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77 lines
2.0 KiB
77 lines
2.0 KiB
# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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using JuMP
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"""
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generate_initial_conditions!(instance, optimizer)
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Generates feasible initial conditions for the given instance, by constructing
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and solving a single-period mixed-integer optimization problem, using the given
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optimizer. The instance is modified in-place.
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"""
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function generate_initial_conditions!(instance::UnitCommitmentInstance,
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optimizer)
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G = instance.units
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B = instance.buses
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t = 1
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mip = JuMP.Model(optimizer)
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# Decision variables
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@variable(mip, x[G], Bin)
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@variable(mip, p[G] >= 0)
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# Constraint: Minimum power
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@constraint(mip,
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min_power[g in G],
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p[g] >= g.min_power[t] * x[g])
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# Constraint: Maximum power
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@constraint(mip,
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max_power[g in G],
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p[g] <= g.max_power[t] * x[g])
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# Constraint: Production equals demand
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@constraint(mip,
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power_balance,
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sum(b.load[t] for b in B) == sum(p[g] for g in G))
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# Constraint: Must run
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for g in G
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if g.must_run[t]
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@constraint(mip, x[g] == 1)
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end
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end
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# Objective function
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function cost_slope(g)
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mw = g.min_power[t]
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c = g.min_power_cost[t]
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for k in g.cost_segments
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mw += k.mw[t]
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c += k.mw[t] * k.cost[t]
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end
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if mw < 1e-3
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return 0.0
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else
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return c / mw
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end
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end
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@objective(mip,
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Min,
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sum(p[g] * cost_slope(g) for g in G))
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JuMP.optimize!(mip)
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for g in G
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if JuMP.value(x[g]) > 0
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g.initial_power = JuMP.value(p[g])
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g.initial_status = 24
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else
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g.initial_power = 0
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g.initial_status = -24
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end
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end
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end
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