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# The Institute for the Design of Advanced Energy Systems Integrated Platform
# Framework (IDAES IP) was produced under the DOE Institute for the
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# by the software owners: The Regents of the University of California, through
# Lawrence Berkeley National Laboratory,  National Technology & Engineering
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# Research Corporation, et al.  All rights reserved.
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"""
Python script to read costing components
This script reads the library of costing components (scaled cost, reference
parameters, costing exponents, etc.) from the json files.
First, open json file, then create a python dictionary that gets imported into
power_plant_costing.py

Three python dictionaries that are loaded:
* BB_costing_exponents
* BB_costing_params
* sCO2_costing_params

"""
__author__ = "Costing Team (<NAME> and <NAME>)"
__version__ = "1.0.0"

import os
import json
from pyomo.common.fileutils import this_file_dir

directory = this_file_dir()


"""
The costing exponents dictionary contains information from the QGESS on
capital cost scaling methodology (DOE/NETL-2019/1784). Specifically it includes
scaling exponents, valid ranges for the scaled parameter, and units for those
ranges. It is important to note the units only apply to the ranges and are not
neccessarily the units that the reference parameter value will be given in.
This dictionary is nested with the following structure:

tech type --> account --> property name --> property value
"""

with open(os.path.join(directory, "BB_costing_exponents.json"), "r") as file:
    BB_costing_exponents = json.load(file)


"""
The costing params dictionary contains information from the BBR4 COE
spreadsheet. It includes the total plant cost (TPC), reference parameter value,
and units for that value.

Some accounts are costed using two different reference parameters, these
accounts have been divided into two separate accounts following the naming
convention x.x.a and x.x.b.

This dictionary is nested with the following structure:
tech type --> CCS --> account --> property name --> property values
"""
with open(os.path.join(directory, "BB_costing_parameters.json"), "r") as file:
    BB_costing_params = json.load(file)


with open(os.path.join(directory, "sCO2_costing_parameters.json"), "r") as file:
    sCO2_costing_params = json.load(file)
