| ... | @@ -10,12 +10,14 @@ This tutorial provides a guide to simulate an agrivoltaic system with PASE. |
... | @@ -10,12 +10,14 @@ This tutorial provides a guide to simulate an agrivoltaic system with PASE. |
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# Modules
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# Modules
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The PASE software is coded in object-oriented Python.
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The PASE software is coded in object-oriented Python.
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The engine running the computations is made of modules, located in the MODULES/ directory.
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The engine running the computations is made of modules, located in the pase/ directory.
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Those modules are imported at the start of the simulation script.
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Those modules are imported at the start of the simulation script.
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The `example.py` script is the preferred example for newcomers.
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# Inputs
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# Inputs
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## Parameter files
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As a user, you can easily run PASE using the `example.py` script "as is" and only adapting the parameters of the simulation.
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As a user, you can easily run PASE using the `example.py` script "as is" and only adapting the parameters of the simulation.
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These parameters are set in YAML configuration files contained in the INPUTS/ directory's subdirectories.
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These parameters are set in YAML configuration files contained in the INPUTS/ directory's subdirectories.
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Each parameter in these files includes detailed information such as:
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Each parameter in these files includes detailed information such as:
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| ... | @@ -29,6 +31,11 @@ Each parameter in these files includes detailed information such as: |
... | @@ -29,6 +31,11 @@ Each parameter in these files includes detailed information such as: |
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To update a parameter, change only the value following the line labeled **"Value:"**.
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To update a parameter, change only the value following the line labeled **"Value:"**.
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This helps ensure consistent formatting and preserves the contextual information about each parameter.
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This helps ensure consistent formatting and preserves the contextual information about each parameter.
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**Important**: note that some parameters are marked as optional.
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There are very few of those, and by default all parameters are mandatory.
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Even if a parameter may seem unrelated to your specific application, it may affect computations in indirect ways.
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Take the time to specify correct parameter values !
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The parameters are located in several subdirectories according to their purpose:
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The parameters are located in several subdirectories according to their purpose:
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- AV_CENTRAL/ : set parameters of the agrivoltaics plant (number of panels, azimuth of the central, etc.)
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- AV_CENTRAL/ : set parameters of the agrivoltaics plant (number of panels, azimuth of the central, etc.)
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| ... | @@ -37,12 +44,42 @@ The parameters are located in several subdirectories according to their purpose: |
... | @@ -37,12 +44,42 @@ The parameters are located in several subdirectories according to their purpose: |
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- SCENARIOS/ : define the parameters of the simulation scenario, such as location, latitude and longitude, altitude, simulation options, start and end year of the simulation, etc.
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- SCENARIOS/ : define the parameters of the simulation scenario, such as location, latitude and longitude, altitude, simulation options, start and end year of the simulation, etc.
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- WEATHER_FILES/ : the simulation can run on data fetched from an online database or on data files located in this subdirectory.
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- WEATHER_FILES/ : the simulation can run on data fetched from an online database or on data files located in this subdirectory.
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## Daily weather files - precipitation and vapour pressure data
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## Weather data
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To run simulations, PASE needs these four weather variables :
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- global horizontal irradiance [W/m²]
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- air temperature [°C]
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- daily sum of precipitations [mm/d]
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- daily average of atmospheric water vapor pressure [hPa]
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In the scenario file, users chose WeatherDataOption 1 or 2 :
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1. Fetch weather data from PVGIS
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2. User provides all weather data
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Those two options are described in detail below.
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### 1. Fetch weather data from PVGIS
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With this option, hourly weather data (GHI and air temperature) is downloaded through the PVGIS API.
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The resulting dataframe has columns :
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'DateTime', 'G(h)', 'Gb(n)', 'Gd(h)', 'T2m', 'WS10m'
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- DateTime: Timestamp in %Y-%m-%d %H:%M:%S format (e.g. 2020-01-01 00:10:00)
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- G(h): global horizontal irradiance [W/m²]
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- Gb(n): direct normal irradiance [W/m²]
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- Gd(h): diffuse horizontal irradiance [W/m²]
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- T2m: temperature at 2 m from the ground [°C]
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- WS10m: wind speed at 10 m from the ground [m/s]
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When choosing this option, user must still provide the daily precipitation (daily sum, [mm/d])
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and atmospheric water vapor pressure (daily average, [hPa]) data in the form of a csv file.
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This is detailed in the next section.
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#### Daily weather file - precipitation and vapour pressure data
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The crop modeling component of PASE requires daily weather data to compute evapotranspiration and related processes.
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The crop modeling component of PASE requires daily weather data to compute evapotranspiration and related processes.
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Two key variables are needed: daily precipitation and water vapor pressure.
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Two key variables are needed: daily precipitation and water vapor pressure.
