StochasticPowerModels

StochasticPowerModels.jl is an extension package of PowerModels.jl for Stochastic (Optimal) Power Flow. It is designed to enable inclusion of uncertainty in Steady-State Power Network Optimization.

For additional background on the approach, please read our PSCC paper.

Note that development is ongoing, and changes can be breaking without notice. We plan to register the package once we feel comfortable with the state of the implementation.

Core Problem Specification

• Stochastic Optimal Power Flow (sOPF)

Core Network Formulation

• Exact
  • ACR
  • IVR

Core Stochastic Specification

For now, we only support Polynomial Chaos Expansion. We may add alternative stochastic optimization methods at a later stage.

Network Data with Stochastic Data Extension

• Matpower ".m" files, extended to include:
  • stochastic germ: mpc.sdata,
  • stochastic bus data: mpc.bus_sdata, including: dst_id, μ, σ, λvmin and λvmax,
  • stochastic gen data: mpc.gen_sdata, including: λpmin, λpmax, λqmin and λqmax, and
  • stochastic branch data: mpc.branch_sdata, including: λcmax.

For an example, the user is referred to /test/data/matpower/case5_spm.m

Installation

The latest stable release of StochasticPowerModels can be installed using the Julia package manager:

] add https://github.com/timmyfaraday/StochasticPowerModels.jl.git

In order to test whether the package works, run:

] test StochasticPowerModels

Acknowledgements

The primary developer is Tom Van Acker (@timmyfaraday), with support from the following contributors:

• Arpan Koirala (@arpkoirala), KU Leuven, ACR formulation
• Frederik Geth (@frederikgeth), CSIRO, reduced IVR formulation

License

This code is provided under a BSD license.