def preparation():
project_path = 'C:\\Users\\FrancescoBaldi\\switchdrive\\Work in progress\\Paper 0\\Ecos2015PaperExtension\\'
path_files = project_path + os.sep
sys.path.append(path_files)
filenames = input.filenames(project_path) # Note: this is just a test
CONSTANTS = kk.constantsSetting()
CONSTANTS["filenames"] = filenames
processed_temp = pd.read_hdf(CONSTANTS["filenames"]["dataset_output"], 'processed')
dataset_raw = pd.read_hdf(filenames["dataset_raw"], 'table')
data = pd.DataFrame(index=processed_temp.index)
indexes_2_save_processed = {"Passengers_calc", "Demands:Electricity:HVAC:Edot", "T_air",
"AE1:Cyl:FuelPh_in:mdot", "AE2:Cyl:FuelPh_in:mdot", "AE3:Cyl:FuelPh_in:mdot", "AE4:Cyl:FuelPh_in:mdot",
"ME1:Cyl:FuelPh_in:mdot", "ME2:Cyl:FuelPh_in:mdot", "ME3:Cyl:FuelPh_in:mdot","ME4:Cyl:FuelPh_in:mdot",
"ME2:HRSG:Steam_in:mdot", "ME3:HRSG:Steam_in:mdot",
"AE1:HRSG:Steam_in:mdot", "AE2:HRSG:Steam_in:mdot", "AE3:HRSG:Steam_in:mdot", "AE4:HRSG:Steam_in:mdot",
"CoolingSystems:HTcollector24:HTWater_out:mdot", "CoolingSystems:HTcollector13:HTWater_out:mdot",
"CoolingSystems:HTcollector24:HTWater_out:T", "CoolingSystems:HTcollector13:HTWater_out:T",
"ME1:on", "ME2:on", "ME3:on", "ME4:on", "AE1:on", "AE2:on", "AE3:on", "AE4:on",
}
indexes_2_save_raw = {"SBO 1 OUTLET PRESSUR:7313:bar:Average:900", "SBO 2 OUTLET PRESSUR:7333:bar:Average:900", "Boiler_Port", "Boiler_starbord"}
for idx in indexes_2_save_processed:
data[idx] = processed_temp[idx]
for idx in indexes_2_save_raw:
data[idx] = dataset_raw[idx]
# Prepare the input
constant_input = (data, CONSTANTS, "optimization")
# Set the boundaries
lb = [0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 0.2, 343, 0.5, 1e2, 2000]
ub = [1000, 1000, 1.0, 1.0, 1.0, 1.0, 1.0, 353, 0.9, 1e5, 8000]
# param[0] = Constant demand to the HTHR systems
# param[1] = Constant steam demand
# param[2] = a1 factor of the HVAC re-heater (HVAC,RH)
# param[3] = a1 factor of the hot water heater (HWH)
# param[4] = a1 factor of the HVAC pre-heater (HVAC,PH)
# param[5] = a1 factor of the Galley (G)
# param[6] = a1 factor of the Other users (TH, OT, HFOT)
# param[7] = Fixed temperature of the HRHT
# param[8] = Effectiveness of the HTHR heat exchangers
# param[9] = Boiler drum steam storage capacity [MJ, energy]
# param[10] = Boiler heat rate when in use [kW]
# Launch the optimization
# xopt, fopt = pso(fitnessFunction, lb, ub, args=constant_input, debug=True)
# Test 1: Storage size lower boundary = 1e4
# xopt = [2.91644687e+02, 8.17208680e+01, 5.53887266e-01, 9.09731971e-01, 9.94747229e-01, 5.00805591e-01, 2.77852293e-01, 3.44650539e+02, 8.61087194e-01, 1.00000000e+04, 7.81351743e+03]
# opt = 0.37162408752748827
# Test 2: Storage size lower boundary = 1e3
# Note: the 3* factor in param[9] comes from trying to manually adapt the frequency of the start-stops to the boiler pressure signal
xopt = [1.36929841e+02, 1.76569058e+02, 5.90926596e-01, 7.06974933e-01, 9.98138178e-01, 5.47476618e-01, 2.69942265e-01, 3.45398252e+02, 7.18364651e-01, 3*2.06480953e+03, 2.92188518e+03]
fopt = 0.3633742911019279
fitnessFunction(xopt, data, CONSTANTS, "test")
return (xopt, fopt)
def preparation():
project_path = 'C:\\Users\\FrancescoBaldi\\switchdrive\\Work in progress\\Paper 0\\Ecos2015PaperExtension\\'
path_files = project_path + os.sep
sys.path.append(path_files)
filenames = input.filenames(project_path) # Note: this is just a test
CONSTANTS = kk.constantsSetting()
CONSTANTS["filenames"] = filenames
