AI and energy have always been interconnected to each other. In fact, many experts believe that AI will end up revolutionizing the energy sector in the near future. It is expected to do so by expediting the adoption of renewables in a bid to overcome energy’s uncertain and variable nature. One doesn’t need to look far into the past to learn how inefficient our current electricity infrastructure truly is.

Owing to freezing temperatures last February, almost the entirety of Texas came to a stand-still. Power outages crippled life in the state. AI can be the necessary element that finally prevents such inconveniences from ever arising again. Suffice to say, AI in Energy Industry has a significant role to play.

Designing AI That’s Fit for Purpose

A core principle of AI is that design should be fit for its purpose. Fortunately, when it comes to AI in energy management, there are already strides being made that can considerably enhance the current conditions and effectiveness of the energy sector. AI in Energy Industry today can facilitate faster integration of renewable energy sources. Machine Learning algorithms, for instance, leverage large data sets to identify patterns and make predictions.

As such, energy companies today can forecast demand with increased accuracy. Energy industries can also forecast weather conditions with the help of self-learning weather modules, thus significantly reducing the cost of generating renewable energy.

The continuing advancements in Machine Learning can also help energy companies accomplish complete autonomy over energy systems, especially over power grids, which are arguably the most sophisticated mechanized systems in the world.

Predicting Maintenance For Infrastructure

Aside from forecasting energy demand and weather conditions, another area where AI truly excels is in its ability to predict maintenance for Infrastructure. Defective and inefficient infrastructure is said to cost the energy industry around $50 billion dollars in revenue losses every year. The use of smart-scheduling technology for frequent check-ups of critical renewable infrastructure can help mitigate those losses.

The implementation of ‘Computer Vision’ solutions can also help improve the long-term performance of energy infrastructure. Such solutions can predict and virtually identify defects in a cost-effective and time-efficient manner. AI solutions like ‘Computer Vision’ can act as the perfect alternative to manual inspection procedures.

Uses of AI in The Energy Sector

The Energy Sector can reach new heights of success by learning how to efficiently use Artificial Intelligence to the best of its capabilities. Let’s understand the role played by AI in energy management.

  1. Digitization of Data
    With the world rapidly embracing digitization, the energy sector can no longer afford to lag behind. AI can help the industry store, process, and manage data in a manner that is cost-effective and saves time. This can make energy companies more productive and better equipped to accomplish their goals.
  2. Forecasting
    Predictive analytics is a major task being accomplished by AI for the energy industry. With the help of advanced deep learning and machine learning, energy companies can predict system overloads, energy demands, and possible power failures. This can help companies be ready for changing conditions and better equipped to save power and cut costs.
  3. Facilitating Energy Storage
    Energy storage is in itself a complicated issue. Storing renewable energy, on the other hand, can be even more problematic as the production of such kinds of energy is often chaotic. Integrating renewable energy with AI can alleviate this problem, thus facilitating seamless energy storage management alongside increased business value and minimized power losses.
  4. Failure Prediction and Prevention
    You have to understand that Energy is a powerful resource that needs to be handled with the utmost care. Failure to do so can have disastrous consequences. As AI can be used to predict system overloads and warn operators of a possible transformer breakdown beforehand, it can prevent massive disasters from ever occurring.