Watt’s Next? The AI Revolution Shaping The Future Of Energy

The topic of energy is rapidly becoming central to the conversation around AI. In that conversation, we’re primarily talking about how energy-hungry AI is, whether we’re using that energy to train complicated AI models or responding to the huge amount of demand for generating results and inferences from those trained models. On the other hand, another conversation is focused on how AI is helping power suppliers. AI is increasingly helping power suppliers with the generation, transmission, and consumption of energy..

How AI is Used to Help Optimize Energy Generation and Use

To satisfy the ever-increasing, energy-hungry demands of today, the energy industry needs to make sure they're producing and supplying energy as required for today’s needs as well as planning and managing capacity to deal with spikes in demand and increasing energy needs. This requires addressing both the generation side of energy as well as the storage, transmission, and consumption parts of the energy equation. This requires a smart balance to ensure that there isn’t a shortage of needed energy capacity, but also not excess energy generation that is wasted.

To solve these challenges, AI optimizes the operation of smart grids by predicting electricity demand, balancing supply, and detecting inefficiencies. AI algorithms help utilities manage the distribution of electricity more effectively, reducing energy waste and enhancing reliability. These intelligent systems can take into account existing and predicted demand, weather patterns, historical data, and many other variables.

With the increasing use of variable renewable energy sources such as solar and wind, these systems need to factor in many more variables than was previously the case with more steadily producing sources of power such as oil, coal, gas, and nuclear sources. AI systems are able to factor all these variables into the equation to manage and make the grid even smarter than before.

AI is being used to enhance grid stability by not only predicting and responding to all these fluctuations in energy supply and demand, but also helping to automatically adjust power distribution to prevent blackouts. AI is also helping with managing the integration of different intermittent renewable energy sources, managing storage of excess generated power, and helping to provide more resiliency and stability to the energy grid. AI systems can automatically adjust power distribution to prevent blackouts.

MORE FROMFORBES VETTED
70+ Early Black Friday Deals: Save Up To 50% On Beauty, Tech And More
By
Jordan Thomas
Forbes Staff
The 116 Best Black Friday Deals So Far, According To Our Editors
By
Kara Cuzzone
Forbes Staff

AI systems can also manage the integration of intermittent renewable energy sources. Additionally, AI optimizes the management of energy storage systems such as batteries, by predicting when to store or release energy based on demand forecasts and price signals. This maximizes the efficiency and profitability of energy storage, particularly in renewable energy applications. In addition, AI enables more intelligent distribution of energy by managing decentralized energy resources, such as rooftop solar panels and microgrids.

On the energy consumer side, AI is helping consumers and businesses optimize their energy consumption by analyzing usage patterns and suggesting ways to reduce energy usage. AI systems can analyze usage patterns and automatically adjust temperature controls or high energy usage systems, and further suggest ways to reduce energy usage.

AI systems learn habits and behaviors over time, and use that collected data to make adjustments over time. Furthermore, AI streamlines the process of conducting energy audits by analyzing data from buildings, factories, and other facilities. AI-powered tools can identify energy inefficiencies, recommend improvements, and calculate potential savings.

AI Keeps Energy Generation Humming

To keep energy generation consistent, AI is being used to monitor and predict the maintenance needs of energy infrastructure, such as power plants, wind turbines, and solar panels. By analyzing data from sensors, AI-powered predictive maintenance is helping identify equipment failures before they happen, reducing downtime and maintenance costs.

AI systems can look at a wide range of energy product data to make predictions and forecast when equipment failures may happen or when parts are going to need to be replaced or repaired.

Likewise, AI is helping energy companies stay compliant with energy regulations and keep energy generation as environmentally friendly as possible. AI is providing additional analytic insights to utility companies and governments to monitor carbon emissions by analyzing energy usage, and modeling the impact of different strategies on emissions and track progress toward sustainability goals.

In addition to being a vital resource, energy is also a financially traded commodity. Energy prices are set by market demand and supply, with the cost of energy fluctuating on a minute-by-minute basis. AI is used for energy trading to analyze market trends, forecast prices, and optimize trading strategies.

Sophisticated algorithms can process vast amounts of data to identify trading opportunities and reduce risks. Energy companies and financial institutions use AI to enhance their trading operations.

So while AI is getting an increasingly bad rap in terms of its impact on energy consumption, AI is also helping to be part of the solution, providing tools to help improve efficiency and lessen the burden for energy generation, transmission, consumption, and storage.