processed_temp = pd.read_hdf(CONSTANTS["filenames"]["dataset_output"], 'processed')
dataset_raw = pd.read_hdf(filenames["dataset_raw"], 'table')
data = pd.DataFrame(index=processed_temp.index)
indexes_2_save_processed = {"Passengers_calc", "Demands:Electricity:HVAC:Edot", "T_air",
"AE1:Cyl:FuelPh_in:mdot", "AE2:Cyl:FuelPh_in:mdot", "AE3:Cyl:FuelPh_in:mdot", "AE4:Cyl:FuelPh_in:mdot",
"ME1:Cyl:FuelPh_in:mdot", "ME2:Cyl:FuelPh_in:mdot", "ME3:Cyl:FuelPh_in:mdot","ME4:Cyl:FuelPh_in:mdot",
"ME2:HRSG:Steam_in:mdot", "ME3:HRSG:Steam_in:mdot",
"AE1:HRSG:Steam_in:mdot", "AE2:HRSG:Steam_in:mdot", "AE3:HRSG:Steam_in:mdot", "AE4:HRSG:Steam_in:mdot",
"CoolingSystems:HTcollector24:HTWater_out:mdot", "CoolingSystems:HTcollector13:HTWater_out:mdot",
"CoolingSystems:HTcollector24:HTWater_out:T", "CoolingSystems:HTcollector13:HTWater_out:T",
"ME1:on", "ME2:on", "ME3:on", "ME4:on", "AE1:on", "AE2:on", "AE3:on", "AE4:on",
}
indexes_2_save_raw = {"SBO 1 OUTLET PRESSUR:7313:bar:Average:900", "SBO 2 OUTLET PRESSUR:7333:bar:Average:900", "Boiler_Port", "Boiler_starbord"}
for idx in indexes_2_save_processed:
data[idx] = processed_temp[idx]
for idx in indexes_2_save_raw:
data[idx] = dataset_raw[idx]
# Prepare the input
constant_input = (data, CONSTANTS, "optimization")
# Set the boundaries
lb = [0.0, 0.5, 0.5, 0.5, 0.0, 0.0, 343, 1e4, 2000]
ub = [1.2, 1.5, 1.2, 1.2, 1.0, 1.0, 353, 1e5, 8000]
# param[0] = weighting factor of the HVAC re-heater (HVAC,RH)
# param[1] = weighting factor of the hot water heater (HWH)
# param[2] = weighting factor of the HVAC pre-heater (HVAC,PH)
# param[3] = weighting factor of the Galley (G)
# param[4] = 0-lev weighting factor of the Other users (TH, OT, HFOT)
# param[5] = 1-lev weighting factor of the Other users (TH, OT, HFOT)
# param[6] = Fixed temperature of the HRHT
# param[7] = Boiler drum steam storage capacity [MJ, energy]
# param[8] = Boiler heat rate when in use [kW]
# Launch the optimization
xopt, fopt = pso(fitnessFunction, lb, ub, args=constant_input, debug=True)
# xopt = [4.52478586e-01, 1.00615880e+00, 9.43346251e-01, 7.99418205e-01, 1.81078383e-01, 4.62759293e-01, 3.48521369e+02, 1.07001004e+04, 6.84890150e+03]
# xopt = [6.91524220e-02, 8.88251348e-01, 7.05557625e-01, 9.16916717e-01, 5.84153147e-01, 6.79672716e-01, 3.45217955e+02, 5.08353465e+04, 6.00408344e+03]
fopt = 0.36495629012944736
fitnessFunction(xopt, data, CONSTANTS, "test")
return (xopt, fopt)
# - DATA READING # - DATA CLEANING # - DATA PROCESSING # - EXPLORATORY DATA ANALYSIS # - ENERGY ANALYSIS # - EXERGY ANALYSIS ###################################### ## INPUT ## ###################################### # Loading appropriate modules import pandas as pd import input filenames = input.filenames() # Note: this is just a test ###################################### ## DATA READING ## ###################################### # Responsible: FA import datareading as dr data_path = 'C:\\Users\\FrancescoBaldi\\Dropbox\\Energy and exergy analysis of a cruise ship - Journal Extension\\' dataset_raw = pd.read_hdf(data_path + 'birka_all_data.h5', 'table') #N_POINTS = 319* 4 * 24 #temp = CONSTANTS.monthLimits(N_POINTS) #MONTH_LIMIT_IDX = temp[0]
def preparation():
project_path = 'C:\\Users\\FrancescoBaldi\\switchdrive\\Work in progress\\Paper 0\\Ecos2015PaperExtension\\'
path_files = project_path + os.sep
sys.path.append(path_files)
filenames = input.filenames(project_path) # Note: this is just a test
CONSTANTS = kk.constantsSetting()
CONSTANTS["filenames"] = filenames