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### Data Sources
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##### Data Sources
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You can obtain the necessary data in one of two ways:
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You can obtain the necessary data in one of two ways:
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| ... | @@ -50,26 +87,78 @@ From Agri4Cast: if your study area is covered, you can download the daily weathe |
... | @@ -50,26 +87,78 @@ From Agri4Cast: if your study area is covered, you can download the daily weathe |
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Manual creation: if no Agri4Cast data is available, you must prepare a custom CSV file containing the required variables (see below).
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Manual creation: if no Agri4Cast data is available, you must prepare a custom CSV file containing the required variables (see below).
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### File Structure
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##### File Structure
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The input file must be a **semicolon-separated** CSV with the following columns:
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The input file must be a comma- or semicolon-separated CSV with the following columns:
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| Column Name | Description | Units | Example |
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| Column name | Description | Units | Example |
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| ---------------- | ---------------------------------- | ----- | -------- |
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|------------------| ---------------------------------- | ----- | -------- |
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| `DAY` | Calendar date in `yyyymmdd` format | - | 20210415 |
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| `DAY` | Calendar date in `yyyymmdd` format | - | 20210415 |
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| `VAPOR_PRESSURE` | Daily mean vapor pressure | hPa | 12.3 |
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| `VAPOR_PRESSURE` | Daily mean vapor pressure | hPa | 12.3 |
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| `PRECIPITATION` | Daily total precipitation | mm/d | 4.7 |
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| `PRECIPITATION` | Daily total precipitation | mm/d | 4.7 |
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### Formatting Requirements
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Each row in this file provides data for one day.
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##### Formatting Requirements
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- Use UTF-8 encoding and `;` as the column separator.
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- Use UTF-8 encoding
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- Include a header row exactly matching the column names above.
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- `;` or `,` as the column separator
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- Include a header row exactly matching the column names above
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- Ensure all dates are valid (mind **leap years***) and continuous if the simulation requires complete coverage.
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- Ensure all dates are valid (mind **leap years***) and continuous if the simulation requires complete coverage.
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### Example File
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##### Example File
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A minimal reference file is provided in the repository under INPUTS/WEATHER_FILES/minimal_PRECIP_VP.csv
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A minimal reference file is provided in the repository under INPUTS/WEATHER_FILES/minimal_PRECIP_VP.csv
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### 2. User-provided weather data
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With this option, all four weather variables (GHI, air temperature,
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precipitation and vapor pressure) must be provided by the user in the form of a csv file.
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##### File Structure
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The input file must be a comma- or semicolon-separated CSV with the following columns:
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| Column name | Description | Unit | Format | Example |
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|----------------|----------------------------------------|------|------------------|:----------------:|
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| date | Timestamp of measurements | - | dd/mm/yyyy hh:mm | 25/10/2017 15:00 |
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| G(h) | Global horizontal irradiance | W/m² | float | 125.2 |
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| T2m | Air temperature at 2 m from the ground | °C | float | 12.6 |
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| PRECIP | Daily sum of precipitation | mm/d | float | 12 |
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| VAPOR_PRESSURE | Atmospheric water vapor pressure | hPa | float | 6.86 |
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Each row in this file provides data for a timestep. PASE is designed
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to parse the data file and automatically infer the sampling period.
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Fully supported sampling periods are 1h, 15 min and 10 min.
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Other sampling periods may work for part of the simulations.
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GHI and air temperature will be used at the provided timestep, while
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precipitation and atmospheric water vapor pressure data will be respectively
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summed and averaged on each day to serve as inputs to crop models.
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##### Formatting Requirements
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- Use UTF-8 encoding
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- `;` or `,` as the column separator
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- Include a header row exactly matching the column names above
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- Ensure all dates are valid (mind **leap years***) and continuous if the simulation requires complete coverage.
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##### Example File
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A minimal reference file is provided in the repository under INPUTS/WEATHER_FILES/Michamps_2017_WD2.csv (temporarily, this file is available in [branch 160](https://gitlab.uliege.be/deal-public/pase/-/blob/160-feature-adding-legumes-growth/INPUTS/WEATHER_FILES/Michamps_2017_WD2.csv?ref_type=heads)).
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### Summary
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The following table provides an overview of the information a weather file should contain, based on the value of WeatherDataOption.
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| Column name | Description | Unit | WeatherDataOption 1 | WeatherDataOption 2 |
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| date | Timestamp (format depends on WeatherDataOption) | - | x | x |
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| G(h) | Global horizontal irradiance | W/m² | | x |
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| T2m | Air temperature at 2 m from the ground | °C | | x |
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| PRECIP | Daily sum of precipitation | mm/d | x | x |
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| VAPOR_PRESSURE | Atmospheric water vapor pressure | hPa | x | x |
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# Running a simulation
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# Running a simulation
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Once the parameters are set, the simulation can start.
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Once the parameters are set, the simulation can start.
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