Model Inputs/Outputs¶
The model requires several input parameters, provided via input files. These parameters, their dimensions, and descriptions are as follows:
Inputs¶
The parameters used, their desciptions, and their input file name in the model are as follows:
Parameter [Unit] |
Description |
Input file 1 |
|---|---|---|
historical capacity 2 [MW] |
The capacity of each technology in each zone for each year, taking into account the number of years that each technology has been in operation starting from the beginning of the planning period. |
historical_capacity |
capacity factor [N/A] |
Capacity factor of different non-dispatchable technologies. |
capacity_factor |
carbon emission limit [tCO2] |
Carbon emission limit of different zones. |
carbon_emission_limit |
emission factor [tCO2/MWh] |
Emission factor of different technologies. |
emission_factor |
water delay time [N/A] |
Water delay time of connection between reservoirs. |
water_delay_time |
demand [MW] |
Demand of different balancing authorities. |
demand |
discount factor [N/A] |
Discount factor for each year. |
discount_factor |
distance [km] |
Distance of different pair of zones. |
distance |
discharge efficiency [N/A] |
Discharge efficiency of storage technologies. |
discharge_ efficiency |
charge efficiency [N/A] |
Charge efficiency of storage technologies. |
charge_ efficiency |
energy to power ratio [MWh/MW] |
Power to energy ratio ratio of storage technologies. |
energy_to_ power_ratio |
fuel price [dollar/MWh] |
Fuel price of different technologies. |
fuel_price |
Predefined hydropower 3 [MW] |
Predefined hydropower output of all reservoirs. |
predefined_hydropower |
inflow [m3/s] |
Inflow of all reservoirs. |
inflow |
initial energy storage level [1/MWh] |
Initial energy storage level of different storage technologies. |
initial_energy_ storage_level |
lifetime [yr] |
Lifetime of different technologies. |
lifetime |
new technology lower bound [MW] |
Lower bound of newly-built installed capacity of different technologies for each investment year. |
new_technology_ lower_bound |
new technology upper bound [MW] |
Upper bound of newly-built installed capacity of different technologies for each investment year. |
new_technology_ upper_bound |
ramp down [1/MW] |
Ramp down rate of different technologies. |
ramp_down |
ramp up [1/MW] |
Ramp up rate of different technologies. |
ramp_up |
reservoir characteristics [As per data sheet] |
Reservoir characteristics data includes designed water head, maximum storage, minimum storage, operational efficiency, area of affiliation, installed capacity, maximum power output, minimum power output, maximum outflow, minimum outflow, and maximum generation outflow. |
reservoir_ characteristics |
reservoir storage upper bound [m3] |
Upper bound of volume of hydropower reservoirs. |
reservoir_storage _upper_bound |
reservoir storage lower bound [m3] |
Lower bound of volume of hydropower reservoirs. |
reservoir_storage_ lower_bound |
final reservoir storage level [m3] |
Final volume of hydropower reservoirs. |
final_reservoir_ storage_level |
initial reservoir storage level [m3] |
Initial volume of hydropower reservoirs. |
initial_reservoir_ storage_level |
technology fixed OM cost [dollar/MW/yr] |
Fixed operation and maintenance cost of different technologies. |
technology_fixed_ OM_cost |
technology variable OM cost [dollar/MW/yr] |
Variable operation and maintenance costs of different technologies. |
technology_variable_ OM_cost |
technology investment cost [dollar/MW] |
Investment cost of different technologies. |
technology_investment _cost |
technology portfolio [MW] |
Existing total installed capacity across all zones. |
technology_ portfolio |
technology upper bound 4 [MW] |
Upper bound of installed capacity of different technologies. |
technology_upper_ bound |
transmission line existing capacity [MW] |
Capacity of existing transmission lines (if there is no exising nor planned transmission lines between two specific zones, leave the data entries blank). |
transmission_line_ existing_capacity |
transmission line efficiency [N/A] |
Efficiency of transmission lines across all zones. |
transmission_line_ efficiency |
transmission line fixed OM cost [dollar/MW/yr] |
Fixed operation and maintenance costs of transmission lines. |
transmission_line_ fixed_OM_cost |
transmission line variable OM cost [dollar/MW/yr] |
Variable operations and maintenance costs of transmission lines. |
transmission_line _variable_cost |
transmission line investment cost [dollar/MW/km] |
Investment cost of transmission lines. |
transmission_line_ investment_cost |
transmission line lifetime [yr] |
Lifetime of transmission lines. |
transmission_line_ lifetime |
technology type [N/A] |
Categories of different technologies. |
technology_type |
reservoir tailrace level-discharge function [m & m3/s] |
Relationship between tailrace level and total discharge for different reservoirs. |
reservoir_tailrace_ level_discharge_ function |
reservoir forebay level-volume function [m & m3] |
Relationship between forebay level and volume for different reservoirs |
reservoir_forebay_ level_volume_ function |
Note
inf refers to Infinity, indicating that there is no upper bound.
