Progress Matrices Module

class progress.mod_matrices.RAMatrices(nb)

Bases: object

Creates generation, incidence, and curtailment matrices for the RA model.

Parameters:

nb (int) – Number of buses in the system.

Ainc(nl, fb, tb)

Creates an incidence matrix for modeling flow constraints.

Parameters:

  • nl (int) – Number of lines.

  • fb (list[int]) – List of “from bus” indices for each line.

  • tb (list[int]) – List of “to bus” indices for each line.

Returns:

A 2D NumPy array with shape (nl, nb) where each row represents one line. Entries of +1 and -1 indicate the sending and receiving buses, respectively.

Return type:

numpy.ndarray

chmat(ness, essbus, nb)

Creates a matrix for ESS charging variables.

Parameters:

  • ness (int) – Number of energy storage systems (ESS).

  • essbus (list[int]) – List of ESS bus indices.

  • nb (int) – Number of buses.

Returns:

A 2D NumPy array with shape (nb, ness) where each column corresponds to an ESS unit and the row index indicates the bus at which that ESS is located.

Return type:

numpy.ndarray

curtmat(nb)

Creates a curtailment matrix for load curtailment variables.

Parameters:

nb (int) – Number of buses.

Returns:

A 2D identity matrix of shape (nb, nb). This matrix is often used to represent a direct mapping of curtailment variables to each bus.

Return type:

numpy.ndarray

genmat(ng, genbus, ness, essbus)

Creates a generation matrix for the optimization problem.

Parameters:

  • ng (int) – Number of generators.

  • genbus (list[int]) – List of generator bus indices.

  • ness (int) – Number of energy storage systems (ESS).

  • essbus (list[int]) – List of ESS bus indices.

Returns:

A 2D NumPy array with shape (nb, ng + ness) where each column corresponds to one generator (or ESS) and the row index indicates the bus to which that generator/ESS is connected.

Return type:

numpy.ndarray