computing

As artificial intelligence (AI) usage and sophistication grows, questions about the sustainability of the traditional model of utilizing huge, centralized data centers are frequently raised. Hyperscale data centers handle most AI workloads today, but they come with high energy demands and environmental costs.

The speed of decision-making at the grid edge has become critical for maintaining stability, preventing cascading failures, optimizing efficiency and integrating intermittent renewable resources. With the proliferation of distributed energy resources (DERs), electric vehicles and smart loads, grid edge intelligence has moved from a luxury to a necessity.

The terms “cloud” and “edge” are used frequently by tech-savvy power industry professionals, but what do they mean and how are they changing plant operations? To get an insider’s perspective, POWER posed the question to Akshay Patwal, strategic business manager with Siemens Energy. Patwal leads the development and commercialization of digital business transformation projects, using […]