Reformat source code

This commit is contained in:
2022-03-01 16:26:51 -06:00
parent 03268dd3df
commit 360308ef4a
7 changed files with 198 additions and 138 deletions

View File

@@ -5,12 +5,12 @@
function _add_flexiramp_vars!(model::JuMP.Model, g::Unit)::Nothing
upflexiramp = _init(model, :upflexiramp)
upflexiramp_shortfall = _init(model, :upflexiramp_shortfall)
mfg=_init(model,:mfg)
mfg = _init(model, :mfg)
dwflexiramp = _init(model, :dwflexiramp)
dwflexiramp_shortfall = _init(model, :dwflexiramp_shortfall)
for t in 1:model[:instance].time
# maximum feasible generation, \bar{g_{its}} in Wang & Hobbs (2016)
mfg[g.name,t]=@variable(model, lower_bound = 0)
mfg[g.name, t] = @variable(model, lower_bound = 0)
if g.provides_flexiramp_reserves[t]
upflexiramp[g.name, t] = @variable(model) # up-flexiramp, ur_{it} in Wang & Hobbs (2016)
dwflexiramp[g.name, t] = @variable(model) # down-flexiramp, dr_{it} in Wang & Hobbs (2016)
@@ -28,8 +28,6 @@ function _add_flexiramp_vars!(model::JuMP.Model, g::Unit)::Nothing
return
end
function _add_ramp_eqs!(
model::JuMP.Model,
g::Unit,
@@ -43,110 +41,145 @@ function _add_ramp_eqs!(
RU = g.ramp_up_limit
RD = g.ramp_down_limit
gn = g.name
minp=g.min_power
maxp=g.max_power
initial_power=g.initial_power
minp = g.min_power
maxp = g.max_power
initial_power = g.initial_power
is_on = model[:is_on]
prod_above = model[:prod_above]
upflexiramp=model[:upflexiramp]
dwflexiramp=model[:dwflexiramp]
mfg=model[:mfg]
upflexiramp = model[:upflexiramp]
dwflexiramp = model[:dwflexiramp]
mfg = model[:mfg]
for t in 1:model[:instance].time
@constraint(model, prod_above[gn, t] + (is_on[gn,t]*minp[t])
<=mfg[gn,t]) # Eq. (19) in Wang & Hobbs (2016)
@constraint(model, mfg[gn,t]<= is_on[gn,t]* maxp[t]) # Eq. (22) in Wang & Hobbs (2016)
if t!=model[:instance].time
@constraint(model, minp[t] * (is_on[gn,t+1]+is_on[gn,t]-1) <=
prod_above[gn, t] - dwflexiramp[gn,t] +(is_on[gn,t]*minp[t])
) # first inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(model, prod_above[gn, t] - dwflexiramp[gn,t] + (is_on[gn,t]*minp[t]) <=
mfg[gn,t+1]
+ (maxp[t] * (1-is_on[gn,t+1]))
) # second inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(model, minp[t] * (is_on[gn,t+1]+is_on[gn,t]-1) <=
prod_above[gn, t] + upflexiramp[gn,t] + (is_on[gn,t]*minp[t])
) # first inequality of Eq. (21) in Wang & Hobbs (2016)
@constraint(model, prod_above[gn, t] + upflexiramp[gn,t] +(is_on[gn,t]*minp[t]) <=
mfg[gn,t+1] + (maxp[t] * (1-is_on[gn,t+1]))
) # second inequality of Eq. (21) in Wang & Hobbs (2016)
if t!=1
@constraint(model, mfg[gn,t]<=prod_above[gn,t-1] + (is_on[gn,t-1]*minp[t])
+ (RU * is_on[gn,t-1])
+ (SU*(is_on[gn,t] - is_on[gn,t-1]))
+ maxp[t] * (1-is_on[gn,t])
) # Eq. (23) in Wang & Hobbs (2016)
@constraint(model, (prod_above[gn,t-1] + (is_on[gn,t-1]*minp[t]))
- (prod_above[gn,t] + (is_on[gn,t]*minp[t]))
<= RD * is_on[gn,t]
+ SD * (is_on[gn,t-1] - is_on[gn,t])
+ maxp[t] * (1-is_on[gn,t-1])
) # Eq. (25) in Wang & Hobbs (2016)
@constraint(
model,
prod_above[gn, t] + (is_on[gn, t] * minp[t]) <= mfg[gn, t]
) # Eq. (19) in Wang & Hobbs (2016)
@constraint(model, mfg[gn, t] <= is_on[gn, t] * maxp[t]) # Eq. (22) in Wang & Hobbs (2016)
if t != model[:instance].time
@constraint(
model,
minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
prod_above[gn, t] - dwflexiramp[gn, t] +
(is_on[gn, t] * minp[t])
) # first inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(
model,
prod_above[gn, t] - dwflexiramp[gn, t] +
(is_on[gn, t] * minp[t]) <=
mfg[gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
) # second inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(
model,
minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
prod_above[gn, t] +
upflexiramp[gn, t] +
(is_on[gn, t] * minp[t])
) # first inequality of Eq. (21) in Wang & Hobbs (2016)
@constraint(
model,
prod_above[gn, t] +
upflexiramp[gn, t] +
(is_on[gn, t] * minp[t]) <=
mfg[gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
) # second inequality of Eq. (21) in Wang & Hobbs (2016)
if t != 1
@constraint(
model,
mfg[gn, t] <=
prod_above[gn, t-1] +
(is_on[gn, t-1] * minp[t]) +
(RU * is_on[gn, t-1]) +
(SU * (is_on[gn, t] - is_on[gn, t-1])) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016)
@constraint(
model,
(prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_on[gn, t-1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t-1])
) # Eq. (25) in Wang & Hobbs (2016)
else
@constraint(model, mfg[gn,t]<=initial_power
+ (RU * is_initially_on)
