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Updating pyomo model #5

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2cb5e08
Several changes
whart222 Jun 10, 2024
5f829ac
Reformatting with black
whart222 Jun 10, 2024
a428814
Updating gurobi mipgap parameter
whart222 Jun 11, 2024
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292 changes: 210 additions & 82 deletions uc_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,46 +3,85 @@
import sys

## Grab instance file from first command line argument
if len(sys.argv) == 1:
print("uc_model.py <data-file> [<solver>]")
sys.exit(0)
data_file = sys.argv[1]
if len(sys.argv) == 3:
solver_name = sys.argv[2]
else:
solver_name = "cbc"

print('loading data')
data = json.load(open(data_file, 'r'))
print("loading data")
data = json.load(open(data_file, "r"))

thermal_gens = data['thermal_generators']
renewable_gens = data['renewable_generators']
thermal_gens = data["thermal_generators"]
renewable_gens = data["renewable_generators"]

time_periods = {t+1 : t for t in range(data['time_periods'])}
time_periods = {t + 1: t for t in range(data["time_periods"])}

gen_startup_categories = {g : list(range(0, len(gen['startup']))) for (g, gen) in thermal_gens.items()}
gen_pwl_points = {g : list(range(0, len(gen['piecewise_production']))) for (g, gen) in thermal_gens.items()}
gen_startup_categories = {
g: list(range(0, len(gen["startup"]))) for (g, gen) in thermal_gens.items()
}
gen_pwl_points = {
g: list(range(0, len(gen["piecewise_production"])))
for (g, gen) in thermal_gens.items()
}

print('building model')
print("building model")
m = ConcreteModel()

m.cg = Var(thermal_gens.keys(), time_periods.keys())
m.pg = Var(thermal_gens.keys(), time_periods.keys(), within=NonNegativeReals)
m.rg = Var(thermal_gens.keys(), time_periods.keys(), within=NonNegativeReals)
m.pg = Var(thermal_gens.keys(), time_periods.keys(), within=NonNegativeReals)
m.rg = Var(thermal_gens.keys(), time_periods.keys(), within=NonNegativeReals)
m.pw = Var(renewable_gens.keys(), time_periods.keys(), within=NonNegativeReals)
m.ug = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)
m.vg = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)
m.wg = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)

m.dg = Var(((g,s,t) for g in thermal_gens for s in gen_startup_categories[g] for t in time_periods), within=Binary) ##
m.lg = Var(((g,l,t) for g in thermal_gens for l in gen_pwl_points[g] for t in time_periods), within=UnitInterval) ##

m.obj = Objective(expr=sum(
sum(
m.cg[g,t] + gen['piecewise_production'][0]['cost']*m.ug[g,t]
+ sum( gen_startup['cost']*m.dg[g,s,t] for (s, gen_startup) in enumerate(gen['startup']))
for t in time_periods)
for g, gen in thermal_gens.items() )
) #(1)
m.ug = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)
m.vg = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)
m.wg = Var(thermal_gens.keys(), time_periods.keys(), within=Binary)

m.dg = Var(
(
(g, s, t)
for g in thermal_gens
for s in gen_startup_categories[g]
for t in time_periods
),
within=Binary,
) ##
m.lg = Var(
((g, l, t) for g in thermal_gens for l in gen_pwl_points[g] for t in time_periods),
within=UnitInterval,
) ##

m.obj = Objective(
expr=sum(
sum(
m.cg[g, t]
+ gen["piecewise_production"][0]["cost"] * m.ug[g, t]
+ sum(
gen_startup["cost"] * m.dg[g, s, t]
for (s, gen_startup) in enumerate(gen["startup"])
)
for t in time_periods
)
for g, gen in thermal_gens.items()
)
) # (1)

