Impact of Artificial Intelligence on Renewable Energy

By Steve Carter, CPA, Audit Partner
ASL Renewable Energy Group

The focus on transitioning the nation’s energy needs from existing to renewable sources is the shared mission and passion of most renewable energy companies. The process of transforming natural resources into usable energy is a confluence of science, technology, and even user behavior. However, many challenges remain to achieving the objective. One issue which has been preventing broader adoption of this energy source is the inconsistency of weather. While technology allows for very accurate forecasting, it’s not always correct, and this can create “spikes” in the availability of energy. That’s why companies are turning to artificial intelligence (AI) to help facilitate solutions. AI can help with better micro-grid management, improved reliability, and optimized energy storage. To help clients, prospects and others understand the impact of AI, ASL has provided a summary of key solutions below.

AI Applications in Renewable Energy

  • Enhanced Energy Controls – As the availability of renewable energy increases, there will be a corresponding need to enhance the effectiveness of energy controls. The collection and review of computer and grid data will permit AI to identify trends and patterns providing operators with essential information on how to manage energy inconsistencies. The result will be a more easily managed energy supply.
  • Microgrid Integration – As more sources of renewable energy become available, the widespread integration of microgrids will be necessary to collect and distribute the energy. AI technologies such as Adaptative Dynamic Programming and multi-agent systems will be essential to providing real-time information about energy management and grid status. AI will also be important in helping to manage the integration of new renewable energy power sources as they come online.
  • Improved Safety & Reliability – While the primary focus of AI is on the collection, management and distribution of renewable energy, the secondary application of safety should not be overlooked. It can help identify energy consumption patterns, where leaks are occurring and the status of critical infrastructure. For example, AI analysis can be used to collect data from windmill turbines to monitor status and overall health, much like the monitors in late model automobiles alerting the owner when maintenance will be needed.

Renewable Energy – AI Companies

There are a number of companies leveraging AI into useful and transforming products:

  • Meteo-Logic – This AI company is focused on weather analytics and its impact on the market. They rely on machine learning and big data to create algorithms that predict the weather and how variations will impact energy supply. The products’ ability to expand and incorporate data from multiple collection points results in the ability to constantly approve results.
  • Ping Things – This company uses big data and AI to detect and predict when events may occur on the power grid. The tools collect data from internal and external sources and is able to predict when a failure may occur. This information permits operators to make real-time changes before outages or larger issues arise.
  • NNergix – This Spain based company uses AI and machine learning to make predictions about the level of renewable energy which will be available to the grid. The data provided allows utility companies to understand the energy upflow and its broader impact on the grid and energy demands.

Contact Us
It’s clear that AI offers many benefits to renewable energy companies and the value they bring to the marketplace. If you have questions about the information outlined above or need assistance with a renewable energy audit, tax or consulting issue, please contact Steve Carter, Audit Principal, at scarter@aslcpa.com or 408-377-8700 ext. 299 and visit our Renewable Energy Group page. We look forward to speaking with you soon!