abnormal weather conditions. All this can be done using predictive AI to analyze historical data and patterns.
Energy grids are prone to cyberattacks as hackers can easily hack the data servers and steal sensitive information. By leveraging the power of AI and machine learning, energy companies can make their data servers more secure. These technologies help the security personnel identify potential threats and take proactive measures to prevent them beforehand.
Improved Integration of Microgrids
While the biggest role of AI in renewable energy is to manage intermittency, it also helps manage microgrids and distributed energy. When community-level renewable energy sources are integrated into the main grid, it becomes challenging to balance the energy flow within the grid. Here, an AI-powered control system can play a vital role in resolving issues related to energy quality and grid congestion.
These are just a few of the many methods AI can help renewable energy companies improve their operations.
Real-World Examples of Companies Using AI in Renewable Energy
As described above, artificial intelligence has immense potential to revolutionize the renewable energy sector. As a result, many organizations are adopting this emerging tech trend and partnering with an AI app development company to build revolutionary solutions. Here are some real-world examples of renewable energy companies that leverage AI to drive more businesses.
Xcel Energy, one of the largest energy providers, deploys AI with the assistance of top AI developers, in Colorado to address weather forecasting challenges. The company uses AI-based data mining methods to generate highly accurate and detailed weather reports. With such precise predictions, Xcel can take greater precautions in preserving energy.
The company collects data for weather forecasting from local satellites, wind farms, and weather stations to perform the analysis and identify data patterns to make predictions.
PowerScout, an Oakland, California–based renewable energy company, harnesses the potential of AI and ML to drive more business. The company uses AI to manage solar energy uniquely, demonstrating potential savings on power costs and customer acquisition.
The AI platform of PowerScout collects industry data from over 100 billion data points, which are interconnected to 45 million households. This data helps predict whether a household will be investing in solar energy or not. It also helps solar installers focus their marketing efforts on the right sources, such as the most feasible buyers, which eventually increases their chances of revenue.
Numerous components of the present energy infrastructure, including massive wind turbines and hydro generators, were constructed by General Electric, a significant provider of renewable energy. The business created Predix, a program that forecasts machine health using AI capabilities.
The program helps General Electric create a sustainable renewable energy system by gathering data from various sensors and conducting in-depth analysis to find any machine issues before they break down.
Future of AI in Renewable Energy
Because of the increasing complexity and applications of artificial intelligence, the renewable energy sector is undergoing a rapid transition and will continue to be revolutionized in more astounding ways in the future. Thanks to technology, large data sets can be processed, trends can be identified, and the company may benefit from accurate forecasts.
AI in renewable energy can therefore improve energy generation, conversion, and transportation. Furthermore, automation has the potential to significantly boost system productivity, and its dominance is expected to grow over the next ten years.
Modern corporate automation and innovation are being driven by artificial intelligence (AI) in today’s highly technologically advanced world. Because of this, an increasing number of renewable energy companies are working with a leading AI app development company to build innovative solutions that will help them reach a wider audience.