AI-Powered Energy Storage Technologies Will Be Key in Growing the Battery Market and Accelerating Renewable Energy Adoption
The energy storage market is hitting warp speed, fueled by technological breakthroughs and soaring demand for electric vehicles and renewable energy sources. In 2022, the global energy storage market size reached an astounding $14.9 billion and is projected to grow at a 15.8% CAGR from 2023 to 2033. What recent or coming developments in the world of energy storage technologies are experts saying will have the most impact in supporting this projected growth?
For starters, as energy storage technology charges ahead, industries and consumers alike can expect significant changes. One pivotal development is the surging demand for batteries to power electric vehicles, transforming the automotive landscape. In addition, energy storage systems, encompassing batteries, pumped-storage hydroelectricity, thermal energy storage, and flywheel energy storage, serve as crucial backup power sources in the commercial, industrial, and residential sectors. These systems not only facilitate the adoption of renewable energy but also drive the exponential growth of the electric vehicle market.
As energy storage solutions provide more fail-safes for the energy industry and become the foundation of power for interconnected and increasingly-smart EVs, they’re also becoming a test case for edge analytics, playing a role in providing enhanced data capture and insights into energy usage. David Miller, Vice President of Business Development at clean energy adoption and solutions company Gridmatic, believes that the integration of artificial intelligence in energy storage technologies is going to be one of the most exciting and useful developments for the market to continue to grow in size and importance.
David’s Thoughts
“The development in energy storage technology that we are most excited about is forecasting and optimization based on artificial intelligence or AI. Previously, many grid-scale storage projects were designed with a single application in mind, like providing frequency support to the grid or shaving the peak during certain hours of the day. Those applications did not require advanced controls, but storage projects today in the leading U.S. markets for storage, like CAISO and Ercot, bid into both energy and ancillary service markets in both the day ahead and real time.
To do this requires constantly managing trade-offs, which is complicated and beyond the capabilities of a human to operate these batteries. Effectively, algorithmic forecasting and optimization are required. Fortunately, advances in AI to energy price forecasting are making this more effective than ever. We expect these technologies to take off for energy storage, deployment, and to spread to other dispatchable resources like flexible loads and beyond.”
