def constraint_checker(diameter_array, min_pre, min_vel, max_vel, file,
num_nodes, num_links, num_pipes):
# reconstruct .inp file from diameter array and store it as a temp file
for pipe in range(len(diameter_array)):
if diameter_array[pipe] > 0:
ep.ENsetlinkvalue(pipe + 1, 0, diameter_array[pipe])
ep.ENsaveinpfile(file)
ep.ENopenH()
ep.ENinitH()
ep.ENrunH()
# initialize an array of nodal heads
head_array = np.zeros(num_nodes)
# initialize an array of pipe velocities
velocity_array = np.zeros(num_links)
fail_pressure_list = []
fail_min_vel_list = []
fail_max_vel_list = []
negative_diameter_list = []
fail_pressure = False
fail_min_vel = False
fail_max_vel = False
negative_diameter = False
for node in range(num_nodes):
if ep.ENgetnodevalue(node + 1,
11) < min_pre and ep.ENgetnodetype(node + 1) == 0:
fail_pressure_list.append(node)
fail_pressure = True
for pipe in range(num_pipes):
if ep.ENgetlinkvalue(pipe + 1, 9) < min_vel:
fail_min_vel_list.append(pipe)
fail_min_vel = True
elif ep.ENgetlinkvalue(pipe + 1, 9) > max_vel:
fail_max_vel_list.append(pipe)
fail_max_vel = True
i = 0
for diameter in diameter_array:
i += 1
if diameter <= 0:
negative_diameter_list.append(i)
negative_diameter = True
print('Fail pressure list (nodes):', fail_pressure_list)
print('Lower than min velocity list (links):', fail_min_vel_list)
print('Higher than max velocity list (links):', fail_max_vel_list)
if fail_pressure or fail_min_vel or fail_max_vel or negative_diameter:
return False
else:
return True
def HydrantRating(MyNode, Demands):
#Open the EPANET toolkit & hydraulics solver
em.ENopen("example2.inp", "example2.rpt")
em.ENopenH()
# Get the index of the node of interest
nodeindex = em.ENgetnodeindex(MyNode)
rating = []
# Iterate over all demands
for dem in Demands:
em.ENsetnodevalue(nodeindex, em.EN_BASEDEMAND, dem)
em.ENinitH(em.EN_NOSAVE)
em.ENrunH()
pressure = em.ENgetnodevalue(nodeindex, em.EN_PRESSURE)
rating.append(pressure)
# Close hydraulics solver & toolkit */
em.ENcloseH()
em.ENclose()
return rating
def simulation_supply(year, weatherforecast_kind, weatherforecast_accumulationtime, penetration_rate, control_type, number_simulation, original_epanet_file, original_swmm_file, irrigation_start, irrigation_end):
#created file names
name = original_epanet_file[:-4] + '_{}_{}_{}_{}_{}_{}'.format(year, weatherforecast_kind, weatherforecast_accumulationtime, penetration_rate, control_type, number_simulation)
epanet_file = name + '.inp'
epanet_report_file = name + '.rpt'
json_file_drainage = original_swmm_file[:-4] + '_{}_{}_{}_{}_{}_{}.json'.format(year, weatherforecast_kind, weatherforecast_accumulationtime, penetration_rate, control_type, number_simulation)
json_file = name + '.json'
#read in results from urban drainage simulation
with open('results/{}'.format(json_file_drainage)) as myfile:
data = json.load(myfile)
water_demand_supply = data['water_demand_supply'][0]
water_harvesting = data['water_harvesting'][0]
#read in classifcation houses to junctions
if os.name == 'nt':
classification_path = 'water\\Classification_Houses_Junctions.csv'
else:
classification_path = 'water/Classification_Houses_Junctions.csv'
classification = pd.read_csv(classification_path, sep=';', header=None, names=['PropertyID','JunctionID'])
classification.set_index('PropertyID',inplace=True)
#read in daily weather data
if os.name == 'nt':
daily_weather_path = 'weather\\weather_daily_2015.csv'
else:
daily_weather_path = 'weather/weather_daily_2015.csv'
daily_weather = pd.read_csv(daily_weather_path, sep=';', header=0)
