lanl-ansi / powermodels.jl

A Julia/JuMP Package for Power Network Optimization

PowerModels.jl

Status:

PowerModels.jl is a Julia/JuMP package for Steady-State Power Network Optimization. It is designed to enable computational evaluation of emerging power network formulations and algorithms in a common platform. The code is engineered to decouple problem specifications (e.g. Power Flow, Optimal Power Flow, ...) from the power network formulations (e.g. AC, DC-approximation, SOC-relaxation, ...). This enables the definition of a wide variety of power network formulations and their comparison on common problem specifications.

Core Problem Specifications

• Power Flow (pf)
• Optimal Power Flow (opf)
• Optimal Transmission Switching (ots)
• Transmission Network Expansion Planning (tnep)

Core Network Formulations

• AC (polar and rectangular coordinates)
• DC Approximation (polar coordinates)
• LPAC Approximation (polar coordinates)
• SDP Relaxation (W-space)
• SOC Relaxation (W-space)
• QC Relaxation (W+L-space)
• IV (rectangular coordinates)

Network Data Formats

• Matpower ".m" files
• PTI ".raw" files (PSS(R)E v33 specification)

Documentation

The package documentation includes a variety of useful information including a quick-start guide, network model specification, and baseline results.

Additionally, these presentations provide a brief introduction to various aspects of PowerModels,

• Network Model Update, v0.6
• PSCC 2018
• JuMP Developers Meetup 2017

Development

Community-driven development and enhancement of PowerModels are welcome and encouraged. Please fork this repository and share your contributions to the master with pull requests. See CONTRIBUTING.md for code contribution guidelines.

Acknowledgments

This code has been developed as part of the Advanced Network Science Initiative at Los Alamos National Laboratory. The primary developer is Carleton Coffrin (@ccoffrin) with support from the following contributors,

• Per Aaslid (@peraaslid) SINTEF ER, Branch flow storage model and linear branch flow formulation
• Juan Luis Barbería (@jbarberia) UTN-BA, PSS(R)E v33 data export, Jacobian support for basic network data
• Russell Bent (@rb004f) LANL, Matpower export, TNEP problem specification
• Jose Daniel Lara (@jd-lara) Berkeley, Julia v1.0 compatibility
• Jay Dave (@jay-dave) KU Leuven, LPAC for TNEP and OTS problems
• Hakan Ergun (@hakanergun) KU Leuven, HVDC lines
• David Fobes (@pseudocubic) LANL, PSS(R)E v33 data support
• Rory Finnegan (@rofinn) Invenia, Memento Logging
• Frederik Geth (@frederikgeth) CSIRO, storage modeling advise, Branch Flow and current-voltage formulation
• Jonas Kersulis (@kersulis) University of Michigan, Sparse SDP formulation
• Miles Lubin (@mlubin) MIT, Julia/JuMP advise
• Yeesian Ng (@yeesian) MIT, Documenter.jl setup
• Kaarthik Sundar (@kaarthiksundar) LANL, OBBT utility
• Mathieu Tanneau (@mtanneau) Georgia Tech, PTDF matrix computation
• Byron Tasseff (@tasseff) LANL, multi-infrastructure updates

Citing PowerModels

If you find PowerModels useful in your work, we kindly request that you cite the following publication:

@inproceedings{8442948,
  author = {Carleton Coffrin and Russell Bent and Kaarthik Sundar and Yeesian Ng and Miles Lubin},
  title = {PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations},
  booktitle = {2018 Power Systems Computation Conference (PSCC)},
  year = {2018},
  month = {June},
  pages = {1-8},
  doi = {10.23919/PSCC.2018.8442948}
}

Citation of the original works for problem definitions (e.g. OPF) and power flow formulations (e.g. SOC) is also encouraged when publishing works that use PowerModels.

License

This code is provided under a BSD license as part of the Multi-Infrastructure Control and Optimization Toolkit (MICOT) project, C15024.

powermodels.jl's Issues

Best Output Behavior of Bus Phase Angles, when the model has no such variable

For example, in the SOC relaxation, should the output Bus Phase Angles absent, NaN, 0?

More Robust String Parsing in Matpower Files

Extend the split_line function in the Matpower parser to support splitting lines with multiple single-quoted string values.

Fixing Bus Types when Parsing Matpower

When parsing .m files, if a generator bus type is incorrect (e.g. type 2 with no generators) fix it.

Key use case, is running an AC-PF solve on a non-NESTA Polish case (e.g. case2737sop.m).

Matpower Bus Names

Add parsing for bus_names in Matpower parser.

Re-work how solutions are reported

See if this can be simplified and if the the generic per-unit / mixed-units functions can be applied.

Use "!" for fcns that modify inputs

Functions that modify their inputs typically have an exclamation point at the end of their names, to help them stand out. I can make a PR if you would like to adopt this convention.

Export all types for forms and abstract forms

DC with Line Losses

Double check that a DC OPF with Line Losses is actually imposing losses.

Add a Relaxation Scheme with SOC Constraint and Lower Bound 4D Cuts

PowerDataSets to Dict{Symbol,Any}

To make GenericPowerModel more extensible.

Possibly remove ext.

Type Parsing in build_sets

The various Int(x) calls may not be necessary.

When parsing .m files these fields are already parsed to Int. When parsing .json these values may come in as Int, Float, or Number. Needs to be investigated.

