AI is Making Waves in Energy Storage and Production


According to the Center for Climate and Energy Solutions, renewables made up almost 20% of electricity generation in 2020, with hydro and wind making up the majority. That’s expected to rise to 35% by 2030. And with a fifth of the world’s largest companies prioritizing net-zero, we must work to find new, sustainable energy sources. However, with that comes the challenge of finding ways to store energy efficiently. And as artificial intelligence (AI) continues to evolve, it’s becoming increasingly clear that AI can play a critical role in production and storage. This blog post will explore how AI is being used in the energy industry and discuss its potential for the future.

What is energy storage?

Energy storage can include systems for providing power or cooling for a local community, aggregating solar power, and providing cold storage for generating reliable electric power. Some storage systems are stand-alone, while others are integrated with a distributed energy resource. Because solar generation varies throughout the day, storage systems can take power on and off as needed to avoid significant grid outages. Furthermore, an aggregated system can serve a community and deliver energy to several homes at different times throughout the day.

Energy storage technologies

Various short-term and long-term energy storage technologies allow us to save energy in ample quantities over different periods. Since discovering electricity, we have sought effective methods to store that energy on demand. As technology advances and energy demands change, the energy storage industry has continued to evolve, adapt, and innovate. Energy storage systems provide a range of technological approaches to managing our power supply. The goal is to create a more resilient energy infrastructure and save on costs for utilities and consumers alike.

Here are some of the diverse ways energy is currently stored: 

  • Batteries – a range of electrochemical storage solutions, including advanced chemistry batteries, flow batteries, and capacitors
  • Thermal – capturing heat and cold to create energy on-demand or offset energy needs
  • Mechanical Storage – other innovative technologies to harness kinetic or gravitational energy to store electricity
  • Hydrogen – excess electricity generation can be converted into hydrogen via electrolysis and stored
  • Pumped Hydropower – creating large-scale reservoirs of energy with water
  • Flywheels – an electric motor is used to spin up a wheel or rotor to store energy. The energy is then discharged by an electric generator, thus spinning down the flywheel
  • Compressed air energy storage – compressed air is used to create a potent energy reserve.

These technologies are highly advanced machines that hold and release energy, but they can’t:

  • Optimize their operations by controlling when they are charged and discharged depending on the electricity price
  • Control how and when they are charged every day to achieve a longer cycle life
  • Coordinate their operations with other energy storage solutions, power generation capacities, and consumers 
  • Predict when a failure will occur and act before it happens 

How AI transforms energy production and storage

The rise of AI has made it possible to automate vast production and storage areas in the energy industry. Grids use AI to work smarter and faster, collecting data from smart meters, business records, weather forecasts, etc. Machine learning algorithms can then process this information and optimize grid performance for greater efficiency. AI brings with it many benefits for producers too. For example, AI can optimize plant design for maximum efficiency and output. It can boost the performance of new renewable energy sources like solar panels or wind turbines, reducing maintenance needs with predictive analytics. Power systems can also use AI to predict faults before they occur.


How AI takes effect 

A significant amount of readily accessible, well-structured, and accurate data exists in the energy sector, making it ideal for various AI applications. We feed this data into an AI system to deliver results that greatly benefit energy storage solutions. 

Demand and generation forecasting: AI forecasts electricity generation and demand and the price at a particular point in time by considering various data sources, such as years of historical electricity and weather data. Accurate forecasts support the safe and reliable operation of the grid by balancing electricity supply and demand. Forecasting also substantially improves the operational efficiency of energy storage solutions. 

Wind and solar forecasts: Wind and solar forecasts are vital in reducing the uncertainty associated with renewable energy generation; scheduled energy delivery is more valuable to the grid than standard, non-time-based delivery. Using that energy can be difficult because energy production and storage capabilities constantly change daily. AI utilizes weather and satellite data to develop renewable energy forecasts, plus modeling and statistical analysis. Many energy storage solutions are deployed to offset wind power and solar generation uncertainty, so accurate predictions are crucial. 

Predictive maintenance: AI detects anomalies across an array of electrical, electro-mechanical, chemical, and thermal subsystems before they cause any damage to the system, enabling the operator to act in time. It does so by gathering data from the environment and different sensors. This data is used to train powerful machine learning models capable of detecting the conditions that typically lead to the failure of a particular component. Predictive maintenance reduces downtime, improves the operational life of a storage system, prevents damage, and increases profits for the operator.

The future of energy

Companies in the energy industry use AI to process and analyze data more quickly and with less human intervention. This means they can react to new developments (such as sudden power outages) much faster than before. These new developments mean savings for the production side of the industry and increased safety for consumers.

As AI is embedded into electricity grids worldwide, it will anticipate any potential problems and make sure they don’t happen (by automatically shutting down a power grid, for example). Artificial intelligence is already transforming smart grids to become truly intelligent, enabling them to meet the energy demands of the future. As energy storage becomes more and more integral to the smart grid, AI will revolutionize our understanding of consumption patterns, allowing power grid operators to operate their assets better to drive revenue.

AI is a disruptive technology that has the potential to radically change the way we live, work, and interact. The energy industry will be no exception to this trend. AI has the potential to transform the way we produce and store energy in various ways. The future of energy may look very different from what we have come to know so far. But one thing is sure: AI will play a significant role in shaping that future.

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