Estimating Home Battery ROI using M365 Copilot Researcher Agent

Disclaimer: All data and numbers presented in this prompt are entirely fictitious and used solely for illustrative purposes. Any resemblance to actual persons, organizations, or events is purely coincidental. The content is intended to demonstrate functionality or provide examples and should not be interpreted as real or factual information.

WHY did I create this prompt?

Using my previous prompt (7) Home battery Research | LinkedIn I finally selected a particular battery brand and size (which is a story in itself ;-) ). Now I wanted to get a better feeling about the potential return on investment as far as this is possible given all the variables at play. Given my earlier great experiences with M365 Copilot I now decided to give it a go again with M365 Copilot Researcher Agent.

HOW did I create this prompt?

I've started with the prompt I published earlier but then put in the specific battery, battery size and cost (including installation cost). I not only added the Local weather data, Dynamic historic pricing information, Charging sessions, Power usage (P1 data) and my current fixed electricity tariffs but now also added

• my solar production data

• technical details about the specific battery

• net metering policy changes in the coming year

Then I asked M365 Copilot to improve my prompt (with some iterations) and landed on the final prompt . Example input files: https://www.linkedin.com/smart-links/AQGwAOCNrwM8ZA

PROMPT START: You are an energy analyst. Build a comprehensive ROI model for a ZYC 15.36 kWh battery system based on my energy usage and environmental data. The battery purchase and installation price is € 14301,- Use the following files:

• EV charging data: "ev chargepoint session data.csv"

• Dynamic electricity pricing: "dynamic pricing file.csv" (add 21% VAT to all prices)

• Local temperature data: "local weather data.csv"

• Historical energy usage: "P1 Data.csv"

• Solar production: "solar power.csv"

Financial Modeling Requirements:

• Compare two scenarios: With dynamic electricity pricing Without dynamic electricity pricing (fixed price: €0.229585/kWh incl. VAT)

Account for:

• Battery degradation assumptions: 2% per year

• Battery Maximum Continuous Current 100A

• Battery Peak Current (5 Seconds) 200A

• Battery Efficiency (@ 0.5C) 95.0%

• Battery Life Cycles＞6,000

• Inflation rate: 2,5% per year

• Apply 100% net metering until 31 December 2026, starting 1 January 2027 apply 0% net metering

• Outdoor placement efficiency losses (based on temperature data), the selected battery ensures reliable performance, down to -10°C

• Annual grid delivery cost: €431

• Grid feed-in tariff after net metering: €0.123/kWh

• EV charging cost: €0.38/kWh

Environmental Factors:

• Model battery efficiency loss based on outdoor temperature.

• Specify number of days impacted by suboptimal temperatures.

Deliverables:

• Detailed financial model: ROI, payback period, net savings

• Sensitivity analysis: dynamic pricing, degradation, inflation

• Visualizations: ROI over time Energy flow diagram (solar → battery → EV/grid) Battery performance simulation

Output Format:

• Use tables for financial metrics

• Use charts for ROI and energy flow

• Provide a short executive summary with key insights

PROMPT END

WHY it was worth my time to invest in creating this prompt?

Executing this prompt in M365 Copilot Researcher Agent resulted in a great report (example report: https://www.linkedin.com/smart-links/AQErl7ONx1O_uQ ) provided me an estimation of the potential returns on investment and the value provided. This report I would never have been able to create myself and I wasn't able to find tools online that could do this either 😉 .