import datetime as dt
from dispaset.postprocessing import postprocessing as post
import importlib
importlib.reload(post)
import dispaset as ds
import matplotlib.pyplot as plt
from matplotlib.pyplot import *
import seaborn as sns
import matplotlib.dates as mdates
import pickle
import time as tm
import logging
import shutil
import json
shutil.copy('input_data/ConfigGCC2.xlsx', 'Simulations/ConfigGCC2.xlsx')
# Load the configuration file
config = ds.load_config_excel('Simulations/ConfigGCC2.xlsx')
# Build the simulation environment:
SimData, FuelPrices, FuelPrices2 = ds.build_simulation(
config, LocalSubsidyMultiplier=1, ExportCostMultiplier=1)
r = ds.solve_GAMS(config['SimulationDirectory'], config['GAMS_folder'])
path = 'Simulations/simulation_GCC'
inputs, results = ds.get_sim_results(path=path, cache=True)
with open('output_data/results.json', 'w') as fp:
json.dump(str(results), fp)
- build the mode
- run the model
- display and analyse the results
@author: Sylvain Quoilin
"""
# Add the root folder of Dispa-SET to the path so that the library can be loaded:
import sys, os
sys.path.append(os.path.abspath('..'))
# Import Dispa-SET
import dispaset as ds
# Load the configuration file
config = ds.load_config_excel('../ConfigFiles/ConfigEU.xlsx')
# Limit the simulation period (for testing purposes, comment the line to run the whole year)
config['StartDate'] = (2016, 1, 1, 0, 0, 0)
config['StopDate'] = (2016, 1, 7, 0, 0, 0)
# Build the simulation environment:
SimData = ds.build_simulation(config)
# Solve using GAMS:
_ = ds.solve_GAMS(config['SimulationDirectory'], config['GAMS_folder'])
# Load the simulation results:
inputs, results = ds.get_sim_results(config['SimulationDirectory'],
cache=False)
from itertools import product
import cPickle as pickle
import logging
import os
os.chdir('..')
# Import Dispa-SET
import dispaset as ds
# Define path to save results. Each run will be a pickled tuple: (inputs, results)
path_to_save = r'./scenario_runs'
# Load the configuration file
config = ds.load_config_excel('ConfigFiles/ConfigCY.xlsx')
# Define your different input files as a list. The number of total runs will be the product of the length of the defined lists.
heat_demand_scen = [
'./Database/Heat_demand/CY/Vassilikos_CCP2.csv',
'./Database/Heat_demand/CY/Vassilikos_CCP2.csv_80'
]
power_scen = [
'./Database/PowerPlants/##/2015.csv',
'./Database/PowerPlants/##/2015_heat.csv',
]
cost_heat_slack_scen = [20.0, 51.0, 100.0]
res_mod_scen = [0.8, 1.0, 1.2]