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fuzzy_controller.py
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226 lines (171 loc) Β· 9.82 KB
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'''
Created on 15 de ago de 2017
@author: fvj
'''
class Controller():
def __init__(self, grid, battery, load):
self.grid = grid
self.battery = battery
self.load = load
self.fuzzy_inputs = self.setup_inputs()
self.fuzzy_outputs = self.setup_outputs()
self.rules = self.setup_rules()
def setup_inputs(self):
model = {}
model['battery_charge'] = TriangularFuzzySet(['NB', 'NS', 'ZE', 'PS', 'PB'], 0, self.battery.max_charge)
model['load_power'] = TriangularFuzzySet(['NB', 'NS', 'ZE', 'PS', 'PB'], min(self.load.demand_prediction), max(self.load.demand_prediction))
return model
def setup_outputs(self):
model = {}
model['battery_power'] = TriangularFuzzySet(['NB', 'NS', 'ZE', 'PS', 'PB'], self.battery.min_power, self.battery.max_power)
return model
def setup_rules(self): # or and not
rules = []
rules.append( ({'load_power':'NB'}, {'battery_power':'PB'}) )
rules.append( ({'load_power':'NS'}, {'battery_power':'PS'}) )
rules.append( ({'load_power':'ZE'}, {'battery_power':'ZE'}) )
rules.append( ({'load_power':'PS'}, {'battery_power':'NS'}) )
rules.append( ({'load_power':'PB'}, {'battery_power':'NB'}) )
rules.append( ({'battery_charge':'NB'}, {'battery_power':'NB'}) )
rules.append( ({'battery_charge':'PB'}, {'battery_power':'PS'}) )
# rules.append( ({'load_power':'NB'}, {'battery_power':'PB'}) )
# rules.append( ({'load_power':'NS'}, {'battery_power':'PS'}) )
# rules.append( ({'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'load_power':'PS'}, {'battery_power':'NS'}) )
# rules.append( ({'load_power':'PB'}, {'battery_power':'NB'}) )
#
# rules.append( ({'battery_charge':'NB'}, {'battery_power':'NB'}) )
# rules.append( ({'battery_charge':'PS'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'PB'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'NB', 'load_power':'NB'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'NB', 'load_power':'NS'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'NB', 'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'NB', 'load_power':'PS'}, {'battery_power':'NS'}) )
# rules.append( ({'battery_charge':'NB', 'load_power':'PB'}, {'battery_power':'NB'}) )
#
# rules.append( ({'battery_charge':'NS', 'load_power':'NB'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'NS', 'load_power':'NS'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'NS', 'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'NS', 'load_power':'PS'}, {'battery_power':'NS'}) )
# rules.append( ({'battery_charge':'NS', 'load_power':'PB'}, {'battery_power':'NB'}) )
#
# rules.append( ({'battery_charge':'ZE', 'load_power':'NB'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'ZE', 'load_power':'NS'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'ZE', 'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'ZE', 'load_power':'PS'}, {'battery_power':'NS'}) )
# rules.append( ({'battery_charge':'ZE', 'load_power':'PB'}, {'battery_power':'NS'}) )
#
# rules.append( ({'battery_charge':'PS', 'load_power':'NB'}, {'battery_power':'PB'}) )
# rules.append( ({'battery_charge':'PS', 'load_power':'NS'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'PS', 'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'PS', 'load_power':'PS'}, {'battery_power':'NS'}) )
# rules.append( ({'battery_charge':'PS', 'load_power':'PB'}, {'battery_power':'NS'}) )
#
# rules.append( ({'battery_charge':'PB', 'load_power':'NB'}, {'battery_power':'PB'}) )
# rules.append( ({'battery_charge':'PB', 'load_power':'NS'}, {'battery_power':'PS'}) )
# rules.append( ({'battery_charge':'PB', 'load_power':'ZE'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'PB', 'load_power':'PS'}, {'battery_power':'ZE'}) )
# rules.append( ({'battery_charge':'PB', 'load_power':'PB'}, {'battery_power':'ZE'}) )
return rules
def dispatch_battery(self):
