Solvers

monee solves energy-flow problems by translating the network model and its formulation into a mathematical programme and delegating to a numerical solver back-end. Two solver interfaces are provided.

The GekkoSolver (monee.solver.gekko) is the default back-end. It wraps the GEKKO optimisation suite, which ships its own solver binaries (APOPT, IPOPT, BPOPT) and requires no extra installation beyond pip install monee.

Suitable for:

  • Nonlinear energy-flow simulation — AC power flow, Weymouth gas flow, Darcy–Weisbach water/heat flow.

  • General NLP and MINLP optimisation problems.

Limitations:

  • MILP / MIQCP problems are handled by APOPT’s built-in MINLP solver, which can be slow for large mixed-integer models. For those cases use the Pyomo back-end with a dedicated MILP solver.

Usage

monee.run_energy_flow() uses GekkoSolver by default:

import monee.express as mx
from monee import run_energy_flow

net = mx.create_multi_energy_network()
bus_0 = mx.create_bus(net)
bus_1 = mx.create_bus(net)
mx.create_line(net, bus_0, bus_1, 100, r_ohm_per_m=7e-5, x_ohm_per_m=7e-5)
mx.create_ext_power_grid(net, bus_0)
mx.create_power_load(net, bus_1, p_mw=0.1, q_mvar=0.0)

result = run_energy_flow(net)

You can also instantiate the solver directly to pass solver options:

from monee.solver.gekko import GekkoSolver

result = GekkoSolver().solve(net, solver=3)  # solver=3 → IPOPT

The PyomoSolver (monee.solver.pyo) translates the monee model into a Pyomo ConcreteModel and delegates to any solver supported by Pyomo — including Gurobi, GLPK, HiGHS, CBC, and CPLEX.

Suitable for:

  • MILP and MIQCP problems, e.g. optimal power flow with binary switching decisions using MISOCP_NETWORK_FORMULATION.

  • Situations where a specific commercial or open-source solver is required.

Limitations:

  • GEKKO-specific mathematical operators (if2, max2, sign2) are not available in the Pyomo back-end. Formulations that rely on these operators will raise NotImplementedError. Use Pyomo-compatible formulations or write your own using standard Pyomo expressions.

  • Requires Pyomo and a compatible solver installed separately.

Usage

from monee.solver.pyo import PyomoSolver

result = PyomoSolver().solve(
    net,
    solver_name="highs",   # or "gurobi", "glpk", "cbc", ...
)

See Use the Pyomo solver for a complete worked example including MISOCP optimal power flow.

Choosing a solver

Scenario

Recommended solver

Formulation

AC power flow (simulation)

GEKKO

AC_NETWORK_FORMULATION

Gas flow (simulation)

GEKKO

NL_WEYMOUTH_NETWORK_FORMULATION

Water / heat flow (simulation)

GEKKO

NL_DARCY_WEISBACH_NETWORK_FORMULATION

AC optimal power flow (convex relaxation)

Pyomo + Gurobi / HiGHS

MISOCP_NETWORK_FORMULATION

Custom MILP problem

Pyomo + MILP solver

custom formulation

Tip

When in doubt, start with GEKKO — it works out of the box and handles all nonlinear problems. Switch to Pyomo only when you need a MILP / MIQCP solver or a specific commercial solver back-end.