Skip to content

A curve by convex combination#

A generator's cost curve, tied to its dispatch through one weight per breakpoint. This is the floor of the piecewise family: the three pages after it are this same model with the weights restricted a different way.

Read the math for what the block expands to. The file declares no weight, and cost_curve_lam appears below because the block emits it. One row makes the weights sum to 1, and one row per link ties that link's expression to the weighted breakpoints. method: convex adds nothing further. A convex curve under a minimised cost settles on one segment without being held there.

description: >-
  Least-cost dispatch where each generator's cost curve is piecewise-linear in
  its output, expanded into a lambda formulation.

dimensions:
  snapshot:
    description: dispatch periods
    dtype: int
  generator:
    description: dispatchable units
    dtype: str
  bp:
    description: breakpoints of the cost curve
    dtype: int

parameters:
  capacity:
    description: maximum dispatch
    dims: [generator]
  load:
    description: demand to be met
    dims: [snapshot]
  bp_x:
    description: breakpoint dispatch levels, one curve per generator
    dims: [generator, bp]
  bp_y:
    description: cost at each breakpoint, one curve per generator
    dims: [generator, bp]

variables:
  dispatch:
    description: dispatched power
    dims: [snapshot, generator]
    bounds:
      lower: 0
      upper: capacity
  op_cost:
    description: operating cost, piecewise-linear in dispatch
    dims: [snapshot, generator]
    bounds:
      lower: 0

piecewise:
  cost_curve:
    description: >-
      cost read off the generator's curve — convex, so the weights need no
      binaries to keep them on one segment
    along: bp
    dims: [snapshot, generator]
    links:
      dispatch: [dispatch, bp_x]
      op_cost: [op_cost, bp_y]
    method: convex

constraints:
  balance:
    dims: [snapshot]
    expression: sum(dispatch, over=generator) == load

objective:
  sense: minimize
  description: total operating cost, taken off the curves rather than from a marginal rate
  expression: sum(op_cost)

Least-cost dispatch where each generator's cost curve is piecewise-linear in its output, expanded into a lambda formulation.

Sets#

Symbol Meaning
\(\mathcal{T}\) index \(t\) — snapshot — dispatch periods
\(\mathcal{G}\) index \(g\) — generator — dispatchable units
\(\mathcal{B}\) index \(b\) — bp — breakpoints of the cost curve

Parameters#

Symbol Meaning
\(\mathrm{capacity}\) capacity over \(\mathcal{G}\) — maximum dispatch
\(\mathrm{load}\) load over \(\mathcal{T}\) — demand to be met
\(\mathrm{x}\) bp_x over \(\mathcal{G} \times \mathcal{B}\) — breakpoint dispatch levels, one curve per generator
\(\mathrm{y}\) bp_y over \(\mathcal{G} \times \mathcal{B}\) — cost at each breakpoint, one curve per generator

Variables#

Symbol Meaning
\(\mathit{dispatch}\) dispatch over \(\mathcal{T} \times \mathcal{G}\) — dispatched power
\(\mathit{op\_cost}\) op_cost over \(\mathcal{T} \times \mathcal{G}\) — operating cost, piecewise-linear in dispatch

Upright is what the data supplies — a parameter such as \(\mathrm{capacity}\), a coordinate map, a label — and italic is what the solver chooses, such as \(\mathit{dispatch}\). An index is italic too, being what a quantifier chooses, and a set is script.

\(t \boxminus_{v} k\) denotes translation with \(v\) standing where index \(t-k\) leaves the dimension (shift(edge=v)), so the row at that boundary is built and carries \(v\) rather than being dropped.

\(\mathrm{pos}(t)\) denotes where index \(t\) sits along its dimension's own order — the order shift steps along, not the order labels sort in — counted from \(0\). The index itself stays the coordinate, so \(t\) compares against labels and \(\mathrm{pos}(t)\) against positions.

\(\lvert \mathcal{T} \rvert\) denotes the size of the set being counted along, and a position counted from the end prints against it — \(\lvert \mathcal{T} \rvert - 1\) is the last position, one less than the size because the first is \(0\).

Objective#

\[ \min \sum_{t \in \mathcal{T},\ g \in \mathcal{G}} \mathit{op\_cost}_{t,g} \]

Subject to#

balance

\[ \sum_{g \in \mathcal{G}} \mathit{dispatch}_{t,g} = \mathrm{load}_{t} \qquad \forall\, t \in \mathcal{T} \]

cost_curve

\[ \left( \mathit{dispatch}_{t,g},\ \mathit{op\_cost}_{t,g} \right) \in \mathrm{conv}_{b \in \mathcal{B}}(\mathrm{x}_{g,b},\ \mathrm{y}_{g,b}) \qquad \forall\, t \in \mathcal{T},\ g \in \mathcal{G} \]

Variable domains#

dispatch

\[ 0 \le \mathit{dispatch}_{t,g} \le \mathrm{capacity}_{g} \qquad \forall\, t \in \mathcal{T},\ g \in \mathcal{G} \]

op_cost

\[ \mathit{op\_cost}_{t,g} \ge 0 \qquad \forall\, t \in \mathcal{T},\ g \in \mathcal{G} \]

Assumptions#

cost_curve_complete

\[ \mathrm{x}_{g,b} \text{ is defined} \wedge \mathrm{y}_{g,b} \text{ is defined} \qquad \forall\, g \in \mathcal{G},\ b \in \mathcal{B} \]

cost_curve_increasing

\[ \mathrm{x}_{g,b \boxminus_{0} 1} < \mathrm{x}_{g,b} \qquad \forall\, g \in \mathcal{G},\ b \in \mathcal{B} \,:\, \mathrm{pos}(b) > 0 \]

cost_curve_curvature

\[ \lvert \{ b \in \mathcal{B} \,:\, \left( \mathrm{y}_{g,b} - \mathrm{y}_{g,b \boxminus_{0} 1} \right) \cdot \left( \mathrm{x}_{g,b \boxplus_{0} 1} - \mathrm{x}_{g,b} \right) > \left( \mathrm{y}_{g,b \boxplus_{0} 1} - \mathrm{y}_{g,b} \right) \cdot \left( \mathrm{x}_{g,b} - \mathrm{x}_{g,b \boxminus_{0} 1} \right) \wedge \mathrm{pos}(b) > 0 \wedge \mathrm{pos}(b) \neq \lvert \mathcal{B} \rvert - 1 \} \rvert = 0 \vee \lvert \{ b \in \mathcal{B} \,:\, \left( \mathrm{y}_{g,b} - \mathrm{y}_{g,b \boxminus_{0} 1} \right) \cdot \left( \mathrm{x}_{g,b \boxplus_{0} 1} - \mathrm{x}_{g,b} \right) < \left( \mathrm{y}_{g,b \boxplus_{0} 1} - \mathrm{y}_{g,b} \right) \cdot \left( \mathrm{x}_{g,b} - \mathrm{x}_{g,b \boxminus_{0} 1} \right) \wedge \mathrm{pos}(b) > 0 \wedge \mathrm{pos}(b) \neq \lvert \mathcal{B} \rvert - 1 \} \rvert = 0 \qquad \forall\, g \in \mathcal{G} \]