Add reserve shortfall penalty

pull/19/head
Aleksandr Kazachkov 4 years ago committed by Alinson S. Xavier
parent 7a1b6f0f55
commit 000215e991
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@ -28,13 +28,14 @@ Each section is described in detail below. For a complete example, see [case14](
### Parameters
This section describes system-wide parameters, such as power balance penalties, optimization parameters, such as the length of the planning horizon and the time.
This section describes system-wide parameters, such as power balance and reserve shortfall penalties, and optimization parameters, such as the length of the planning horizon and the time.
| Key | Description | Default | Time series?
| :----------------------------- | :------------------------------------------------ | :------: | :------------:
| `Time horizon (h)` | Length of the planning horizon (in hours). | Required | N
| `Time horizon (h)` | Length of the planning horizon (in hours). | Required | N
| `Time step (min)` | Length of each time step (in minutes). Must be a divisor of 60 (e.g. 60, 30, 20, 15, etc). | `60` | N
| `Power balance penalty ($/MW)` | Penalty for system-wide shortage or surplus in production (in $/MW). This is charged per time step. For example, if there is a shortage of 1 MW for three time steps, three times this amount will be charged. | `1000.0` | Y
| `Reserve shortfall penalty ($/MW)` | Penalty for system-wide shortage in meeting reserve requirements (in $/MW). This is charged per time step. Negative value implies reserve constraints must always be satisfied. | `-1` | Y
#### Example
@ -42,7 +43,8 @@ This section describes system-wide parameters, such as power balance penalties,
{
"Parameters": {
"Time horizon (h)": 4,
"Power balance penalty ($/MW)": 1000.0
"Power balance penalty ($/MW)": 1000.0,
"Reserve shortfall penalty ($/MW)": -1.0
}
}
```

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@ -98,6 +98,10 @@ function _from_json(json; repair = true)
json["Parameters"]["Power balance penalty (\$/MW)"],
default = [1000.0 for t in 1:T],
)
shortfall_penalty = timeseries(
json["Parameters"]["Reserve shortfall penalty (\$/MW)"],
default = [-1.0 for t in 1:T],
)
# Read buses
for (bus_name, dict) in json["Buses"]
@ -264,6 +268,7 @@ function _from_json(json; repair = true)
instance = UnitCommitmentInstance(
T,
power_balance_penalty,
shortfall_penalty,
units,
buses,
lines,

@ -72,6 +72,8 @@ end
mutable struct UnitCommitmentInstance
time::Int
power_balance_penalty::Vector{Float64}
"Penalty for failing to meet reserve requirement."
shortfall_penalty::Vector{Float64}
units::Vector{Unit}
buses::Vector{Bus}
lines::Vector{TransmissionLine}

@ -4,15 +4,11 @@
function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
net_injection = _init(model, :expr_net_injection)
reserve = _init(model, :expr_reserve)
curtail = _init(model, :curtail)
for t in 1:model[:instance].time
# Fixed load
net_injection[b.name, t] = AffExpr(-b.load[t])
# Reserves
reserve[b.name, t] = AffExpr()
# Load curtailment
curtail[b.name, t] =
@variable(model, lower_bound = 0, upper_bound = b.load[t])

@ -29,13 +29,28 @@ end
function _add_reserve_eqs!(model::JuMP.Model)::Nothing
eq_min_reserve = _init(model, :eq_min_reserve)
for t in 1:model[:instance].time
instance = model[:instance]
for t in 1:instance.time
# Equation (68) in Kneuven et al. (2020)
# As in Morales-España et al. (2013a)
# Akin to the alternative formulation with max_power_avail
# from Carrión and Arroyo (2006) and Ostrowski et al. (2012)
shortfall_penalty = instance.shortfall_penalty[t]
eq_min_reserve[t] = @constraint(
model,
sum(
model[:expr_reserve][b.name, t] for b in model[:instance].buses
) >= model[:instance].reserves.spinning[t]
sum(model[:reserve][g.name, t] for g in instance.units) +
(shortfall_penalty >= 0 ? model[:reserve_shortfall][t] : 0.0) >=
instance.reserves.spinning[t]
)
# Account for shortfall contribution to objective
if shortfall_penalty >= 0
add_to_expression!(
model[:obj],
shortfall_penalty,
model[:reserve_shortfall][t],
)
end
end
return
end

@ -44,12 +44,16 @@ _is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
reserve = _init(model, :reserve)
reserve_shortfall = _init(model, :reserve_shortfall)
for t in 1:model[:instance].time
if g.provides_spinning_reserves[t]
reserve[g.name, t] = @variable(model, lower_bound = 0)
else
reserve[g.name, t] = 0.0
end
reserve_shortfall[t] =
(model[:instance].shortfall_penalty[t] >= 0) ?
@variable(model, lower_bound = 0) : 0.0
end
return
end
@ -210,11 +214,5 @@ function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
model[:is_on][g.name, t],
g.min_power[t],
)
# Add to reserves expression
add_to_expression!(
model[:expr_reserve][g.bus.name, t],
model[:reserve][g.name, t],
1.0,
)
end
end

@ -51,6 +51,12 @@ function solution(model::JuMP.Model)::OrderedDict
sol["Switch on"] = timeseries(model[:switch_on], instance.units)
sol["Switch off"] = timeseries(model[:switch_off], instance.units)
sol["Reserve (MW)"] = timeseries(model[:reserve], instance.units)
sol["Reserve shortfall (MW)"] = OrderedDict(
t =>
(instance.shortfall_penalty[t] >= 0) ?
round(value(model[:reserve_shortfall][t]), digits = 5) : 0.0 for
t in 1:instance.time
)
sol["Net injection (MW)"] =
timeseries(model[:net_injection], instance.buses)
sol["Load curtail (MW)"] = timeseries(model[:curtail], instance.buses)

@ -324,11 +324,16 @@ function _validate_reserve_and_demand(instance, solution, tol = 0.01)
# Verify spinning reserves
reserve =
sum(solution["Reserve (MW)"][g.name][t] for g in instance.units)
if reserve < instance.reserves.spinning[t] - tol
reserve_shortfall =
(instance.shortfall_penalty[t] >= 0) ?
solution["Reserve shortfall (MW)"][t] : 0
if reserve + reserve_shortfall < instance.reserves.spinning[t] - tol
@error @sprintf(
"Insufficient spinning reserves at time %d (%.2f should be %.2f)",
"Insufficient spinning reserves at time %d (%.2f + %.2f should be %.2f)",
t,
reserve,
reserve_shortfall,
instance.reserves.spinning[t],
)
err_count += 1

@ -20,8 +20,14 @@ if ENABLE_LARGE_TESTS
end
function _small_test(formulation::Formulation)::Nothing
instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
UnitCommitment.build_model(instance = instance, formulation = formulation) # should not crash
instances = ["matpower/case118/2017-02-01", "test/case14"]
for instance in instances
# Should not crash
UnitCommitment.build_model(
instance = UnitCommitment.read_benchmark(instance),
formulation = formulation,
)
end
return
end

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