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Settings#

One of the base fragments of Calliope in fragments. The weightings every topic reads, and the objective. The objective is the system cost plus a penalty, and both are sums other files add to, so this file names no technology.

dimensions:
  timesteps:
    description: Calliope's `timesteps` — time steps, in order
    dtype: datetime
  costs:
    description: Calliope's `costs` — cost classes, such as monetary and CO2

parameters:
  timestep_resolution:
    description: >-
      `timestep_resolution` — hours a time step lasts. Calliope's default is
      1, and data prep fills it
    dims: [timesteps]
  timestep_weights:
    description: >-
      `timestep_weights` — how many times a time step counts, as after
      clustering. Calliope's default is 1, and data prep fills it
    dims: [timesteps]
  objective_cost_weights:
    description: >-
      `objective_cost_weights` — what one unit of a cost class weighs in the
      objective. Calliope's default is 1, and data prep fills it
    dims: [costs]
  bigM:
    description: >-
      `bigM` — a number larger than any decision can take. Calliope's
      default is 1e6, and data prep fills it
    dims: []

expressions:
  system_cost:
    description: >-
      the weighted cost of the system, over every cost class — Calliope's
      `min_cost_optimisation` less its unmet-demand penalty. The cost file and
      every file that prices something outside a technology add to it
    dims: []
    empty: true
  penalty:
    description: >-
      what the objective adds to the system cost to keep a model feasible —
      Calliope's `$unmet_demand` sub-expression. It is zero, and a file that
      keeps a model feasible adds to it
    dims: []
    expression: "0"

objective:
  description: >-
    `min_cost_optimisation` — the weighted cost of installing and operating
    every technology, plus the penalty on unmet demand
  sense: minimize
  expression: system_cost + penalty

Sets#

Symbol Meaning
\(\mathcal{T}\) index \(t\) — timesteps — Calliope's timesteps — time steps, in order
\(\mathcal{K}\) index \(k\) — costs — Calliope's costs — cost classes, such as monetary and CO2

Parameters#

Symbol Meaning
\(\mathrm{timestep\_resolution}\) timestep_resolution over \(\mathcal{T}\) — timestep_resolution — hours a time step lasts. Calliope's default is 1, and data prep fills it
\(\mathrm{timestep\_weights}\) timestep_weights over \(\mathcal{T}\) — timestep_weights — how many times a time step counts, as after clustering. Calliope's default is 1, and data prep fills it
\(\mathrm{objective\_cost\_weights}\) objective_cost_weights over \(\mathcal{K}\) — objective_cost_weights — what one unit of a cost class weighs in the objective. Calliope's default is 1, and data prep fills it
\(\mathrm{bigM}\) bigM (scalar) — bigM — a number larger than any decision can take. Calliope's default is 1e6, and data prep fills it

Definitions#

Symbol Meaning
\(\mathrm{penalty}\) penalty (scalar) — what the objective adds to the system cost to keep a model feasible — Calliope's $unmet_demand sub-expression. It is zero, and a file that keeps a model feasible adds to it
\(\mathit{system\_cost}\) system_cost (scalar) — the weighted cost of the system, over every cost class — Calliope's min_cost_optimisation less its unmet-demand penalty. The cost file and every file that prices something outside a technology add to it

Objective#

\[ \min \mathit{system\_cost} + \mathrm{penalty} \]

Definitions#

penalty

\[ \mathrm{penalty} = 0 \]

system_cost

\[ \mathit{system\_cost} = \cdots \]