processed_temp = pd.read_hdf(CONSTANTS["filenames"]["dataset_output"],
'processed')
dataset_raw = pd.read_hdf(filenames["dataset_raw"], 'table')
data = pd.DataFrame(index=processed_temp.index)
indexes_2_save_processed = {
"Passengers_calc",
"Demands:Electricity:HVAC:Edot",
"T_air",
"AE1:Cyl:FuelPh_in:mdot",
"AE2:Cyl:FuelPh_in:mdot",
"AE3:Cyl:FuelPh_in:mdot",
"AE4:Cyl:FuelPh_in:mdot",
"ME1:Cyl:FuelPh_in:mdot",
"ME2:Cyl:FuelPh_in:mdot",
"ME3:Cyl:FuelPh_in:mdot",
"ME4:Cyl:FuelPh_in:mdot",
"ME2:HRSG:Steam_in:mdot",
"ME3:HRSG:Steam_in:mdot",
"AE1:HRSG:Steam_in:mdot",
"AE2:HRSG:Steam_in:mdot",
"AE3:HRSG:Steam_in:mdot",
"AE4:HRSG:Steam_in:mdot",
"CoolingSystems:HTcollector24:HTWater_out:mdot",
"CoolingSystems:HTcollector13:HTWater_out:mdot",
"CoolingSystems:HTcollector24:HTWater_out:T",
"CoolingSystems:HTcollector13:HTWater_out:T",
"ME1:on",
"ME2:on",
"ME3:on",
"ME4:on",
"AE1:on",
"AE2:on",
"AE3:on",
"AE4:on",
}
indexes_2_save_raw = {
"SBO 1 OUTLET PRESSUR:7313:bar:Average:900",
"SBO 2 OUTLET PRESSUR:7333:bar:Average:900", "Boiler_Port",
"Boiler_starbord"
}
for idx in indexes_2_save_processed:
data[idx] = processed_temp[idx]
for idx in indexes_2_save_raw:
data[idx] = dataset_raw[idx]
# Prepare the input
constant_input = (data, CONSTANTS, "optimization")
# Set the boundaries
lb = [0.0, 0.0, 0.0, 0.5, 0.5, 0.5, 0.2, 343, 0.5, 1e4, 2000]
ub = [1000, 1000, 1.0, 1.0, 1.0, 1.0, 1.0, 353, 0.9, 1e7, 8000]
# param[0] = Constant demand to the HTHR systems
# param[1] = Constant steam demand
# param[2] = a1 factor of the HVAC re-heater (HVAC,RH)
# param[3] = a1 factor of the hot water heater (HWH)
# param[4] = a1 factor of the HVAC pre-heater (HVAC,PH)
# param[5] = a1 factor of the Galley (G)
# param[6] = a1 factor of the Other users (TH, OT, HFOT)
# param[7] = Fixed temperature of the HRHT
# param[8] = Effectiveness of the HTHR heat exchangers
# param[9] = Boiler drum steam storage capacity [MJ, energy]
# param[10] = Boiler heat rate when in use [kW]
# Launch the optimization
xopt, fopt = pso(fitnessFunction, lb, ub, args=constant_input, debug=True)
# Test 1
# xopt = [0.00000000e+00, 0.00000000e+00, 2.54803569e-01, 9.99957005e-01, 1.00000000e+00, 5.48135386e-01, 2.02497633e-01, 3.46800156e+02, 5.00000000e-01, 9.91841867e+06, 7.92913650e+03]
# xopt = [1.11658780e+02, 1.01578823e+01, 2.58777430e-01, 7.33523799e-01, 1.00000000e+00, 7.31005444e-01, 2.00407605e-01, 3.43000000e+02, 5.00000000e-01, 1.00000000e+07, 2.83632523e+03]
# fopt = 0.3632706766877296
fitnessFunction(xopt, data, CONSTANTS, "test")
return (xopt, fopt)
import preprocessingO as ppo
import energyanalysis as ea
import auxiliaryDemand as aux
import coolingsystems as cs
from helpers import d2df
import export as ex
import clustering
import postProcessing as post
#%%
######################################
## DATA READING ##
######################################
# Responsible: FA
# Setting the filenames
filenames = input.filenames(project_path) # Note: this is just a test
# Reading the input data (measurements)
dataset_raw = pd.read_hdf(filenames["dataset_raw"], 'table')
# load the dictionary with the header names
header_names = dr.keysRenaming(dataset_raw, filenames["headers_translate"])
######################################
## DATA PROCESSING ##
######################################
# Responsible: FB
#%%
# Setting the important constants
CONSTANTS = kk.constantsSetting()
CONSTANTS["filenames"] = filenames
(dict_structure, processed) = us.structurePreparation(
CONSTANTS, dataset_raw.index,