All case studies
Energy
Energy storage scheduling optimization
An optimization model that schedules charging and discharging to minimize cost under real operating constraints.
- Cost minimizing schedules
- Real operating constraints
- Market behavior simulation
The challenge
Storage assets were scheduled with simple rules that ignored price signals and demand profiles, leaving value on the table.
Our solution
We developed a Pyomo optimization model that captures operational constraints, demand profiles, and pricing signals to simulate realistic energy market behavior and produce optimal charge and discharge schedules.
The outcome
The model supports data driven scheduling decisions, lowering cost and improving overall system performance.
