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resultsWriter.py
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resultsWriter.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Sep 10 17:48:29 2020
@author: INATECH-XX
"""
from datetime import datetime
import pandas as pd
import os
class ResultsWriter():
def __init__(self,
database_name,
simulation_id,
write_to_db,
starting_date='2018-01-01T00:00:00',
host='localhost',
port=8086,
user='root',
password='root',
world=None):
self.user = user
self.password = password
self.database_name = database_name
self.simulation_id = simulation_id
self.starting_date = starting_date
self.world = world
self.index = pd.date_range(
self.world.starting_date,
periods=len(self.world.snapshots),
freq=f'{str(60 * self.world.dt)}T'
)
if write_to_db:
from influxdb import InfluxDBClient
from influxdb import DataFrameClient
# Creating connection and Database to save results
self.client = InfluxDBClient(host=host, port=port)
self.client.create_database(database_name)
self.client.switch_database(database_name)
self.dfClient = DataFrameClient(host=host,
port=port,
username=self.user,
password=self.password,
database=self.database_name)
self.dfClient.switch_database(self.database_name)
def writeDataFrame(self, df, measurement, tags=None):
if tags is None:
tags = {'simulationID': 'Historic_Data'}
self.dfClient.write_points(dataframe=df,
measurement=measurement,
tags=tags,
protocol='line')
def save_results_to_DB(self):
start = datetime.now()
self.world.logger.info('Writing Capacities and Prices to Server - This may take couple of minutes.')
# writing Merit Order Price
tempDF = pd.DataFrame(self.world.pfc, index=self.index, columns=['Merit order']).astype('float32')
self.writeDataFrame(tempDF, 'Prices', tags={'simulationID': self.world.simulation_id, "user": "EOM"})
# writing EOM market prices
tempDF = pd.DataFrame(self.world.mcp, index=self.index, columns=['Simulation']).astype('float32')
self.writeDataFrame(tempDF, 'Prices', tags={'simulationID': self.world.simulation_id, "user": "EOM"})
# writing EOM demand
tempDF = pd.DataFrame(self.world.markets['EOM']['EOM_DE'].demand.values(), index=self.index, columns=['EOM demand']).astype('float32')
self.writeDataFrame(tempDF, 'Demand', tags={'simulationID': self.world.simulation_id, "user": "EOM"})
# writing residual load
tempDF = pd.DataFrame(self.world.res_load['demand'].values, index=self.index, columns=['Residual load']).astype('float32')
self.writeDataFrame(tempDF, 'Demand', tags={'simulationID': self.world.simulation_id, "user": "EOM"})
# writing residual load forecast
tempDF = pd.DataFrame(self.world.res_load_forecast['demand'].values, index=self.index, columns=['Residual load forecast']).astype('float32')
self.writeDataFrame(tempDF, 'Demand', tags={'simulationID': self.world.simulation_id, "user": "EOM"})
# save total capacities, must-run and flex capacities and corresponding bid prices of power plants
self.write_pp()
# write storage capacities
self.write_storages()
finished = datetime.now()
self.world.logger.info(f'Saving into database time: {finished - start}')
def save_result_to_csv(self):
self.world.logger.info('Saving results into CSV files...')
