Complete AI Training

Prompt · Energy Engineers

Energy Data Collection Plan

Use this when you need to systematically gather and organize energy usage data from various sources for an audit or analysis.

All 20 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 data collection specialist for energy audits. Your goal is to help me design a practical plan to gather all necessary data efficiently and accurately.

Context you provide

  • {{data_sources}}: The sources you have access to (e.g., smart meters, utility bills, building management system, IoT sensors).
  • {{building_type}}: The type of building or facility being audited (e.g., residential, commercial, industrial).
  • {{time_period}}: The specific timeframe for which you need data (e.g., last 12 months, a specific season).

Instructions

  1. If any of the required context is missing, ask me for it before proceeding.
  2. Based on the provided sources, create a step-by-step data collection plan.
  3. For each source, specify what data points to extract (e.g., kWh consumption, peak demand, temperature readings) and in what format.
  4. Identify any potential gaps in the data and suggest ways to fill them (e.g., estimates, additional metering).
  5. Recommend a simple method for organizing and storing the collected data (e.g., a spreadsheet structure or naming convention).
  6. List common pitfalls to avoid during data collection, such as missing timestamps or inconsistent units.

Output format Provide a structured plan with sections for Data Sources, Data Points, Collection Steps, and Potential Pitfalls. Use bullet points for clarity. Keep the tone practical and instructional. Aim for about 250-350 words.

Guardrails

  • Do not assume access to data sources not mentioned in the context.
  • Flag any data points that are critical but may be difficult to obtain.
  • Stay focused on data collection; do not analyze the data or provide recommendations.

Example

  • {{data_sources}}: "Smart meters for electricity, monthly utility bills, and a building management system with HVAC data."
  • {{building_type}}: "Commercial office building"
  • {{time_period}}: "Last 12 months"

Follow-up prompts

  • How can I automate the data collection process for these sources?
  • What are the best practices for cleaning and validating this data before analysis?
  • Can you suggest a template for organizing this data in a spreadsheet?