Source code for technology.technology_a_model
"""
Template for technology model file.
Corresponds to Technology A in the template decision context.
"""
import numpy as np
[docs]def capital_cost(scale, parameter):
"""
Capital cost function.
Parameters
----------
scale : float
The scale of operation.
parameter : array
The technological parameterization.
"""
# Stack the capital cost values into a single array to return.
return np.stack((parameter[0] * scale**0.6,
parameter[1] * scale**0.6,
parameter[2] * scale**0.6,
parameter[3] * scale**0.6,
parameter[4] * scale**0.6))
[docs]def fixed_cost(scale, parameter):
"""
Capital cost function.
Parameters
----------
scale : float
The scale of operation.
parameter : array
The technological parameterization.
"""
# Fixed costs are being modeled as a fraction of the
# total capital cost
# Stack the fixed cost values into a single array to return.
return np.stack(0.1 * (parameter[0] + parameter[1] + parameter[2] + parameter[3] + parameter[4]) * scale)
[docs]def production(scale, capital, lifetime, fixed, input, parameter):
"""
Production function.
Parameters
----------
scale : float
The scale of operation.
capital : array
Capital costs.
lifetime : float
Technology lifetime.
fixed : array
Fixed costs.
input : array
Input quantities.
parameter : array
The technological parameterization.
"""
# Stack the calculated output values into a single array to return.
return np.stack((scale * parameter[10] * parameter[11] * parameter[12] * parameter[13] * input[0],
scale * parameter[13] * input[1],
scale * parameter[13] * input[0]))
[docs]def metrics(scale, capital, lifetime, fixed, input_raw, input, input_price, output_raw, output, cost, parameter):
"""
Metrics function.
Parameters
----------
scale : float
The scale of operation.
capital : array
Capital costs.
lifetime : float
Technology lifetime.
fixed : array
Fixed costs.
input_raw : array
Raw input quantities (before losses).
input : array
Input quantities.
output_raw : array
Raw output quantities (before losses).
output : array
Output quantities.
cost : array
Costs.
parameter : array
The technological parameterization.
"""
_annualized_cost_per_unit_F = (capital[0] + capital[1] + capital[2] + capital[3] + capital[4] + fixed*lifetime[0] + input_price[0] * input_raw[0] + input_price[1] * input_raw[1] + input_price[2] * input_raw[2] - 12.0 * output[1] - 9.0 * output[2])/output[0] - parameter[15]
_labor_per_unit_F = (parameter[8] * output_raw[0] + parameter[9] * (output_raw[1] + output_raw[2]))/output[0] - parameter[16]
_impact_per_unit_F = (parameter[5] * input_raw[0] + parameter[6] * input_raw[1] + parameter[7] * input_raw[2]) / output[0] - parameter[17]
_overall_efficiency = output[0] / (input_raw[0] + input_raw[1] + input_raw[2]) - parameter[18]
# Stack the metric values into a single array to return.
return np.stack((_annualized_cost_per_unit_F,
_labor_per_unit_F,
_impact_per_unit_F,
_overall_efficiency))