The Role of AI in Renewable Energy: Complete Guide

By: | September 8th, 2023

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.

Rana el Kaliouby, a pioneer in AI, said, “AI is taking on many new roles in society — becoming our coworkers, serving as virtual assistants in our homes, operating our cars, and more.”

Undoubtedly, from the power of AI, the renewable energy sector has witnessed substantial growth over the years. The technology helps the industry make better projections, reduce expenses, and improve ROI. There are many applications of AI in renewable energy that efficiently manage the sector and reduce forecasting challenges.

So, if you operate in the renewable energy sector, you can greatly benefit by harnessing the power of AI. But how precisely? Let’s discover it in the sections below.

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.

Grid Management

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. 

Maintenance 

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 maintenance so that they can be prepared for power outages ahead of time. 

Weather Forecasting

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.

Cybersecurity

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

Xcel Energy, one of the largest energy providers, deploys AI 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

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 in a unique way, 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.

General Electric

General Electric, a leading renewable energy company, has built many parts of the current energy infrastructure, from hydro generators to giant wind turbines. The company has developed Predix, a software that uses AI capabilities to generate predictions on machine health.

The software collects data from different sensors and performs in-depth analysis to detect potential faults in the machine before it breaks down, helping General Electric build a sustainable grid of renewable energy.

Future of AI in Renewable Energy 

With the ever-increasing complexity and applications of AI in renewable energy, the sector is transforming rapidly and will be revoltionized in more remarkable ways over the years. The technology can help analyze vast amounts of data, observe patterns, and benefit the business from accurate predictions.

Accordingly, AI in renewable energy can help improve energy production, conversion, and even delivery. Also, it can significantly improve the productivity of systems by automation, and its dominance is estimated to get more prevalent in the coming decade.

Final Thoughts

In this technology-driven world, AI is at the forefront of driving innovation and automation in the modern business world. It is why several renewable energy companies are increasingly partnering with AI app development companies to build emerging solutions that can help them drive more businesses. 

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