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new_ev_scheduler_v3.py
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new_ev_scheduler_v3.py
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import numpy as np
import cvxpy as cp # type: ignore
def get_c_vpp(available_v2g_ev_lst, c_vpp_dept_times_lst, c_vpp_soc_init_lst, c_vpp_I_EV_charging, c_vpp_D_EV_charging, c_vpp_D_EV_charging_count, c_vpp_pv_diff_lst, N_EV, p_im, current_time, tau):
# Constants
ALPHA_C = 11
ALPHA_D = -11
B_CAP = 80
ETA_C = 0.98
ETA_D = 0.98
FINAL_SOC = 0.97
DAY_HRS = 24
# Input
I_EV_charging = c_vpp_I_EV_charging
D_EV_charging = c_vpp_D_EV_charging
D_EV_charging_count = c_vpp_D_EV_charging_count
# Variables
#SELECT_M = cp.Variable((N_EV, DAY_HRS),boolean=True)
AD = cp.Variable((N_EV, DAY_HRS),nonpos=True)
AC = cp.Variable((N_EV, DAY_HRS),nonneg=True)
y = cp.Variable((N_EV, DAY_HRS))
soc_t = cp.Variable((N_EV, DAY_HRS),nonneg=True)
lax_t = cp.Variable((N_EV, DAY_HRS),nonneg=True)
z = cp.Variable(DAY_HRS)
constraints = []
for ev in range(N_EV):
for t in range(current_time):
#constraints += [SELECT_M[ev][t] == 0]
constraints += [AD[ev][t] == 0]
constraints += [AC[ev][t] == 0]
constraints += [y[ev][t] == 0]
constraints += [soc_t[ev][t] == 0]
constraints += [lax_t[ev][t] == 0]
for ev_idx, ev in enumerate(available_v2g_ev_lst):
for t in range(current_time, ev.departure_time):
#print('TTT ', t)
if (D_EV_charging[ev_idx][t] < 0):
if(np.abs(D_EV_charging[ev_idx][t]) > np.abs(ALPHA_D)):
D_EV_charging[ev_idx][t] = ALPHA_D
constraints += [AD[ev_idx][t] >= D_EV_charging[ev_idx][t] * D_EV_charging_count[ev_idx][t] ]
#constraints += [AD[ev_idx][t] >= D_EV_charging[ev_idx][t] * SELECT_M[ev_idx][t]]
constraints += [AC[ev_idx][t] <= I_EV_charging[ev_idx][t] * ALPHA_C ]
#constraints += [AC[ev_idx][t] <= I_EV_charging[ev_idx][t] * (1-SELECT_M[ev_idx][t]) * ALPHA_C]
#D_EV_charging[ev_idx][t] = 1
else:
constraints += [AD[ev_idx][t] == 0]
constraints += [AC[ev_idx][t] <= I_EV_charging[ev_idx][t] * ALPHA_C]
constraints += [y[ev_idx][t] == (AC[ev_idx][t] + AD[ev_idx][t])]
if (t == current_time):
constraints += [soc_t[ev_idx][t] == c_vpp_soc_init_lst[ev_idx] + ((I_EV_charging[ev_idx][t] * AC[ev_idx][t] * ETA_C)/B_CAP + (D_EV_charging_count[ev_idx][t] * (AD[ev_idx][t]/ETA_D))/B_CAP)]
else:
constraints += [soc_t[ev_idx][t] == soc_t[ev_idx][t-1] + ((I_EV_charging[ev_idx][t] * AC[ev_idx][t] * ETA_C)/B_CAP + (D_EV_charging_count[ev_idx][t] * (AD[ev_idx][t]/ETA_D))/B_CAP)]
constraints += [soc_t[ev_idx][t] >= (1-FINAL_SOC)]
#constraints += [soc_t[ev_idx][t] <= (FINAL_SOC)]
constraints += [lax_t[ev_idx][t] == I_EV_charging[ev_idx][t] * (((c_vpp_dept_times_lst[ev_idx]-(t+1)) - (((FINAL_SOC - soc_t[ev_idx][t])*B_CAP)/(ALPHA_C*ETA_C))))]
if ((t+1) < ev.departure_time):
constraints += [lax_t[ev_idx][t] >= 0.001]
#constraints += [lax_t[ev_idx][t] >= 0.0001]
#if (t == (ev.departure_time - 1)):
# constraints += [soc_t[ev_idx][t] <= FINAL_SOC]
#constraints += [cp.sum(AD[ev_idx]) <= tau]
for ev_idx, ev in enumerate(available_v2g_ev_lst):
for t in range(ev.departure_time, DAY_HRS):
#constraints += [SELECT_M[ev_idx][t] == 0]
constraints += [AD[ev_idx][t] == 0]
constraints += [AC[ev_idx][t] == 0]
constraints += [y[ev_idx][t] == 0]
constraints += [soc_t[ev_idx][t] == 0]
constraints += [lax_t[ev_idx][t] == 0]
for t in range(DAY_HRS):
constraints += [z[t] == cp.sum(y, axis=0)[t]]
c_vpp = np.sum(c_vpp_pv_diff_lst - z) @ p_im.T
obj = cp.Maximize(c_vpp)
problem = cp.Problem(obj, constraints)