m.demand = Constraint(time_periods.keys())
m.reserves = Constraint(time_periods.keys())
for t,t_idx in time_periods.items():
m.demand[t] = sum( m.pg[g,t]+gen['power_output_minimum']*m.ug[g,t] for (g, gen) in thermal_gens.items() ) + sum( m.pw[w,t] for w in renewable_gens ) == data['demand'][t_idx] #(2)
m.reserves[t] = sum( m.rg[g,t] for g in thermal_gens ) >= data['reserves'][t_idx] #(3)
for t, t_idx in time_periods.items():
m.demand[t] = (
sum(
m.pg[g, t] + gen["power_output_minimum"] * m.ug[g, t]
for (g, gen) in thermal_gens.items()
)
+ sum(m.pw[w, t] for w in renewable_gens)
== data["demand"][t_idx]
) # (2)
m.reserves[t] = (
sum(m.rg[g, t] for g in thermal_gens) >= data["reserves"][t_idx]
) # (3)

m.uptimet0 = Constraint(thermal_gens.keys())
m.downtimet0 = Constraint(thermal_gens.keys())
Expand All @@ -54,36 +93,82 @@
m.shutdownt0 = Constraint(thermal_gens.keys())

for g, gen in thermal_gens.items():
if gen['unit_on_t0'] == 1:
if gen['time_up_minimum'] - gen['time_up_t0'] >= 1:
m.uptimet0[g] = sum( (m.ug[g,t] - 1) for t in range(1, min(gen['time_up_minimum'] - gen['time_up_t0'], data['time_periods'])+1)) == 0 #(4)
elif gen['unit_on_t0'] == 0:
if gen['time_down_minimum'] - gen['time_down_t0'] >= 1:
m.downtimet0[g] = sum( m.ug[g,t] for t in range(1, min(gen['time_down_minimum'] - gen['time_down_t0'], data['time_periods'])+1)) == 0 #(5)
if gen["unit_on_t0"] == 1:
if gen["time_up_minimum"] - gen["time_up_t0"] >= 1:
m.uptimet0[g] = (
sum(
(m.ug[g, t] - 1)
for t in range(
1,
min(
gen["time_up_minimum"] - gen["time_up_t0"],
data["time_periods"],
)
+ 1,
)
)
== 0
) # (4)
elif gen["unit_on_t0"] == 0:
if gen["time_down_minimum"] - gen["time_down_t0"] >= 1:
m.downtimet0[g] = (
sum(
m.ug[g, t]
for t in range(
1,
min(
gen["time_down_minimum"] - gen["time_down_t0"],
data["time_periods"],
)
+ 1,
)
)
== 0
) # (5)
else:
raise Exception('Invalid unit_on_t0 for generator {}, unit_on_t0={}'.format(g, gen['unit_on_t0']))

m.logicalt0[g] = m.ug[g,1] - gen['unit_on_t0'] == m.vg[g,1] - m.wg[g,1] #(6)

startup_expr = sum(
sum( m.dg[g,s,t]
for t in range(
max(1,gen['startup'][s+1]['lag']-gen['time_down_t0']+1),
min(gen['startup'][s+1]['lag']-1,data['time_periods'])+1
)
)
for s,_ in enumerate(gen['startup'][:-1])) ## all but last
raise Exception(
"Invalid unit_on_t0 for generator {}, unit_on_t0={}".format(
g, gen["unit_on_t0"]
)
)

m.logicalt0[g] = m.ug[g, 1] - gen["unit_on_t0"] == m.vg[g, 1] - m.wg[g, 1] # (6)

startup_expr = sum(
sum(
m.dg[g, s, t]
for t in range(
max(1, gen["startup"][s + 1]["lag"] - gen["time_down_t0"] + 1),
min(gen["startup"][s + 1]["lag"] - 1, data["time_periods"]) + 1,
)
)
for s, _ in enumerate(gen["startup"][:-1])
) ## all but last
if isinstance(startup_expr, int):
pass
else:
m.startupt0[g] = startup_expr == 0 #(7)

m.rampupt0[g] = m.pg[g,1] + m.rg[g,1] - gen['unit_on_t0']*(gen['power_output_t0']-gen['power_output_minimum']) <= gen['ramp_up_limit'] #(8)

m.rampdownt0[g] = gen['unit_on_t0']*(gen['power_output_t0']-gen['power_output_minimum']) - m.pg[g,1] <= gen['ramp_down_limit'] #(9)