# self.rule_based_controller()
self.fuzzy_inference_sytem()
def get_control_output(self, f_load_power, f_battery_charge):
result = { str(set_name):0 for set_name in self.fuzzy_outputs['battery_power'].fuzzy_sets.keys() }
for rule in self.rules:
if 'load_power' in rule[0]:
load_power_membership = f_load_power[rule[0]['load_power']]
else:
load_power_membership = 1
if 'battery_charge' in rule[0]:
battery_charge_membership = f_battery_charge[rule[0]['battery_charge']]
else:
battery_charge_membership = 1
and_membership = min(load_power_membership, battery_charge_membership)
result[rule[1]['battery_power']] = max(and_membership, result[rule[1]['battery_power']])
return result
def fuzzy_inference_sytem(self):
f_load_power = self.fuzzy_inputs['load_power'].fuzzify(self.load.power)
f_battery_charge = self.fuzzy_inputs['battery_charge'].fuzzify(self.battery.current_charge)
f_battery_power = self.get_control_output(f_load_power, f_battery_charge)
battery_power = self.fuzzy_outputs['battery_power'].defuzzify(f_battery_power)
self.battery.power = battery_power
def rule_based_controller(self):
bat_soc = self.battery.current_charge/self.battery.max_charge
if self.load.power > 0 and bat_soc < 0.9:
self.battery.power = self.battery.min_power
elif self.load.power < 0 and bat_soc > 0.1:
self.battery.power = self.battery.max_power
else:
self.battery.power = 0
def balance_with_grid(self):
self.grid.power -= self.get_power_sum()
def get_power_sum(self):
power_sum = 0
power_sum += self.grid.power
power_sum += self.battery.power
power_sum += self.load.power
return power_sum
def dispatch(self):
self.dispatch_battery()
self.balance_with_grid()
class TriangularFuzzySet():
def __init__(self, fuzzy_sets, min_value, max_value):
self.min_value = min_value
self.max_value = max_value
self.fuzzy_sets = self.setup_sets(fuzzy_sets)
def setup_sets(self, set_names):
result = {}
n = len(set_names)
value_range = self.max_value - self.min_value
for i in range(n):
ramp_len = value_range/(n-1)
high_v = self.min_value + i*ramp_len
min_v = high_v - ramp_len
max_v = high_v + ramp_len
result[set_names[i]] = TriangularFunction(min_v,high_v,max_v)
return result
def fuzzify(self, value):
result = {}
for set_name, fuzzy_function in self.fuzzy_sets.items():
result[set_name] = fuzzy_function.interpolate(value)
return result
def defuzzify(self, fuzzy_memberships):
return self.centroid(fuzzy_memberships)
def centroid(self, fuzzy_memberships):
points = self.get_sampled_membership(fuzzy_memberships, 300)
membership_total_sum = sum(point[1] for point in points)
membership_area_sum = sum(point[0]*point[1] for point in points)
# if membership_total_sum == 0:
# raise Exception('TODO')
return membership_area_sum/membership_total_sum
def get_sampled_membership(self, fuzzy_memberships, sample_points):
value_range = self.max_value - self.min_value
value = self.min_value - value_range
points = []
while (value < self.max_value + value_range):
membership = 0
for set_name, fuzzy_function in self.fuzzy_sets.items():
membership = max(membership, fuzzy_function.saturate(value, fuzzy_memberships[set_name]))
points.append( (value,membership) )
value += value_range/sample_points
return points
def get_membership(self, value, set_name):
for name, fuzzy_function in self.fuzzy_sets.items():
if name == set_name:
return fuzzy_function.interpolate(value)
raise Exception('No such set: \'{}\' ({})'.format(set_name, self.fuzzy_sets.keys()))
class TriangularFunction():
def __init__(self, min_value, high_point, max_value):
self.min_value = min_value
self.high_point = high_point
self.max_value = max_value
def interpolate(self, value):
if value >= self.min_value and value < self.high_point:
return (value-self.min_value)/(self.high_point-self.min_value)
elif value >= self.high_point and value < self.max_value:
return (self.max_value-value)/(self.max_value-self.high_point)
else:
return 0
def saturate(self, value, membership):
return min(membership, self.interpolate(value))