daily_weather['Date'] = pd.to_datetime(daily_weather['Date'], format='%d.%m.%Y')
daily_weather.set_index('Date', inplace=True)
#set irrigation period
start_irrigation = pd.to_datetime('{}.{}.{}'.format(irrigation_start[1], irrigation_start[0], year), format='%d.%m.%Y')
end_irrigation = pd.to_datetime('{}.{}.{}'.format(irrigation_end[1], irrigation_end[0], year), format='%d.%m.%Y') + pd.Timedelta(hours = 23)
duration = end_irrigation - start_irrigation
hours = int(duration.days * 24 + (duration.seconds/3600))
#set daily demand pattern
patterns = {}
patterns['March'] = [0.40, 0.30, 0.15, 0.10, 0.15, 0.50, 1.00, 1.50, 1.60, 1.50, 1.30, 1.20, 1.30, 1.20, 1.15, 1.20, 1.20, 1.40, 1.60, 1.50, 1.20, 1.05, 0.90, 0.60]
patterns['April'] = [0.35, 0.20, 0.20, 0.20, 0.35, 0.70, 1.20, 1.40, 1.40, 1.30, 1.25, 1.20, 1.30, 1.20, 1.25, 1.25, 1.45, 1.70, 1.60, 1.30, 1.10, 0.95, 0.70, 0.45]
patterns['May'] = [0.40, 0.30, 0.30, 0.30, 0.40, 0.85, 1.25, 1.35, 1.30, 1.25, 1.20, 1.15, 1.25, 1.20, 1.15, 1.25, 1.40, 1.65, 1.50, 1.30, 1.15, 0.95, 0.70, 0.45]
patterns['June'] = [0.45, 0.45, 0.40, 0.40, 0.40, 0.80, 1.25, 1.40, 1.30, 1.25, 1.15, 1.15, 1.20, 1.20, 1.15, 1.15, 1.30, 1.60, 1.55, 1.30, 1.10, 0.90, 0.70, 0.45]
patterns['July'] = [0.40, 0.40, 0.30, 0.30, 0.40, 0.80, 1.20, 1.45, 1.35, 1.25, 1.20, 1.25, 1.20, 1.15, 1.05, 1.15, 1.30, 1.60, 1.50, 1.30, 1.15, 1.05, 0.80, 0.45]
patterns['August'] = [0.30, 0.20, 0.15, 0.20, 0.35, 0.70, 1.30, 1.50, 1.45, 1.40, 1.25, 1.25, 1.20, 1.15, 1.05, 1.15, 1.40, 1.70, 1.60, 1.35, 1.15, 1.00, 0.75, 0.45]
patterns['September'] = [0.30, 0.20, 0.15, 0.15, 0.30, 0.75, 1.35, 1.55, 1.50, 1.35, 1.25, 1.20, 1.25, 1.25, 1.10, 1.15, 1.40, 1.65, 1.55, 1.30, 1.15, 1.00, 0.75, 0.40]
#set monthly demand variation factor
month_demand = {}
month_demand['January'] = 0.85
month_demand['February'] = 0.95
month_demand['March'] = 1.00
month_demand['April'] = 1.05
month_demand['May'] = 1.20
month_demand['June'] = 1.10
month_demand['July'] = 1.05
month_demand['August'] = 1.00
month_demand['September'] = 1.00
month_demand['October'] = 0.95
month_demand['November'] = 0.95
month_demand['December'] = 0.90
#set monthly spring variation factor
month_source = {}
month_source['January'] = 0.80
month_source['February'] = 0.75
month_source['March'] = 0.70
month_source['April'] = 0.90
month_source['May'] = 1.15
month_source['June'] = 1.20
month_source['July'] = 1.15
month_source['August'] = 1.15
month_source['September'] = 1.20
month_source['October'] = 1.10
month_source['November'] = 1.00
month_source['December'] = 0.90
#add rainbarrels to epanet file and change year:
f = open(original_epanet_file) #read in
success, val = read_write_swmm.swmm_input_read(f)
if not success:
print(val)
sys.exit(1)
val, house_to_node = modify_epanet_input.implement_irrigation_to_node(val, water_demand_supply, classification, hours)
f = open(epanet_file,'w')
read_write_swmm.swmm_input_write(f,val)
f.close()
#set initial values
node_with_rainbarrel = {} #for node with rainbarrels
demand_pattern_name = 'Demand' #pattern for water demand
water_source_name = 'spring' #node name for water source
#open Epanet Toolkit
en.ENopen(epanet_file, epanet_report_file) #, epanet_bin_file) #open Epanet Toolkit with files
#initiate epanet simulation
en.ENopenH() #open hydraulic solver
en.ENinitH(en.EN_SAVE) #save hydraulic results to bin file
t = start_irrigation #set start time
#set rainbarrel patterns
peak_demand_hour = 17
#get rain barrel control parameters
for key, (junction) in house_to_node.items():
patternid_node = en.ENgetpatternindex('Demand_{}'.format(junction))
node_id = en.ENgetnodeindex(junction)
