- Setup and activate virtual environment.
- Install requirements:
pip install -r requirements.txt-
Open the project in an IDE, e.g. in VisualStudio Code and use the same virtual environment as the Python environment.
-
When running Jupyter install the needed dependencies. They are not part of
requirements.txt.
The virtuous directory contains code for simulation of a solar power plant:
GenerationModelcan produce monthly time series for the energy producedFinancialModelcan take this data and calculate the revenue for selling this energy and also estimate operational costs: maintenance and cleaning
The Jupyter Notebooks (see notebooks) folder use this models to produce concrete
results in the form of charts.
Your colleague has implemented the models and started working with notebooks, when his work was interrupted. Now you need to take over the project and finish it according to the tasks listed below.
You can change any code - both in notebooks or in models.
In notebooks/one-year.ipynb show the financial time series
(cleaning cost, maintenance cost and revenue) as a stacked bar chart
- costs are expected to be shown as negatives, revenues as positives
- X-axis should show months
- Y-axis should show money in EUR
In notebooks/cashflow.ipynb calculate and visualize a cashflow for 20 years.
Cashflow is a bar chart with X-axis having years and each bar representing a total of
cleaning cost, maintenance cost and revenue for entire year.
The notebook has a sample visualization with the fake data, that can be replaced with the real one.
At the moment our solution uses a fixed energy price to calculate the revenues. We want
to use a CSV file price_forecast.csv as the source of prices for each year
and update the cashflow using this data.
Add a new chart showing a part of cashflow from 2025 to 2035 (inclusively) with energy price curve on top of the cashflow bar chart for comparison (second Y-axis)