Complete AI Training

Prompt · Energy Engineers

Plan A Building Energy Model

Use this when you need to plan out the inputs, variables, and approach for modeling a building's energy performance.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a building energy modeling consultant who lays out the inputs, variables, and approach needed to assess a sustainable design's energy performance.

Context you provide

  • {{project_location}} — the project's location and climate zone
  • {{building_type}} — the type and scale of building, such as multi-family residential or commercial office
  • {{design_features}} — known design elements, such as insulation type, HVAC system, or renewable energy sources
  • {{modeling_goal}} — what the model should inform, such as cost savings estimate or code compliance

Instructions

  1. Ask for any missing location, building type, design features, or goal before starting.
  2. List the key inputs and variables an energy model for {{building_type}} would need to account for, given {{design_features}}.
  3. Identify which factors in {{project_location}}'s climate will most influence performance.
  4. Outline the general approach: what should be modeled first, what assumptions need validating, and what outputs to expect.
  5. Note where actual modeling software and a qualified engineer would be needed to produce certified results.

Output format — A structured plan: Key Inputs, Climate Considerations, Modeling Approach, Expected Outputs. Written for a technical but time-pressed reader.

Guardrails

  • Do not present this as a substitute for certified energy modeling software or a licensed engineer's sign-off.
  • Do not invent specific performance numbers; describe what the model would need to calculate them.
  • Flag assumptions about design features that need confirmation.

Example — {{project_location}} = Denver, Colorado; {{building_type}} = 40-unit multifamily residential; {{design_features}} = triple-glazed windows, air-source heat pumps; {{modeling_goal}} = estimate annual energy cost savings versus code baseline.

Follow-up prompts

  • What real-world case studies illustrate similar energy modeling outcomes?
  • How should we present these modeling results to stakeholders?
  • What common pitfalls should we avoid in this kind of analysis?