node_with_rainbarrel[key] = patternid_node, node_id
#get water source index
water_source = en.ENgetnodeindex(water_source_name) #node index
water_source_abstraction = en.ENgetnodevalue(water_source, en.EN_BASEDEMAND) # get base demand
#get Demand pattern index
demand = en.ENgetpatternindex(demand_pattern_name)
#create dictonaries for results
number_nodes = en.ENgetcount(en.EN_NODECOUNT)
water_age = {}
for index in range(1, number_nodes+1):
key = en.ENgetnodeid(index).decode('utf-8')
water_age[key] = {}
pressure_nodes = copy.deepcopy(water_age)
pressure_nodes_peak = copy.deepcopy(water_age)
day = 0
total_demand = 0
while t < end_irrigation: #important that t is as long as duration to read hydraulic results file
en.ENrunH() #run time step
timedelta = en.ENsimtime() #get current simulation time
t = start_irrigation + pd.Timedelta(days = timedelta.days, seconds = timedelta.seconds) #combine it with real date
if t.hour == 23 and t.minute == 0 and t < end_irrigation: #check if new day, 23 because changes will be updated next time step at 0:00
date = t + pd.Timedelta(seconds = 3600) #to get beginning of day
month_name = date.month_name() #get month name
#get daily demand factors
month_factor_demand = month_demand[month_name] #get monthly factor
daily_factor_demand, daily_factor_irrigation = calculate_daily_demand_spring.calculate_demand(daily_weather.loc[date,'Tmean'], daily_weather.loc[date,'Rain']) #calculate daily demand factor based on temperature
demand_factor = month_factor_demand * daily_factor_demand #calculate demand factor for changing pattern
irrigation_factor = month_factor_demand * daily_factor_irrigation #calculate irrigation factor for changing pattern
#get daily source factors
month_factor_source = month_source[month_name] #get monthly factor
daily_factor_source = calculate_daily_demand_spring.calculate_spring(daily_weather.loc[date,'Tmean'],daily_weather.loc[date,'Rain']) #calculate daily source factor based on temperature
source_factor = month_factor_source * daily_factor_source #calculate month factor for changing base source
#set daily demand pattern
demand_pattern = patterns[t.month_name()] #get daily pattern depending on month
daily_demand_pattern = [i * demand_factor for i in demand_pattern] #change pattern
en.ENsetpattern(demand, daily_demand_pattern) #set pattern
#set daily water source pouring
daily_source_abstraction = source_factor * water_source_abstraction #change -demand
en.ENsetnodevalue(water_source, 1, daily_source_abstraction) #set demand
#reset demand patterns for node with rain barrel - necessary for multiple rain barrels at one node
for key, (pattern_node_id, node_id) in node_with_rainbarrel.items():
en.ENsetpattern(pattern_node_id, daily_demand_pattern)
#set individual rain barrel pattern
for key, (pattern_node_id, node_id) in node_with_rainbarrel.items():
water_demand = water_demand_supply[key][str(date)] #get irrigation demand for rain barrels m3
water_harvested = water_harvesting[key][str(date)] #get saved water m3
#set filling time rain barrel
pattern_time = 23
#get base demand for node
base_demand = en.ENgetnodevalue(node_id,en.EN_BASEDEMAND)
#get actual pattern for node with rain barrel
actual_pattern_value_filling = en.ENgetpatternvalue(pattern_node_id, pattern_time)
actual_pattern_value_peak = en.ENgetpatternvalue(pattern_node_id, peak_demand_hour+1)
#set filling of rain barrel
water_abstraction_filling = actual_pattern_value_filling * base_demand
water_abstraction_filling_new = water_abstraction_filling + water_demand / (60*60) * 1000 #calculate l/s
