The global energy demands are growing every year, and fossil fuels won’t be able to fulfill our energy needs in the future. Carbon emissions from fossil fuels hit an all-time high in 2018 due to increased energy consumption.
On the other hand, renewable energy is emerging out as a reliable alternative to fossil fuels. It is much safer and cleaner than conventional sources. With the advancements in technology, the renewable energy sector has made significant progress in the last decade.
However, there are still a few challenges in this sector that can be addressed with the help of emerging technologies.
Artificial Intelligence (AI) and Machine Learning (ML) technologies can analyze the past, optimize the present, and predict the future. And, AI in the renewable energy sector can resolve most of the challenges.
Challenges of the Renewable Energy Sector
One of the significant challenges of producing renewable energy is the unpredictability of the weather.
Solar and wind are the leading sources of renewable energy, and the power generation largely depends on the weather.
Although with efficient technologies in place for weather forecasting, there are going to be sudden changes in the climate which can affect the energy flow. The supply chain of renewable energy is prone to such vulnerabilities. It needs to be smoothened enough to cope up with the unexpected changes.
Secondly, the recent developments in energy storage technology are quite promising, but they’re yet to be tested thoroughly.
The demand for renewable energy will only increase in the future. And, that’s why renewable energy companies need to invest in AI, IoT, and other emerging technologies to improve productivity and overcome the shortfalls.
Even the large consumers of renewable energy, like supermarkets, factories, offices, railways can use AI technology to make data-driven decisions.
How AI Technology Can Improve the Renewable Energy Sector
The electric grid is one of the complex machines on Earth, but it is evolving rapidly with the addition of variable renewable energy sources.
Due to the inherent variability of wind and solar, the current grid faces many challenges in accommodating the diversity of renewable energy.
The utility industry needs smart systems that can help improve the integration of renewables into the existing grid and make renewable energy an equal player in the energy supply.
Here’s how AI technology can improve the reliability of renewable energy and modernize the overall grid.
1. Smart, Centralized Control Centers
The energy grid can be interconnected with devices and sensors to collect a large amount of data.
When coupled with AI, this data can give new insights to the grid operators for better control operations. It offers flexibility to the energy suppliers to cleverly adjust the supply with demand.
The advanced load control systems can be installed with the equipment, such as industrial furnaces or large AC units, which can automatically switch off when the power supply is low. Intelligent storage units can also be adjusted based on the flow of supply.
Additionally, smart machines and advanced sensors can make weather and load predictions that can overall improve the integration and efficiency of renewable energy.
2. Improved Integration of Microgrids
AI can help with the integration of microgrids and managing distributed energy. When the community level renewable energy generation units are added to the primary grid, it becomes hard to balance the energy flow within the grid.
The AI-powered control system can play a vital role in solving the quality and congestion issues.
3. Improved Safety and Reliability
While the biggest goal of AI in renewable energy is to manage the intermittency, it can also offer improved safety, efficiency, and reliability.
It can help you understand the energy consumption patterns, identify the energy leakage and health of the devices.
For example, the AI-powered predictive analysis can collect the data from wind turbine sensors to monitor wear and tear. The system will monitor the overall health of the equipment and alert the operator when the maintenance is needed.
4. Expand the Market
The integration of AI can help renewable energy suppliers expand the marketplace by introducing new service models and encouraging higher participation.
The AI-powered systems will be able to analyze the data related to energy collection and provide insights on energy consumption.
This data would help suppliers optimize the existing services and launch new service models. It can also help retail suppliers to target new consumer markets.
5. Smart Grid with Intelligent Storage
Integration of artificial intelligence with Intelligent Energy Storage (IES) can provide a sustainable and reliable solution to the renewable energy industry.
This smart grid will be able to analyze a vast amount of data collected from several sensors and make timely decisions on energy allocation.
This will also help microgrids to efficiently manage the local energy needs while continuing the power exchange with the main grid.
Companies That Are Using AI to Improve Renewable Energy Operations
Artificial intelligence has the potential to revolutionize the renewable energy sector. Below are some of the renewable energy technology companies that are using AI to drive more business.
1. Xcel Energy
One of the largest energy providers, Xcel is deploying AI technology in Colorado to address the weather forecasting challenges. Xcel uses the AI-based data mining methods of the National Center for Atmospheric Research to generate detailed weather reports with high accuracy.
The AI system collects data from local satellites, weather stations, and wind farms to perform the analysis. The algorithms are designed to identify data patterns and make predictions.
With such highly accurate predictions, companies like Xcel can take greater precautions in harnessing and preserving energy.
2. General Electric
From giant wind turbines to hydro generators, General Electric has developed many parts of the current energy infrastructure. General Electric has built a software called Predix that uses the power of AI to make predictions on machine health.
Predix collects data from different sensors from the equipment and performs in-depth analysis to predict failure in the machine before it happens. The software has helped GE build a sustainable and reliable grid of renewable energy.
This Oakland, California–based startup uses AI and machine learning to improve consumer education and drive more business. PowerScout uses industry data and AI to demonstrate potential savings on power cost.
AI has helped the company reduce costs on customer acquisition. PowerScout’s AI platform gathers data from more than 100 billion data points that are connected to 45 million households.
It collects the data from several sources and predicts whether or not a given household will be investing in solar energy. It has also helped solar installers to focus their marketing efforts on the most likely buyers, thus improving the chances of revenue.
AI provides more power to human potential. Many renewable energy suppliers are investing in artificial intelligence to drive their business. AI can analyze a massive amount of data and offer helpful insights so that companies can make intelligent choices.
In the renewable energy sector, the primary goal of AI integrated systems is to minimize the forecasting challenges and efficiently integrate renewable energy into the central energy grid.
AI can also help renewable energy suppliers to design effective strategies and policies around current energy consumption and demands.
We, at Imaginovation, develop custom software applications for funded startups to fortune 500 companies. If you’re a renewable energy supplier that wants to harness the power of AI to drive more business, get in touch with us.