def get_basics(Horizon_T, day):
AMB_network = top(network="ABM")
AMB_network = add_loads_to_topology(AMB_network)
AMB_network = add_generators_to_topology(AMB_network)
H, h = AMB_network.H, AMB_network.h
print("Topology loaded")
"""
Tweak case : add a fake generator
"""
node_name = "MDN"
AMB_network.add_generator(
Generator("diesel_gen",
node_name,
0,
0,
Pmax=200,
Pmin=0,
marginal_cost=[0, 0]))
"""
Get the load data
"""
d = get_load_matrix(AMB_network, day, Horizon_T)
d = tweak_d(d, load_factor=1, index_to_tweak=10, load_factor_for_node=1)
print("Load historical data loaded and tweaked")
"""
Get the bid matrices
"""
b, P_max, P_min = get_producers_matrices(AMB_network, day, Horizon_T)
print("Load historical bids")
"""
Load now the topology of generators
"""
Mn = AMB_network.Mn
return H, h, Mn, b, P_max, P_min, d
def launch_model():
AMB_network = top(network="ABM")
"""
Create loads on each node
"""
Existing_sub_nodes = ld.get_existing_subnodes()
historical_loads = ld.get_historical_loads()
Simp_nodes_dict = ld.get_nodes_to_subnodes()
Simp_nodes_dict["MAN"] = ["MAN2201"]
Existing_sub_nodes.append("MAN2201")
nodes_to_index = pd.read_csv(stored_path.main_path +
'/data/ABM/ABM_Nodes.csv')
for i, node in enumerate(AMB_network.names_2_nodes.keys()):
# print("Load added at node : " + node)
index = nodes_to_index[nodes_to_index["Node names"] ==
node]["Node index"].values[0]
load = Load(node, node, index, type="real_load")
load.add_load_data(historical_loads, Simp_nodes_dict,
Existing_sub_nodes)
AMB_network.add_load(load)
file_path = stored_path.main_path + '/data/generators/generator_adjacency_matrix_dict1.json'
with open(file_path) as f:
data = json.loads(f.read())
number_of_added_generators = 0
for name_generator in data.keys():
L_ = data[name_generator]
try:
if type(L_[0]) != float:
if not math.isnan(L_[-2]):
if L_[-1] == "Gas" or L_[-1] == "Biogas":
add = 35
if L_[-1] == "Geothermal":
add = 10
if L_[-1] == "Coal":
add = 50
if L_[-1] == "Diesel":
add = 150
if L_[-1] == 'Hydro':
P_min = 0.1 * L_[-2]
else:
P_min = 0
g = Generator(name_generator,
L_[0],
0,
L_[-1],
Pmax=L_[-2],
Pmin=P_min,
marginal_cost=add + np.array(L_[1]))
AMB_network.add_generator(g)
number_of_added_generators += 1
except:
pass
node_name = "MDN"
# index = 10
AMB_network.add_generator(
Generator("diesel_gen",
node_name,
0,
0,
Pmax=200,
Pmin=0,
marginal_cost=[0, 0]))
# AMB_network.generators[10]
"""
get d_t for day 12 and trading period 1
"""
Horizon_T = 48
day = 2
d = []
for k, node in enumerate(AMB_network.loads.keys()):
d.append([])
for j in range(day * 48, day * 48 + Horizon_T):
d[k].append(
1 * 1000 *
AMB_network.loads[node][0].return_d(1 + j // 48, j % 48 + 1))
# d[1] = d[1]*2
d = np.array(d)
# # d[1] = d[1]*10
#
# import matplotlib.pyplot as plt
# plt.plot(sum(d))
# plt.show()
#
# sum(d[:,0])
# d = np.zeros((d.shape[0], Horizon_T))
# d = P_min
"""
Add topology specific characteristics
"""
n_generator = AMB_network.get_number_of_gen()
b = np.zeros((n_generator, Horizon_T))
P_max = np.zeros((n_generator, Horizon_T))
P_min = np.zeros((n_generator, Horizon_T))
for node in AMB_network.generators.keys():
for g in AMB_network.generators[node]:
for i, j in enumerate(range(day * 48, day * 48 + Horizon_T)):
if g.name == "diesel_gen":
pmax, pmin, a = 500, 0, 200
else:
pmax, pmin, a = LMP.get_P_min_a(g.name, 1 + j // 48,
j % 48 + 1, g.type)
P_max[g.index, i] = pmax
P_min[g.index, i] = pmin if g.type == "Hydro" else 0
b[g.index, i] = a if a > 0 else np.random.randint(0, 100)
print("Loading data done")
list_of_generator = {}
for node in AMB_network.generators.keys():
for g in AMB_network.generators[node]:
list_of_generator[g.index] = g
new_dict = {}
for key in sorted(list_of_generator.keys()):
new_dict[key] = list_of_generator[key]
H, h = AMB_network.H, AMB_network.h
Mn = AMB_network.Mn
save = d[10].copy()
save_d = d.copy()
d[10] = save
d = 1.3 * save_d.copy()
d[10] = save * 12.1
cost_of_battery = 200 * 1000 / (2 * 365)
model = run_program(d,
b,
P_max,
P_min,
H,
h,
Mn,
i_battery=None,
z_start=1,
cost_of_battery=cost_of_battery)
beta = np.array([[pyo.value(model.beta[t, i]) for i in range(Horizon_T)]
for t in range(H.shape[0])])
save_results(model, i_test=4)
print("\n___ OBJ ____")
print(pyo.value(model.obj))
if __name__ == '__main__':
"""
Real test
"""
from lmpnz.Network.Topology.Topology import Topology as top
import lmpnz.Network.PriceBids.Load.Load as ld
from lmpnz.Network.PriceBids.Generator.Generator import Generator
from lmpnz.Network.PriceBids.Load.Load import Load
from lmpnz.GuillaumeExample import LMP
import pandas as pd
import stored_path
import json
import math
AMB_network = top(network="ABM")
"""
Create loads on each node
"""
Existing_sub_nodes = ld.get_existing_subnodes()
historical_loads = ld.get_historical_loads()
Simp_nodes_dict = ld.get_nodes_to_subnodes()
Simp_nodes_dict["MAN"] = ["MAN2201"]
Existing_sub_nodes.append("MAN2201")
nodes_to_index = pd.read_csv(stored_path.main_path +
'/data/ABM/ABM_Nodes.csv')
for i, node in enumerate(AMB_network.names_2_nodes.keys()):
# print("Load added at node : " + node)
index = nodes_to_index[nodes_to_index["Node names"] ==
node]["Node index"].values[0]
load = Load(node, node, index, type="real_load")