AC optimal power flow (discopt.opf)

Contents

AC optimal power flow (discopt.opf)#

The optimal power flow (OPF) problem chooses generator setpoints and bus voltages to meet electrical demand at minimum generation cost, subject to the full nonlinear AC power-flow (Kirchhoff) equations. Because the power injections are quadratic in the bus voltages, AC-OPF is a nonconvex quadratically-constrained quadratic program (QCQP) — the canonical benchmark for relaxation and global optimization research in power systems.

The rectangular-coordinate AC-OPF builder now lives in the standalone discopt-apps plugin (#431), mirroring the course extraction (#430). It is no longer bundled with the core discopt package. The builder is pure modeling code over discopt.modeling.core, so the spatial branch-and-bound solver in core handles the resulting Model as an ordinary QCQP — no core changes are required.

Installation#

pip install discopt-apps

Usage#

from discopt.opf import (
    ACOPF,
    Bus,
    Line,
    admittance_matrix,
    build_ac_opf_rectangular,
    two_bus_example,
)

acopf = two_bus_example()
model = build_ac_opf_rectangular(acopf)
result = model.solve()

See the discopt-apps documentation for the full AC-OPF formulation and examples.

Contents