Kennedy Kyalo
Economic Analysis of Investing in a Solar Battery Using NPV and IRR
View the Project on GitHub ken-warren/solar_battery-investment
Economic Analysis of Investment in a Solar Battery
Table of Contents
Overview
Households have electricity needs that can be met by purchasing electricity from a provider or generating it using solar panels. In this project, the user has installed solar panels on their roof, generating electricity from sunlight. Currently, the solar-generated electricity is used immediately in their house, reducing electricity costs. The user is considering purchasing a battery to store excess solar-generated electricity. The battery would discharge energy when solar power isn’t sufficient. We’ll analyze the potential savings in electricity costs from installing the battery, considering different scenarios of electricity price increases. Calculations will include extra electricity from the solar panel and battery combination, implied dollar savings, NPV, and IRR.
Data Source
The user provides their hourly data for 2020 including the following information:
- Date and Hour: Timestamps representing each hour of the year.
- Solar Electricity Generated (kWh): The amount of electricity generated by the solar panels during that hour.
- Electricity Used (kWh): The electricity consumed during the same hour.
Tools
- Jupyter notebook - for cleaning, analysis and documentation Guidance to installation
- Python. Install
The following Libraries will be essential;
import numpy_financial as npf # Financial calculations eg calculation of IRR
import pandas as pd # Data manipulation
import matplotlib.pyplot as plt # Data visualization
import seaborn as stl # Reading data (Excel)
If the above Libraries are not yet installed,you can follow the following steps:
- Open you CMD prompt
- Copy and paste each of the following lines:
pip install numpy_finacial, pandas, matplotlib.pyplot, seaborn
This will get your python environment ready for analysis.
Data Cleaning
This phase includes:
- Finding and dropping missing values
- Inspection of duplicates
- Deletion of negative values
- Inspection of outliers and correcting them.
Data Analysis
Battery Consideration
The user is considering purchasing a battery to store excess solar-generated electricity. The battery would discharge energy during hours when solar power isn’t sufficient. Electricity, including solar, battery-stored, and purchased, is measured in kilowatt hours (kWh). The specific battery under consideration costs $7,000, has a 20-year lifetime, and can store up to 12.5 kWh.
Electricity Pricing
Starting from 1 January 2022, the user pays $0.17 per kWh for electricity from their provider. According to a government report, electricity prices increase annually by 4%. However, the user believes that climate change will lead to faster price increases, estimating an additional 0.25% p.a.
Data and Analysis
The user has provided solar electricity generation and usage data for 2020 (hourly increments). Our analysis will focus on calculating the extra electricity generated by the solar panel and battery combination compared to using only solar panels. Additionally, we’ll estimate the implied dollar savings in electricity costs resulting from installing the battery.
Scenarios to Analyze
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Scenario 1: Assuming electricity prices increase as expected (4% p.a.).
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Scenario 2: Considering the user’s estimated price increases (starting at 4% p.a. and rising by 0.25% p.a.).
Calculations
We’ll perform the following calculations:
- Extra electricity (in kWh) from the solar panel + battery combination.
- Implied dollar savings resulting from battery installation.
- NPV (Net Present Value) of the battery investment using a discount rate of 6% p.a.
- IRR (Internal Rate of Return) for both scenarios. Remember, the IRR represents the discount rate where NPV equals the initial cost.💡
Results
- Data Cleaning
- There were no missing values in the provided data set.
- There were no duplicates in the rows of the data set.
- All the negative values were omitted to ensure no distortion in the analysis.
- There were extreme outliers in electricity usage since the maximum value (46000 KWh) is more than four times the mean (7.319 KWh) and median (0.621 KWh). To correct the outliers, the extreme values were replaced with the median of the variable. Using the IQR method, the outliers were plotted as shown below.
- Data Analysis
Hourly Average Solar Energy Generation and Electricity Usage
The table below shows the overall hourly calculations for the first 12 hours:
| Hour | Average Solar Usage (KWh) | Average Electricity Usage (KWh) | Electricity Needed (KWh) | Excess Solar (KWh) | Cumulative Battery Charge (KWh) | Electricity Consumption With Battery (KWh) | Savings ($) |
|---|---|---|---|---|---|---|---|
| 0 | 0.000 | 0.777 | 283.654 | 0.000 | 0.000 | 283.654 | 0.00 |
| 1 | 0.000 | 0.402 | 146.542 | 0.000 | 1.412 | 145.106 | 0.24 |
| 2 | 0.000 | 0.251 | 91.478 | 0.000 | 2.436 | 90.454 | 0.17 |
| 3 | 0.000 | 0.408 | 148.806 | 0.000 | 3.078 | 148.164 | 0.11 |
| 4 | 0.079 | 0.552 | 179.531 | 6.711 | 0.000 | 172.679 | 1.16 |
| 5 | 0.271 | 0.611 | 174.193 | 50.010 | 0.000 | 157.564 | 2.83 |
| 6 | 0.723 | 1.223 | 322.020 | 139.593 | 0.000 | 275.367 | 7.93 |
| 7 | 1.395 | 1.478 | 366.399 | 336.018 | 0.000 | 290.979 | 12.82 |
| 8 | 2.085 | 1.301 | 279.744 | 565.341 | 0.000 | 224.670 | 9.36 |
| 9 | 2.243 | 1.084 | 200.682 | 623.748 | 0.000 | 145.080 | 9.45 |
| 10 | 2.134 | 0.826 | 130.602 | 607.830 | 0.000 | 95.646 | 5.94 |
| 11 | 1.984 | 0.837 | 146.340 | 564.981 | 0.000 | 107.424 | 6.62 |
Inferences
- Hours 18-23 have high electricity needed compared to the other hours in 2020.
- Excess solar electricity is generated between 8-15 hours
- Hours 1 to 3 have high charge levels with hour 3 having the maximum charge level recorded in 2020 (3.078 kWh).
- Hour 17 to 23 recorded high amounts of electricity bought assuming the solar battery had already been installed.
- Hours 4 to 19 recorded significant savings with 7th hour of all days in 2020 having the maximum savings of $12.82. The annual savings for 2020 was $122.
Monthly Average Solar Energy Generation and Electricity Usage
- Future Projections
NPV & IRR
- The NPV for future projections in both scenario 1 and 2 (-4465.01, -4357.52) had negative values suggesting that investing in a solar battery would be unworthy. The IRR for both scenarios (-0.05, -0.08) had a low negative value hence the profitability on the investment would be less desirable. The table below shows the NPV and IRR of the projected years
| Cash Flow Methods | Scenario 1 | Scenario 2 |
|---|---|---|
| NPV | -4465.01 | -4357.52 |
| IRR | -0.05 | -0.08 |
Conclusion
The analysis reveals that while installing a battery to store excess solar-generated electricity can theoretically lead to significant savings in electricity costs, the financial viability of such an investment is questionable based on the NPV and IRR calculations. Both scenarios indicate negative NPV values and low negative IRR values, suggesting that the investment may not be profitable under the current assumptions. However, the integration of solar panels with a battery storage system still offers potential benefits in terms of energy independence and sustainability.
Recommendations
- Explore Alternative Battery Options - Investigate other battery models or brands that might offer better efficiency, longer lifespan, or lower costs. This could improve the financial viability of the investment.
- Consider Government Incentives and Rebates - Look into any available government incentives, rebates, or tax credits for renewable energy installations. These can significantly offset the initial investment cost and improve the overall return on investment.
- Optimize Energy Consumption - Implement energy-saving measures within the household to reduce overall electricity consumption. This can enhance the effectiveness of the solar and battery system, maximizing savings and improving the financial outlook of the investment.