/Code_for_CCACOPF

This repository is created for "Chance Constraints for Improving the Security of AC Optimal Power Flow"

Primary LanguageJulia

This code was developed under Julia v0.4 by Miles Lubin in 2016 and later
modified by Yury Dvorkin. In preparation for this release (March 2018), we were
able to run it under only Julia 0.5.2. On Julia 0.5 it prints some deprecation
warnings that can be safely ignored. Note that the official releases of Julia
0.5 and earlier no longer run on Linux
(https://discourse.julialang.org/t/git-ssl-errors-while-installing-packages).

The following packages must be installed:

  - Distributions
  - Ipopt
  - JuMP
  - JuMPChance
  - MAT
  - MatpowerCases

To run the code, execute main.jl, or include() it from a Julia prompt.

The input data is given as follows:

  - Configuration file case.dat
  - File acopf_input.jl uses MatpowerCases to load the system data based on the
    configuration in case.data
  - We also specify additional input data in lines 38-59 of main.jl

The results of the solve are returned by createandsolvemodel().

The CCACOPF model is formulated in model_nl.jl (JuMP model `m_chance`). Prior to
formulating the CCACOPF model we solve a deterministic ACOPF model (JuMP model
`m`). The formulation for the deterministic ACOPF model is based on code
provided by Harsha Nagarajan (LANL).