+ (SU*(is_on[gn,t] - is_initially_on))
+ maxp[t] * (1-is_on[gn,t])
) # Eq. (23) in Wang & Hobbs (2016) for the first time period
@constraint(model, initial_power
- (prod_above[gn,t] + (is_on[gn,t]*minp[t]))
<= RD * is_on[gn,t]
+ SD * (is_initially_on - is_on[gn,t])
+ maxp[t] * (1-is_initially_on)
) # Eq. (25) in Wang & Hobbs (2016) for the first time period
@constraint(
model,
mfg[gn, t] <=
initial_power +
(RU * is_initially_on) +
(SU * (is_on[gn, t] - is_initially_on)) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016) for the first time period
@constraint(
model,
initial_power -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_initially_on - is_on[gn, t]) +
maxp[t] * (1 - is_initially_on)
) # Eq. (25) in Wang & Hobbs (2016) for the first time period
end
@constraint(model, mfg[gn,t]<=
(SD*(is_on[gn,t] - is_on[gn,t+1]))
+ (maxp[t] * is_on[gn,t+1])
) # Eq. (24) in Wang & Hobbs (2016)
@constraint(model, -RD * is_on[gn,t+1]
-SD * (is_on[gn,t]-is_on[gn,t+1])
-maxp[t] * (1-is_on[gn,t])
<= upflexiramp[gn,t]
) # first inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(model, upflexiramp[gn,t] <=
RU * is_on[gn,t]
+ SU * (is_on[gn,t+1]-is_on[gn,t])
+ maxp[t] * (1-is_on[gn,t+1])
) # second inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(model, -RU * is_on[gn,t]
-SU * (is_on[gn,t+1]-is_on[gn,t])
-maxp[t] * (1-is_on[gn,t+1])
<= dwflexiramp[gn,t]
) # first inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(model, dwflexiramp[gn,t] <=
RD * is_on[gn,t+1]
+ SD * (is_on[gn,t]-is_on[gn,t+1])
+ maxp[t] * (1-is_on[gn,t])
) # second inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(model, -maxp[t] * is_on[gn,t]
+minp[t] * is_on[gn,t+1]
<= upflexiramp[gn,t]
) # first inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, upflexiramp[gn,t] <=
maxp[t] * is_on[gn,t+1]
) # second inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, -maxp[t] * is_on[gn,t+1]
<= dwflexiramp[gn,t]
) # first inequality of Eq. (29) in Wang & Hobbs (2016)
@constraint(model, dwflexiramp[gn,t] <=
(maxp[t] * is_on[gn,t])
-(minp[t] * is_on[gn,t+1])
) # second inequality of Eq. (29) in Wang & Hobbs (2016)
@constraint(
model,
mfg[gn, t] <=
(SD * (is_on[gn, t] - is_on[gn, t+1])) +
(maxp[t] * is_on[gn, t+1])
) # Eq. (24) in Wang & Hobbs (2016)
@constraint(
model,
-RD * is_on[gn, t+1] - SD * (is_on[gn, t] - is_on[gn, t+1]) -
maxp[t] * (1 - is_on[gn, t]) <= upflexiramp[gn, t]
) # first inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(
model,
upflexiramp[gn, t] <=
RU * is_on[gn, t] +
SU * (is_on[gn, t+1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t+1])
) # second inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(
model,
-RU * is_on[gn, t] - SU * (is_on[gn, t+1] - is_on[gn, t]) -
maxp[t] * (1 - is_on[gn, t+1]) <= dwflexiramp[gn, t]
) # first inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(
model,
dwflexiramp[gn, t] <=
RD * is_on[gn, t+1] +
SD * (is_on[gn, t] - is_on[gn, t+1]) +
maxp[t] * (1 - is_on[gn, t])
) # second inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(
model,
-maxp[t] * is_on[gn, t] + minp[t] * is_on[gn, t+1] <=
upflexiramp[gn, t]
) # first inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, upflexiramp[gn, t] <= maxp[t] * is_on[gn, t+1]) # second inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, -maxp[t] * is_on[gn, t+1] <= dwflexiramp[gn, t]) # first inequality of Eq. (29) in Wang & Hobbs (2016)
@constraint(
model,
dwflexiramp[gn, t] <=
(maxp[t] * is_on[gn, t]) - (minp[t] * is_on[gn, t+1])
) # second inequality of Eq. (29) in Wang & Hobbs (2016)
else
@constraint(model, mfg[gn,t]<=prod_above[gn,t-1] + (is_on[gn,t-1]*minp[t])
+ (RU * is_on[gn,t-1])
+ (SU*(is_on[gn,t] - is_on[gn,t-1]))
+ maxp[t] * (1-is_on[gn,t])
) # Eq. (23) in Wang & Hobbs (2016) for the last time period
@constraint(model, (prod_above[gn,t-1] + (is_on[gn,t-1]*minp[t]))
- (prod_above[gn,t] + (is_on[gn,t]*minp[t]))
<= RD * is_on[gn,t]
+ SD * (is_on[gn,t-1] - is_on[gn,t])
+ maxp[t] * (1-is_on[gn,t-1])
) # Eq. (25) in Wang & Hobbs (2016) for the last time period
@constraint(
model,
mfg[gn, t] <=
prod_above[gn, t-1] +
(is_on[gn, t-1] * minp[t]) +
(RU * is_on[gn, t-1]) +
(SU * (is_on[gn, t] - is_on[gn, t-1])) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016) for the last time period
@constraint(
model,
(prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_on[gn, t-1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t-1])
) # Eq. (25) in Wang & Hobbs (2016) for the last time period
end
end
end
end