shutdown_constr = gen['unit_on_t0']*(gen['power_output_t0']-gen['power_output_minimum']) <= gen['unit_on_t0']*(gen['power_output_maximum'] - gen['power_output_minimum']) - max((gen['power_output_maximum'] - gen['ramp_shutdown_limit']),0)*m.wg[g,1] #(10)
m.startupt0[g] = startup_expr == 0 # (7)

m.rampupt0[g] = (
m.pg[g, 1]
+ m.rg[g, 1]
- gen["unit_on_t0"] * (gen["power_output_t0"] - gen["power_output_minimum"])
<= gen["ramp_up_limit"]
) # (8)

m.rampdownt0[g] = (
gen["unit_on_t0"] * (gen["power_output_t0"] - gen["power_output_minimum"])
- m.pg[g, 1]
<= gen["ramp_down_limit"]
) # (9)

shutdown_constr = (
gen["unit_on_t0"] * (gen["power_output_t0"] - gen["power_output_minimum"])
<= gen["unit_on_t0"]
* (gen["power_output_maximum"] - gen["power_output_minimum"])
- max((gen["power_output_maximum"] - gen["ramp_shutdown_limit"]), 0)
* m.wg[g, 1]
) # (10)

if isinstance(shutdown_constr, bool):
pass
Expand All @@ -105,50 +190,93 @@

for g, gen in thermal_gens.items():
for t in time_periods:
m.mustrun[g,t] = m.ug[g,t] >= gen['must_run'] #(11)
m.mustrun[g, t] = m.ug[g, t] >= gen["must_run"] # (11)

if t > 1:
m.logical[g,t] = m.ug[g,t] - m.ug[g,t-1] == m.vg[g,t] - m.wg[g,t] #(12)
m.logical[g, t] = (
m.ug[g, t] - m.ug[g, t - 1] == m.vg[g, t] - m.wg[g, t]
) # (12)

UT = min(gen['time_up_minimum'],data['time_periods'])
UT = min(gen["time_up_minimum"], data["time_periods"])
if t >= UT:
m.uptime[g,t] = sum(m.vg[g,t] for t in range(t-UT+1, t+1)) <= m.ug[g,t] #(13)
DT = min(gen['time_down_minimum'],data['time_periods'])
m.uptime[g, t] = (
sum(m.vg[g, t] for t in range(t - UT + 1, t + 1)) <= m.ug[g, t]
) # (13)
DT = min(gen["time_down_minimum"], data["time_periods"])
if t >= DT:
m.downtime[g,t] = sum(m.wg[g,t] for t in range(t-DT+1, t+1)) <= 1-m.ug[g,t] #(14)
m.startup_select[g,t] = m.vg[g,t] == sum(m.dg[g,s,t] for s,_ in enumerate(gen['startup'])) #(16)

m.gen_limit1[g,t] = m.pg[g,t]+m.rg[g,t] <= (gen['power_output_maximum'] - gen['power_output_minimum'])*m.ug[g,t] - max((gen['power_output_maximum'] - gen['ramp_startup_limit']),0)*m.vg[g,t] #(17)

if t < len(time_periods):
m.gen_limit2[g,t] = m.pg[g,t]+m.rg[g,t] <= (gen['power_output_maximum'] - gen['power_output_minimum'])*m.ug[g,t] - max((gen['power_output_maximum'] - gen['ramp_shutdown_limit']),0)*m.wg[g,t+1] #(18)
m.downtime[g, t] = (
sum(m.wg[g, t] for t in range(t - DT + 1, t + 1)) <= 1 - m.ug[g, t]
) # (14)
m.startup_select[g, t] = m.vg[g, t] == sum(
m.dg[g, s, t] for s, _ in enumerate(gen["startup"])
) # (16)

m.gen_limit1[g, t] = (
m.pg[g, t] + m.rg[g, t]
<= (gen["power_output_maximum"] - gen["power_output_minimum"]) * m.ug[g, t]
- max((gen["power_output_maximum"] - gen["ramp_startup_limit"]), 0)
* m.vg[g, t]
) # (17)