None refers to a null value for current item.
Outputs¶
The output of the model is stored in a NetCDF file, please refer to this simple tutorial and official documentation of Xarray to understand how to manipulate NetCDF files.
The output file contains the following variables:
Variable name [Unit] |
Description |
|---|---|
trans_import [MW] |
The electrical power transmitted from Zone 1 and effectively received by Zone 2 through the transmission line, after adjusting for transmission losses. |
trans_export [MW] |
The electrical power initially sent out by Zone 1 for transmission to Zone 2 via the transmission line, before adjusting for any transmission and distribution losses during its journey to Zone 2. |
gen [MW] |
Power output of different technologies during user-defined time interval. |
install [MW] |
Existing installed capacity of different technologies. |
carbon [Ton] |
Carbon emissions across different years. |
charge [MW] |
Charged electricity of different storage technologies. |
cost [dollar] |
Total cost (including total investment cost, total variable OM cost, and total fixed OM cost) over the planning period. |
cost_breakdown [dollar] |
Breakdown of total cost (including total investment cost, total variable OM cost, and total fixed OM cost) over the planning period, by zone, year, and technology. |
cost_var [dollar] |
Total variable OM cost (including technology variable OM cost, transmission line variable OM cost, and fuel cost) over the planning period. |
cost_var_breakdown [dollar] |
Breakdown of total variable OM cost (including technology variable OM cost, transmission line variable OM cost, and fuel cost) over the planning period, by zone, year, and technology. |
cost_fix [dollar] |
Total fixed OM cost (including technology fixed OM cost, transmission line fixed OM cost) over the planning period. |
cost_fix_breakdown [dollar] |
Breakdown of total fixed OM cost (including technology fixed OM cost, transmission line fixed OM cost) over the planning period, by zone, year, and technology. |
cost_newtech [dollar] |
Total investment cost of technologies over the planning period. |
cost_newtech_breakdown [dollar] |
Breakdown of total investment cost of technologies over the planning period, by zone, year, and technology. |
cost_newline [dollar] |
Investment cost of transmission lines over the planning period. |
cost_newline_breakdown [dollar] |
Breakdown of total investment cost of transmission lines over the planning period, by zone, year, and technology. |
income [dollar] |
Saved cost due to abstracted water resources over the planning period. |
genflow [m3/s] |
Generated water flow of different reservoirs. |
spillflow [m3/s] |
Spilled water flow of different reservoirs. |
Execute various scenarios¶
By employing command-line parameters, you can execute different scenarios using the model. For example, if you wish to run a scenario referred to as "low demand," you can prepare input data named demand_low.xlsx. Subsequently, when running the model, you can utilize command-line parameters to specify the scenario value. For instance, you can execute the model by executing the command python run.py --demand=low.
Setting global parameters¶
This section will guide you on how to tune the PREP-SHOT model parameters to compute the energy system for your needs. After you have prepared your input data based on the previous sections, you can proceed to tune the model parameters before you run it.
Within the root directory of the model, you will find a JSON file containing the parameters that you can tune for the model, named config.json. This file contains the following parameters:
Model Parameter |
Description |
|---|---|
input_folder |
Specifies the name of the folder containing the input data. |
output_filename |
Specifies the name of the output file. |
hour |
Specifies the number of hours in each time period. |
month |
Specifies the number of months in each time period. |
dt |
Specifies the timestep for the simulation in hours. |
hours_in_year |
Specifies the number of hours in a year. Typically, this is set to 8760. |
isinflow |
Specifies whether to include inflow in the optimization problem. It can be used by assigning isinflow = true or false. |
error_threshold |
Specifies the error threshold for the model, while iterating for a solution. This parameter controls the convergence of the hydro model. |
iteration_number |
Specifies the maximum number of iterations for the hydro model, while iterating for a solution. |
solver |
Specifies the solver to be used for the optimization problem. |
solver_path |
Specifies the path of the dynamic library of solver. This is required while automatic detection of the installation directory of the solver fails. Please provide refer to PyOptInterface documentation. |
solver_parameters |
Specifies the solver-specific parameters for mosek, gurobi, highs, and copt. |
After you have tuned the parameters, you can run the model by following the steps in the Installation page.
You can also try out the model with the sample data provided in the input folder. Refer to the Model Inputs/Outputs page for a walkthrough of this example, inspried by real-world data.
Footnotes
- 1
The input files format is
.xlsx.- 2
For instance, assuming the planning period spans from 2020 to 2050, with 2020 being the starting point, let's consider a technology that has been in operation since 2019. In this case, 2020 would mark its 2nd year of operation within the planning period. These inputs are useful for modelling the retirement of existing technologies.
- 3
To model the simplified hydropower operation.
- 4
To model the potential of technologies with land, fuel, and water constraints.