Clean Energy · GH2 Economics · Scenario Optimization · Decision Intelligence
The existing GH2 Excel model was deeply complex. Non-technical users could not interact with it to run scenarios.
Teams could not test what-if configurations across Solar, Wind, BESS, and Electrolyzer sizing simultaneously.
No interactive output — IRR curves, dispatch profiles, and sensitivity dashboards were inaccessible to client-facing teams.
Every scenario change required spreadsheet expert involvement — blocking real-time advisory engagement.
Wrapped the existing Python/GH2 model into a clean, user-accessible front-end — preserving all optimization logic.
Enabled users to configure Solar, Wind, BESS, and Electrolyzer parameters and run optimization in real time.
Built IRR vs. Tariff curves, Dispatch Plots, Sensitivity Dashboards, Capacity Mix Charts, and Cash Flow breakdowns.
Positioned advisory teams to deliver live scenario demonstrations directly within client workshops.
Key decision variables optimized simultaneously.
Prototype delivery timeline end to end.
Renewable energy tender types scoped.
Scenario evaluation time compressed.