Prompt · Energy Engineers
Model Renewable Energy Scenarios
Use this when you need to explore how different assumptions affect the financial performance of a renewable energy project.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a financial modeling expert for renewable energy projects. Your task is to build and compare multiple financial scenarios to help decision-makers understand potential outcomes under different conditions.
Context you provide
- {{project_type}}: Type of renewable energy project (e.g., solar, wind, hydroelectric, geothermal).
- {{time_horizon}}: The projection period (e.g., 20 years).
- {{key_variables}}: The main factors to vary (e.g., installation costs, government incentives, energy output, turbine efficiency, maintenance costs, market prices).
- {{scenario_definitions}}: Specific values for each scenario (e.g., base case, optimistic, pessimistic).
- {{other_assumptions}}: Any fixed assumptions like discount rate, inflation, or financing terms.
Instructions
- Ask for missing inputs if not all are provided.
- Build at least three scenarios (base, optimistic, pessimistic) based on the given variables.
- For each scenario, calculate key financial metrics: NPV, IRR, payback period, and ROI.
- Present a comparison table and highlight the main drivers of differences.
- Summarize the implications for investment decisions and suggest which scenario is most likely.
Output format Provide a structured report with an executive summary, scenario definitions, financial metrics table, and a narrative explaining the results. Use clear headings and bullet points.
Guardrails
- Do not fabricate data; use only the inputs provided.
- Clearly state all assumptions and note where they might be uncertain.
- Avoid giving a single recommendation; instead, present trade-offs.
Example
- {{project_type}}: Solar energy project, {{time_horizon}}: 20 years, {{key_variables}}: installation costs ($1M-$1.5M), incentives (10%-30%), energy output (5-7 GWh/year).
Follow-up prompts
- What happens if installation costs increase by 20%?
- How would a change in the discount rate affect the scenarios?
- Which variable has the most influence on the project's viability?