Cleaning up TNEP line on/off constraints

In light of recent changes can constraint_complex_voltage_ne{T <: AbstractWRForm} be made cleaner? Like constraint_complex_voltage_on_off{T <: AbstractWRForm}?

Documentation - ReadTheDocs

Setup inline code documentation and ReadTheDocs integration.

Test Case with Small Asymmetrical Angle Bounds

Add a test case with small asymmetrical angles, i.e. the outcome of bounds propagation.

Make sure SOC, QC, and SDP models work on this (i.e LNCs are not breaking stuff).

Variable constructor return values

The variable_* functions should return some data structure including all of the variables they have added to the model.

The key challenge here is the type of data structure, as JuMP's @varaible macro can return a single variable, an array of variables, or a dict index-variable mapping.

angle bound limits

Add checks to the appropriate constraints to check angle limits are within +/- pi/2.

Error on Local Edges

Report an error for edges that have the same to and from buses.

JSON Object Types

By default JSON.parse returns Dict{UTF8String, Any} and we typically use Dict{AbstractString, Any}.

1. Figure out why a function of Dict{AbstractString, Any} cannot accpt an argument of Dict{UTF8String, Any}.

2. Migrate code to a robust solution, no types?

3. remove special type cases from JSON.parse() calls

Add data transform flags to internal format

Add flag for per-unit and transformer taps.

When reading in json, apply standardize_cost_order(data), unify_transformer_taps(data) or not, based on these flags.

JuMP 0.15.0 Compatiblity

Fix broken build.

Tests for Variable and Constraint return values

Once #9 is resolved, the number of elements returned from all variable_* calls should be exactly equal to the variables in the JuMP model. And a similar property should be true for the constraint_* calls.

A simple and generic way to test the return value implementation correctness is to test that the total number of returned constraints and variables are consistent with the internal JuMP model.

Constraint Naming Conventions

Add naming conventions to constraints to assist users in understanding the JuMP model.

Variable lookup helper

Consider adding a helper function to do getvariable(pm.model, :loading)[i]. Along the lines of getvariable(pm, :loading, i)

Bibtex Citations for Formulatoins

Add Bibtex citations for the orginal proposal of specific formulations

Check for Feasibility of a Model

Make an easy way to test if a solution is feasible for a given model.

Give constraints names and return dicts of symbols

similar to variables.

Trilinear Product Relaxation

Add to relaxation schemes.

Enable more OTS tests on Travis

move some models over to open source integer solvers, such as Pajarito.jl

Call update_derived_values when reading in a JSON file

JuMP 0.16 Compatablity

Once this is working test for Julia v0.6 compatibility.

Refreshing Derived Values

See if there is a clean but high performance way of doing this.

Unit Tests for Matpower Parser Error Messages

Add unit tests for all Matpower parser error messages.

Abstracting on/off constraints

There is significant repeated code in expansion planning line constraints (i.e. _ne) and OTS on/off constraints (i.e. _on_off).

See if there is a clean way of avoiding this replication without excessive engineering.

Multiphase support

Feature idea.

Optimal power models have traditionally only been done at the bulk power level. But with distributed generation and more advanced volt-var control, there's more opportunity to benefit from optimal models at the distribution level. To do that best, models need to include three phases and include single and two-phase lines and loads..

More robust white space parsing in Matpower files

It would be nice to be able to support mixtures of tabs and spaces. For example see.

Fix Julia v0.5 Warnings

SLP Example

Develop an example of using SLP in PowerModels.

Speed up Tests

See if caching parsed versions of the model data can improve the speed of running package tests.

Documentation - README file

add something reasonable here.

Usecase Tests

Add unit tests to test code snippets in docs.

Variable Name Conventions

I propose the following a standard naming convention for the polar and rectangular variable spaces, let "v" be a complex number, then:

• vm - magnitude of v
• va - angle of v
• vr - real component of v
• vi - imaginary component of v

Strengthen DCLL OTS

in, function constraint_active_ohms_yt_on_off{T <: AbstractDCPLLForm}(pm::GenericPowerModel{T}, branch) add c4 = @constraint(pm.model, p_fr + p_to >= 0).

Consider adding a replicate index to all variables

To more readily support multi-time models.

Possible typos in constraints.jl

In constraint_active_loss_lb, p_fr and p_to are defined identically:

    p_fr = getvariable(pm.model, :p)[f_idx]
    p_to = getvariable(pm.model, :p)[f_idx]

This is also the case for v_fr and v_to, and q_fr and q_to in constraint_reactive_loss_lb:

    v_fr = getvariable(pm.model, :v)[f_bus]
    v_to = getvariable(pm.model, :v)[f_bus]

    q_fr = getvariable(pm.model, :q)[f_idx]
    q_to = getvariable(pm.model, :q)[f_idx]

Semicolon in Strings

In Matpower data files, add support for having semicolons in strings.

Remove arrays from internal data format

This helps in the sparse application of input and output data files.

Use cases

• modifying the internal data after loading
• specifying solution data

Matpower parser generator cost message

make the "std gen cost: ..." message a warning instead of stdout.

Remove Auxiliary Variables in Conic Objective

Update, objective_min_fuel_cost{T <: AbstractConicPowerFormulation}(pm::GenericPowerModel{T}) in objective.jl.

The key is to define the min on a norm form.

Documentation - Developers Guide

Add a special documentation guide / tutorial for developing new variable formulations and problem specifications.

Update README

Add TNEP to list of supported models, also use checkout instead of clone for to get the current development version.