AC ‘dc linear’ Optimal Power Flow Module¶

This module provides functions for AC ‘dc linear’ optimal power flow analysis [1].

functions are found in pyflow_acdc.AC_OPF_L_model

AC ‘dc linear’ Optimal Power Flow¶

Running the OPF¶

This flow sets up and solves the AC ‘dc linear’ OPF. It creates the model, optionally adds TEP/REC/CT investment variables, and solves with a Pyomo solver. Results are then exported back to the grid.

import pyflow_acdc as pyf

pyf.Optimal_L_PF(grid,ObjRule=None,PV_set=False,OnlyGen=True,Price_Zones=False,solver='glpk',tee=False)

Creating the Linear OPF model¶

OPF_create_LModel_AC(model, grid, TEP=False)¶

Creates the AC ‘dc linear’ OPF model.

Parameter	Type	Description
`model`	Model	Pyomo model to populate
`grid`	Grid	Grid to optimize
`Price_Zones`	bool	Enable price zone constraints (if applicable)
`TEP`	bool	Enable TEP investment variables (lines/generators)

Variables

The linear OPF includes variables for:

AC node angles
Generator active power
Renewable generation via availability and curtailment factors
AC line active power flows

Constraints

The model enforces constraints for:

AC nodal active power balance (linearized)
Generator aggregation at nodes
Renewable injection aggregation at nodes
AC branch linearized power flow equations
Thermal limits (including linear big-M formulations for REC/CT states)
Slack angle constraints
Optional array network-flow conservation and investment-linking
Optional investment bounds for generators and lines (if TEP)

Example

from pyflow_acdc.AC_OPF_L_model import OPF_create_LModel_AC
model = OPF_create_LModel_AC(model, grid, TEP=False)

TEP/REC/CT Parameters and Variables¶

TEP_parameters(model, grid, AC_info, DC_info, Conv_info)¶: Sets parameters for TEP/REC/CT decisions (e.g., base multiplicities, initial configs, limits).

TEP_variables(model, grid)¶: Adds investment variables: - Generator multiplicities (optional integer bounded by capability) - AC expansion line multiplicities (integer) - Reconfiguration branch selection (binary) - Cable-type selection (binary per type and line) - Optional type-usage flags and array flow variables

Exporting Results¶

ExportACDC_Lmodel_toPyflowACDC(model, grid, Price_Zones, TEP=False, solver_results=None, tee=False)¶

Exports Pyomo solution back to the grid: - Generator dispatch and renewable gamma - AC node angles and injections - AC line flows and losses (linearized, zero reactive) - TEP/REC/CT selections and flows (including optional array network-flow) - Optional post-processing for time-limit cases (oversizing analysis and fixes)

Example

pyf.ExportACDC_Lmodel_toPyflowACDC(model, grid, Price_Zones=False, TEP=False, solver_results=results, tee=True)

Solvers¶

The linear OPF can be solved by LP/MIP solvers in Pyomo.

Tested with:

GLPK
Gurobi

Notes

If REC/CT/TEP or array flow variables are enabled, the problem becomes MIP. Prefer a MIP-capable solver (e.g., gurobi).