water_abstraction_filling_new_pattern = water_abstraction_filling_new / base_demand
en.ENsetpatternvalue(pattern_node_id, pattern_time, water_abstraction_filling_new_pattern) #change pattern
#set reduction at peak hour
water_abstraction_peak = actual_pattern_value_peak * base_demand * 3600
water_abstraction_peak_without = daily_demand_pattern[peak_demand_hour] * base_demand * 3600
water_abstraction_irrigation_total = sum([i*base_demand for i in daily_demand_pattern]) * 3600 * irrigation_factor
water_reduction_irrigation_poss = (water_demand + water_harvested) * 1000 #calculate l/s
water_reduction_irrigation = min(water_reduction_irrigation_poss, 0.4*water_abstraction_irrigation_total)
water_reduction_total = max(water_abstraction_peak - water_reduction_irrigation, water_abstraction_peak_without * 0.6) / 3600
water_redcution_new_pattern = water_reduction_total / base_demand
en.ENsetpatternvalue(pattern_node_id, peak_demand_hour+1, water_redcution_new_pattern) #change pattern
if day == 0:
total_demand += base_demand
day += 1
#get pressure results at peak demand (17h -> reducing irrigation demand)
if t.hour == 17:
for index in range(1, number_nodes+1):
key = en.ENgetnodeid(index).decode('utf-8') #get key (nodeid)
pressure_nodes_peak[key].update({str(t): en.ENgetnodevalue(index, en.EN_PRESSURE)}) #get pressure for node
#get pressure results at filling time rainbarrels (22-23h -> because at 23 irrigation starts)
if t.hour == 22:
for index in range(1, number_nodes+1):
key = en.ENgetnodeid(index).decode('utf-8') #get key (nodeid)
pressure_nodes[key].update({str(t): en.ENgetnodevalue(index, en.EN_PRESSURE)}) #get pressure for node
en.ENnextH() #next time step
en.ENcloseH() #close hydraulic solver
en.ENopenQ() #open quality solver
en.ENinitQ(en.EN_SAVE) #save quality results to bin file
t = start_irrigation #set start time
while t < end_irrigation: #t should be lower than from hydraulic results (< instead of <=)
en.ENrunQ() #run quality time step
timedelta = en.ENsimtime() #get current simulation time
t = start_irrigation + pd.Timedelta(days = timedelta.days, seconds = timedelta.seconds) #combine it with real date
#get water age results at end of the day
if t.hour == 23:
for index in range(1, number_nodes+1):
key = en.ENgetnodeid(index).decode('utf-8') #get key (nodeid)
water_age[key].update({str(t): en.ENgetnodevalue(index, en.EN_QUALITY)}) #get pressure for node
en.ENstepQ() #next quality time step
en.ENcloseQ() #close quality solver
en.ENclose() #close epanet toolkit and delete files
total_water_results = {}
total_water_results['pressure'] = [pressure_nodes]
total_water_results['pressure_peak'] = [pressure_nodes_peak]
total_water_results['water_age'] = [water_age]
results_json = json.dumps(total_water_results)
f = open('results/{}'.format(json_file),"w")
f.write(results_json)
f.close()
os.remove(epanet_report_file) #delete report file
os.remove(epanet_file) #delete epanet file
em.ENopen(inpName + '.inp', inpName + '.rpt')
#print(inpName)
demMult = em.ENgetoption(em.EN_DEMANDMULT)
### get avg pressure
nnodes = em.ENgetcount(em.EN_NODECOUNT)
junInds = []
for index in range(1, nnodes + 1):
if em.ENgetnodetype(index) == em.EN_JUNCTION:
junInds.append(index)
junPres = [[] for q in range(len(junInds))]
time = []
## RUN SIM
em.ENopenH()
em.ENinitH(0)
while True:
em.ENrunH()
t = em.ENsimtime()
time.append(
datetime.timedelta.total_seconds(t)) #convert time delta to seconds
# Retrieve hydraulic results for time t
# #Tank heights
# for i in range(0,len(tankInds)):
# p=em.ENgetnodevalue(tankInds[i], em.EN_PRESSURE )
# tankLvls[i].append(p)
#