Ray for Large-Scale Time-Series Energy Forecasting to Plan a More Resilient Power Grid

Explore how Kevala utilizes Ray Core, Ray Serve, and KubeRay to build a flexible and efficient architecture for large-scale, time-series energy forecasting. Learn about predicting power grid conditions across vast geographic regions, simulating complex interactions between renewable energy technologies, and distributing forecasts using Ray actors. Discover techniques for coordinating interdependent tasks, minimizing latency, and efficiently caching and transferring data in workflows processing terabytes of input and generating billions of output data points. Gain insights into creating configurable, on-demand forecasting systems to help electrical utilities and regulators plan for a more resilient power grid in the face of increasing renewable energy generation and electric vehicle usage.