problem.solve(cp.MOSEK, mosek_params = {'MSK_IPAR_NUM_THREADS': 8, 'MSK_IPAR_BI_MAX_ITERATIONS': 2_000_000, "MSK_IPAR_INTPNT_MAX_ITERATIONS": 800}, verbose=False)
if problem.status != 'optimal':
#raise Exception("Optimal schedule not found")
print("!!! Optimal schedule not found")
#print('AD ', AD.value)
#print("EV SCHEDD ", y.value)
#print('SOCCC AFTER CHARGE ',soc_t.value)
#print('=================================')
return y.value
def get_c_vpp_input(available_ev_lst, E_im_price, E_VPP, current_time, tau):
DAY_HRS = 24
c_vpp_dept_times_lst = []
c_vpp_soc_init_lst = []
c_vpp_I_EV_charging = []
c_vpp_D_EV_charging = []
c_vpp_D_EV_charging_count = []
p_im = []
c_vpp_pv_diff_lst = []
for idx, ev in enumerate(available_ev_lst):
if (ev != 0 and ev.completed == False):
temp_I_EV_charging = []
temp_D_EV_charging = []
temp_D_EV_charging_count = []
c_vpp_dept_times_lst.append(ev.departure_time)
c_vpp_soc_init_lst.append(ev.soc_t)
for t in range(DAY_HRS):
if (t >= 24):
t = 23
#if((t >= ev.departure_time) or (t < ev.arrival_time)):
if((t >= ev.departure_time) or (t < current_time)):
temp_I_EV_charging.append(0)
temp_D_EV_charging.append(0)
temp_D_EV_charging_count.append(0)
else:
temp_I_EV_charging.append(1)
if (ev.allow_discharge == True):
if ( (t >= (ev.arrival_time)) and (t <= (ev.arrival_time + (tau - 1))) ):
# since contract duration is 1 so discharge MUST be done within first hour
if(ev.new_v2g_val != -1000):
temp_D_EV_charging.append(-1 * ev.new_v2g_val)
temp_D_EV_charging_count.append(1)
else:
temp_D_EV_charging.append(-1 * ev.remaining_discharge_e)
temp_D_EV_charging_count.append(1)
else:
temp_D_EV_charging.append(0)
temp_D_EV_charging_count.append(0)
else:
temp_D_EV_charging.append(0)
temp_D_EV_charging_count.append(0)
c_vpp_I_EV_charging.append(temp_I_EV_charging)
c_vpp_D_EV_charging.append(temp_D_EV_charging)
c_vpp_D_EV_charging_count.append(temp_D_EV_charging_count)
for t in range(DAY_HRS):
if(t < current_time or t >= c_vpp_dept_times_lst[-1]):
p_im.append(0)
c_vpp_pv_diff_lst.append(0)
else:
p_im.append(E_im_price[t])
c_vpp_pv_diff_lst.append(E_VPP[t])
p_im = np.array(p_im)
c_vpp_pv_diff_lst = np.array(c_vpp_pv_diff_lst)
c_vpp_I_EV_charging = np.vstack(c_vpp_I_EV_charging)
c_vpp_D_EV_charging = np.vstack(c_vpp_D_EV_charging)
c_vpp_D_EV_charging_count = np.vstack(c_vpp_D_EV_charging_count)
#print('current_time ', current_time)
#print('I_EV ',c_vpp_I_EV_charging)
#print('D_EV ',c_vpp_D_EV_charging)
#print('D_EV_count ',c_vpp_D_EV_charging_count)
#print('SOC BEFORE',c_vpp_soc_init_lst)
#print('DEPT_T ',c_vpp_dept_times_lst)
return c_vpp_dept_times_lst, c_vpp_soc_init_lst, c_vpp_I_EV_charging, c_vpp_D_EV_charging, c_vpp_D_EV_charging_count, p_im, c_vpp_pv_diff_lst
def offer_discharge_incentive(seed, available_v2g_ev_lst, current_time, E_im_price, E_VPP, tau):
#tau = 3
DAY_HRS = 24
rng = np.random.default_rng(seed)
c_vpp_dept_times_lst, c_vpp_soc_init_lst, c_vpp_I_EV_charging, c_vpp_D_EV_charging, c_vpp_D_EV_charging_count, p_im, c_vpp_pv_diff_lst = get_c_vpp_input(available_v2g_ev_lst, E_im_price, E_VPP, current_time, tau)
N_EV = c_vpp_I_EV_charging.shape[0]
new_EV_schedule = get_c_vpp(available_v2g_ev_lst, c_vpp_dept_times_lst, c_vpp_soc_init_lst, c_vpp_I_EV_charging, c_vpp_D_EV_charging, c_vpp_D_EV_charging_count, c_vpp_pv_diff_lst, N_EV, p_im, current_time, tau)
return new_EV_schedule
def main(seed, available_v2g_ev_lst, current_time, E_im_price, E_VPP, tau):
return offer_discharge_incentive(seed, available_v2g_ev_lst, current_time, E_im_price, E_VPP, tau)