Challenge
Rejlers wanted its DI Energi audience at Sweden's largest annual energy industry conference to experience why the 2045 net-zero transition is a coordination problem, rather than hear another presentation about it.
My contribution
I designed and sole-built the Python economic engine, including stakeholder incentives, scoring, transition mechanics and information-visibility rules.
Approach
Modeled politicians, voters and workers, energy companies and industry as four stakeholder groups with distinct incentives, decision spaces, KPIs and private information.
Structured six turns from 2020 to 2045, with cross-actor dependencies that made isolated optimization insufficient and a win condition of net-zero without economic collapse.
Grounded the economic engine in Swedish energy data while simplifying selectively to strengthen the learning experience.
Outcome
First deployed at DI Energi, the simulation proved useful enough to be reused at other industry conferences and events for more than four years.
Deliverables
- Python simulation backend
- Economic and scoring model
- Stakeholder decision logic
- Information-visibility rules
