When we flip the light switch in our homes, we have come to expect instant access to electricity. Behind the scenes, that reliability depends on utility operators who have developed control systems and fail-safes to keep the power flowing.
But times are changing rapidly, and utility operators face an evolving electrical grid that has become a complex network of diverse energy sources, emerging grid energy storage options, and accelerating demand for electricity in transportation, computing, and industrial uses.
Faced with the challenge of electric grid modernization, many have called for supporting utility managers and operators with artificial intelligence (AI) and machine-learning (ML) tools that can remove some of their decision-making burdens. Understandably, utilities are cautious in adopting new technologies when the consequences of failure are costly and could affect customers. Additionally, the benefits and business cases for these technologies are not yet clear.