Each year, global energy demands are growing. Eventually, fossil fuels won’t be able to fulfill modern energy needs. Today, carbon emissions from fossil fuels have already reached an all-time high because of increased energy consumption.
While this is true, renewable energy is emerging as a smart alternative to more traditional fossil fuels. It is cleaner and safer than conventional sources. Thanks to advancements in technology, the renewable energy sector has experienced more progress and growth in the past 10 years. Even though this is true, there are still several challenges in the sector that must be addressed.
Technologies such as machine learning and AI can analyze the past, optimize what’s going on now, and make predictions for the future. Also, AI in the renewable energy sector and things like the Con-Ed bill may solve many of the issues in the industry.
Challenges Faced in Renewable Energy
One of the biggest challenges related to creating renewable energy is how unpredictable the weather is. Wind and solar are the top sources of renewable energy today, but their ability to generate power depends on the weather.
While weather forecasting technology is impressive, sudden changes can occur, which will affect the flow of energy. Because of this, the supply chain of renewable energy sources is vulnerable to even slight changes. This means processes must be put in place to help ensure renewable energy suppliers can cope with these sudden or unexpected changes.
While innovations in energy storage are promising, they have yet to be thoroughly tested, which means there is no way to know if they provide long-term value.
As mentioned above, it’s predicted that the demand for renewable energy will continue to rise. This is why now is the time for renewable energy suppliers to invest in various emerging technologies, including IoT, AI, and machine learning. This is what will help solve the challenges mentioned above and improve productivity.
Even the biggest renewable energy consumers, such as railways, offices, factories, and grocery stores, can use AI technology to make data-driven decisions. Some specific ways AI will help the renewable energy sector can be found below.
Centralized, Smart Control Centers
The energy grid can be interconnected with sensors and devices to collect data. When this design is paired with AI, the data provide new insights to the grid operators, providing better control operations. It provides more flexibility to energy suppliers to help adjust the supply as needed.
Advanced load control systems are used with larger equipment, such as industrial AC units or furnaces. These will switch off when the supply of power is low. With intelligent storage units, they can also be adjusted based on the flow supply.
Advanced sensors and smart machines will make load predictions and weather predictions that can improve renewable energy efficiency and integration.
Microgrid Integration Improvements
AI will help with microgrid integration. It will also help with the management of distributed energy. When these are added to the main grid, it becomes harder to balance the energy flow. With an AI-powered control system, it is possible to solve the congestion and quality issues.