71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
from src.Functions_Energy_Model import *
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from src.Functions_General import *
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import subprocess
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import signal
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import time
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location_ita = 'Biella' # location in Italian
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capacity = 100 # kWp
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tilt_angle = 30 # gradi
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azimuth = 0 # gradi
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num_years = 1 # anni di simulazione
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derating_factor_percent = 1 # derating factor that reduce the efficiency of the modules in percentage [%]
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config = yaml.safe_load(open("config.yml", 'r'))
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path_export = str(config['filename_output_csv_gen_pv']) # percorso del file di output
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# IGNORE THIS
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isJoe = config['joe_fight']
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joePlaying = False
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if(isJoe == True):
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if shutil.which('ffplay') is not None:
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joePlaying = True
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joe = subprocess.Popen(['ffplay', '-fs', 'assets/joefight.mp4'])
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time.sleep(25) # deve arrivare il drop
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else:
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print("ffplay non installato, no joe fight.")
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# INIZIALIZZAZIONE PARAMETRI PER SIMULAZIONE
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location_eng = location_italian_to_english(location_ita)
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path = "config.yml"
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filename = ""
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key = "project_lifetime_yrs"
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value = num_years
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add_to_file_yml(path, filename, key, value)
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suppress_printing(generate_calendar) # generazione del calendario
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coordinates_dataset = suppress_printing(create_coordinates_dataset, [location_eng]) # crea un dataset con le coordinate di tutte le posizioni
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derating_factor = derating_factor_percent / 100
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# CALCOLO PRODUTTIVITA'
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result_ac_energies_resampled = suppress_printing(simulate_1_kWp_generators, coordinates_dataset, tilt_angle, azimuth)
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# SCALING PRODUTTIVITA'
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result_ac_energies_gens = {} # initialization of the output dictionary
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result_ac_energies_gens['gen_pv_' + str(capacity) + '_kWp'] = result_ac_energies_resampled[location_eng] * capacity
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# DERATING PRODUTTIVITA'
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result_ac_energies_gens_derated = suppress_printing(simulate_gens_derated_productivity, derating_factor, result_ac_energies_gens)
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# GENERAZIONE DATAFRAME
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result_ac_energies_to_csv_df = suppress_printing(simulate_unstacked_productivity, result_ac_energies_gens_derated) # create two unstacked dataframe (the other functions work with dictionaries)
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# ESPORTAZIONE RISULTATI IN CSV
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print("Valore massimo:",max(result_ac_energies_to_csv_df.gen_pv_100_kWp)) # print the maximum value of the generated energy
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print("Somma totale:",sum(result_ac_energies_to_csv_df.gen_pv_100_kWp)) # print the total sum of the generated energy
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result_ac_energies_to_csv_df.to_csv(path_export, encoding='utf-8')
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# GENERAZIONE GRAFICO
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import plotly.express as px
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# Supponendo che la colonna di interesse sia 'gen_pv_100_kWp'
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fig = px.line(
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result_ac_energies_to_csv_df,
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x=result_ac_energies_to_csv_df.index,
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y='gen_pv_100_kWp',
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title='Produttività Fotovoltaica nel Tempo',
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labels={'gen_pv_100_kWp': 'Energia [kWh]', 'index': 'Data/Ora'}
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)
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fig.show()
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if joePlaying:
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joe.terminate()
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joe.kill() |