casadi-ipopt-nlp

name	casadi-ipopt-nlp
description	Nonlinear optimization with CasADi and IPOPT solver. Use when building and solving NLP problems: defining symbolic variables, adding nonlinear constraints, setting solver options, handling multiple initializations, and extracting solutions. Covers power systems optimization patterns including per-unit scaling and complex number formulations.

CasADi + IPOPT for Nonlinear Programming

CasADi is a symbolic framework for nonlinear optimization. IPOPT is an interior-point solver for large-scale NLP.

Quick start (Linux)

apt-get update -qq && apt-get install -y -qq libgfortran5
pip install numpy==1.26.4 casadi==3.6.7

Building an NLP

1. Decision variables

import casadi as ca

n_bus, n_gen = 100, 20
Vm = ca.MX.sym("Vm", n_bus)   # Voltage magnitudes
Va = ca.MX.sym("Va", n_bus)   # Voltage angles (radians)
Pg = ca.MX.sym("Pg", n_gen)   # Real power
Qg = ca.MX.sym("Qg", n_gen)   # Reactive power

# Stack into single vector for solver
x = ca.vertcat(Vm, Va, Pg, Qg)

2. Objective function

Build symbolic expression:

# Quadratic cost: sum of c2*P^2 + c1*P + c0
obj = ca.MX(0)
for k in range(n_gen):
    obj += c2[k] * Pg[k]** + c1[k] * Pg[k] + c0[k]