if t < len(time_periods):
m.gen_limit2[g, t] = (
m.pg[g, t] + m.rg[g, t]
<= (gen["power_output_maximum"] - gen["power_output_minimum"])
* m.ug[g, t]
- max((gen["power_output_maximum"] - gen["ramp_shutdown_limit"]), 0)
* m.wg[g, t + 1]
) # (18)

if t > 1:
m.ramp_up[g,t] = m.pg[g,t]+m.rg[g,t] - m.pg[g,t-1] <= gen['ramp_up_limit'] #(19)
m.ramp_down[g,t] = m.pg[g,t-1] - m.pg[g,t] <= gen['ramp_down_limit'] #(20

piece_mw1 = gen['piecewise_production'][0]['mw']
piece_cost1 = gen['piecewise_production'][0]['cost']
m.power_select[g,t] = m.pg[g,t] == sum( (piece['mw'] - piece_mw1)*m.lg[g,l,t] for l,piece in enumerate(gen['piecewise_production'])) #(21)
m.cost_select[g,t] = m.cg[g,t] == sum( (piece['cost'] - piece_cost1)*m.lg[g,l,t] for l,piece in enumerate(gen['piecewise_production'])) #(22)
m.on_select[g,t] = m.ug[g,t] == sum(m.lg[g,l,t] for l,_ in enumerate(gen['piecewise_production'])) #(23)

m.startup_allowed = Constraint(m.dg_index)
m.ramp_up[g, t] = (
m.pg[g, t] + m.rg[g, t] - m.pg[g, t - 1] <= gen["ramp_up_limit"]
) # (19)
m.ramp_down[g, t] = (
m.pg[g, t - 1] - m.pg[g, t] <= gen["ramp_down_limit"]
) # (20

piece_mw1 = gen["piecewise_production"][0]["mw"]
piece_cost1 = gen["piecewise_production"][0]["cost"]
m.power_select[g, t] = m.pg[g, t] == sum(
(piece["mw"] - piece_mw1) * m.lg[g, l, t]
for l, piece in enumerate(gen["piecewise_production"])
) # (21)
m.cost_select[g, t] = m.cg[g, t] == sum(
(piece["cost"] - piece_cost1) * m.lg[g, l, t]
for l, piece in enumerate(gen["piecewise_production"])
) # (22)
m.on_select[g, t] = m.ug[g, t] == sum(
m.lg[g, l, t] for l, _ in enumerate(gen["piecewise_production"])
) # (23)

m.startup_allowed = Constraint(m.dg.index_set())
for g, gen in thermal_gens.items():
for s,_ in enumerate(gen['startup'][:-1]): ## all but last
for s, _ in enumerate(gen["startup"][:-1]): ## all but last
for t in time_periods:
if t >= gen['startup'][s+1]['lag']:
m.startup_allowed[g,s,t] = m.dg[g,s,t] <= sum(m.wg[g,t-i] for i in range(gen['startup'][s]['lag'], gen['startup'][s+1]['lag'])) #(15)
if t >= gen["startup"][s + 1]["lag"]:
m.startup_allowed[g, s, t] = m.dg[g, s, t] <= sum(
m.wg[g, t - i]
for i in range(
gen["startup"][s]["lag"], gen["startup"][s + 1]["lag"]
)
) # (15)

for w, gen in renewable_gens.items():
for t, t_idx in time_periods.items():
m.pw[w,t].setlb(gen['power_output_minimum'][t_idx]) #(24)
m.pw[w,t].setub(gen['power_output_maximum'][t_idx]) #(24)
m.pw[w, t].setlb(gen["power_output_minimum"][t_idx]) # (24)
m.pw[w, t].setub(gen["power_output_maximum"][t_idx]) # (24)

print("model setup complete")

from pyomo.opt import SolverFactory
cbc = SolverFactory('cbc')

solver = SolverFactory(solver_name)

print("solving")
cbc.solve(m, options={'ratioGap':0.01}, tee=True)
options = {
"gurobi": {"mipgap": 0.01},
"glpk": {"mipgap": 0.01},
"cbc": {"ratioGap": 0.01},
"scip": {"mipgap": 0.01},
}
solver.solve(m, options=options[solver_name], tee=True)