Profiled

nimopt.models.profiled is a dispatch whose capacity varies by hour. dispatch bounds a generator by a single number. Here p_max is a parameter over generators and snapshots. A solar unit is bounded by its hourly availability, and a thermal unit by its rating.

minimize    Σ_{t,g} cost[g] · gen[t,g]
subject to  Σ_g gen[t,g] == load[t]          for each snapshot t
            0 ≤ gen[t,g] ≤ profile[g,t]

The profile is indexed (G, T) and the variable (T, G). A bound is read in the dimension order of the variable it bounds, and both orderings select the same columns.

from nimopt.models import profiled

print(profiled.definition().explain())

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Output

profiled  min  not built
  sets        T · G
  parameters  profile (G,T) · cost (G) · load (T)
  variables   gen (T×G) [0.0, profile]
  constraint  balance (T)  Sum(G, gen[T, G]) == load[T]
  objective   min  Sum(T, G, cost[G] * gen[T, G])

Each snapshot is independent. The optimum is the merit order against the capacities of that hour.

from nimopt.models import profiled

inputs = profiled.data()
solution = profiled.definition().build(inputs).solve()
print(solution.objective, profiled.reference(inputs))

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Output

28119.536003699297 28119.536003699293

Every hour has a balance row. A generator whose profile is zero is a column bounded to zero, not a dropped row.

from nimopt.models import profiled

model = profiled.definition().build(profiled.data())
print(model.absent("balance"))

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Output

balance  8 of 8 rows  stated by terms