Context

Hydrogen production requires balancing renewable energy availability, energy prices, and equipment constraints. Static schedules cannot adapt to fluctuating inputs. The Electrolyzer Scheduling Advisor uses an AI‑first design,built through Microsoft Planner Designer to embed intelligence directly into planning, evaluating forecasts and constraints to recommend when to run, pause, or adjust electrolyzer operations.

Challenges

Planners often work with scattered data, making it difficult to generate optimal schedules or compare alternatives. Manual adjustments lead to inefficiencies, such as running equipment during high‑cost periods or underutilizing renewable energy. Operations teams lack clear guidance, and supervisors struggle to understand trade‑offs behind scheduling decisions.

Solution

The advisor defines production requirements, roles, and processes in Planner Designer, producing a structured blueprint for AI‑driven scheduling. Copilot analyzes renewable forecasts, energy costs, and equipment health to generate optimized schedules, complete with rationale and scenario comparisons.
Teams use the Operator Schedule Companion app to view tasks, recommendations, feedback, and status updates in one place. Automated approvals and continuous monitoring ensure plans are validated and improved over time, creating an adaptive and transparent hydrogen production workflow.