directory = f'output/{self.world.scenario}/'
if not os.path.exists(directory):
os.makedirs(directory)
os.makedirs(directory+'/PP_capacities')
os.makedirs(directory+'/STO_capacities')
# writing EOM market prices as CSV
tempDF = pd.DataFrame(self.world.mcp,
index=self.index,
columns=['Price']).astype('float32')
tempDF.to_csv(directory + 'EOM_Prices.csv')
# save total capacities of power plants as CSV
for powerplant in (self.world.rl_powerplants+self.world.powerplants+self.world.vre_powerplants):
tempDF = pd.DataFrame(data=powerplant.total_capacity, index=self.index, columns=['Total pp']).astype('float32')
tempDF.to_csv(directory + f'PP_capacities/{powerplant.name}_Capacity.csv')
# write storage capacities as CSV
for storage in (self.world.storages+self.world.rl_storages):
tempDF = pd.DataFrame(storage.total_capacity, index=self.index, columns=['Total st']).astype('float32')
tempDF.to_csv(directory + f'STO_capacities/{storage.name}_Capacity.csv')
tempDF = pd.DataFrame(storage.profits, index=self.index, columns=['Profits']).astype('float32')
tempDF.to_csv(directory + f'STO_capacities/{storage.name}_Profits.csv')
tempDF = pd.DataFrame(storage.soc[:-1], index=self.index, columns=['SOC']).astype('float32')
tempDF.to_csv(directory + f'STO_capacities/{storage.name}_SOC.csv')
self.world.logger.info('Saving results complete')
def write_pp(self):
for powerplant in (self.world.rl_powerplants+self.world.powerplants+self.world.vre_powerplants):
tags = {'simulationID': self.world.simulation_id,
'UnitName': powerplant.name,
'Technology': powerplant.technology}
tempDF = pd.DataFrame(data=powerplant.total_capacity, index=self.index, columns=['Total pp']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Capacities',
tags=tags)
tempDF = pd.DataFrame(powerplant.bids_mr, index=['Capacity_MR', 'Price_MR']).T
tempDF = tempDF.set_index(self.index).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Capacities',
tags=tags)
tempDF = pd.DataFrame(powerplant.bids_flex, index=['Capacity_Flex', 'Price_Flex']).T
tempDF = tempDF.set_index(self.index).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Capacities',
tags=tags)
tempDF = pd.DataFrame(powerplant.rewards, index=self.index, columns=['Rewards']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Rewards',
tags=tags)
tempDF = pd.DataFrame(powerplant.regrets, index=self.index, columns=['Regrets']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Regrets',
tags=tags)
tempDF = pd.DataFrame(powerplant.profits, index=self.index, columns=['Profits']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Profits',
tags=tags)
def write_storages(self):
for storage in (self.world.storages+self.world.rl_storages):
tags = {'simulationID': self.world.simulation_id,
'UnitName': storage.name,
'Technology': storage.technology}
tags_with_dir = tags.copy()
tempDF = pd.DataFrame(storage.total_capacity, index=self.index, columns=['Total st']).astype('float32')
tags_with_dir['direction'] = 'discharge'
self.writeDataFrame(dataframe=tempDF.clip(lower=0),
measurement='Capacities',
tags=tags_with_dir)
tags_with_dir['direction'] = 'charge'
self.writeDataFrame(dataframe=tempDF.clip(upper=0),
measurement='Capacities',
tags=tags_with_dir)
tempDF = pd.DataFrame(storage.bids_supply, index=['Capacity_dis', 'Price_dis']).T
tempDF = tempDF.set_index(self.index).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Capacities',
tags=tags)
tempDF = pd.DataFrame(storage.bids_demand, index=['Capacity_ch', 'Price_ch']).T
tempDF = tempDF.set_index(self.index).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Capacities',
tags=tags)
tempDF = pd.DataFrame(storage.rewards, index=self.index, columns=['Rewards']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Rewards',
tags=tags)
tempDF = pd.DataFrame(storage.energy_cost[:-1], index=self.index, columns=['Energy cost']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Energy cost',
tags=tags)
tempDF = pd.DataFrame(storage.soc[:-1], index=self.index, columns=['SOC']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='SOC',
tags=tags)
if 'opt' in self.world.simulation_id:
tempDF = pd.DataFrame(storage.profits, index=self.index, columns=['Profits_opt']).astype('float32')
elif 'base' in self.world.simulation_id:
tempDF = pd.DataFrame(storage.profits, index=self.index, columns=['Profits_base']).astype('float32')
else:
tempDF = pd.DataFrame(storage.profits, index=self.index, columns=['Profits']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Profits',
tags=tags)
if storage.bidding_type == 'opt':
tempDF = pd.DataFrame(storage.opt_profits, index=self.index, columns=['Profits_max']).astype('float32')
self.writeDataFrame(dataframe=tempDF,
measurement='Profits',
tags=tags)
def delete_simulation(self, simID):
self.dfClient.delete_series(tags={'simulationID': simID})
print(simID, 'deleted')
def delete_multiple_simulations(self, simIDs):
reply = input(f'Are you sure you want to delete {str(simIDs)} ???')
if reply.lower() in ['yes', 'y']:
for simID in simIDs:
self.delete_simulation(simID)
else:
print('!!! Ok, NOT deleted !!!')
def delete_database(self, database_name):
check = input('Are you sure you want to delete ' + database_name + ' ??? Type database name to confirm: ')
if check == database_name:
check = input('You are about to delete ' + database_name + ' ??? Are you absolutely sure??? [yes/no]: ')
if check.lower() in ['yes', 'y']:
self.dfClient.drop_database(database_name)
print(database_name, 'database deleted')
else:
print('Ok, not deleted')
else:
print('!!! Wrong name entered !!!')