OpenDSSDirect

OpenDSS is an open-source distribution system simulator. This Julia package implements a "direct" library interface to OpenDSS. See this documentation for detailed information on the direct library interface to OpenDSS. The direct library interface can be faster than the more traditional COM interface.

Installation

For now, this package is registered, so you can use the following to install:

Pkg.add("OpenDSSDirect")

To install the latest development version, use the following from within Julia:

Pkg.checkout("OpenDSSDirect")

This package includes OpenDSS as a library. You do not have to install OpenDSS separately. In particular, it includes the OpenDSSDirect dynamically linked library that implements the direct-access API.

Note that this should work on 32- and 64-bit Windows systems and 64-bit Linux and Mac systems. The Windows dynamic-linked libraries are taken from the official libraries ccompiled by Delphi. The Linux library is based on the LazDSS branch. The Linux library was compiled on an older version of Linux (Centos 6.4). It should run on most newer versions of Linux. If it does not, you can try compiling the library on your system. Including DLL binaries is not the best practice, but this works well enough for now. Installing and compiling Lazarus and LazDSS is not easy to do as part of package installation.

For compiling libraries, please see OpenDSSDirect.make.

Features

Julia is a fast, flexible numerical language with Matlab-like syntax. Like Python or Matlab, scripting OpenDSS can be used for Monte-Carlo batch runs, parameter sweeps, post processing and plotting of results, and more.

Julia has several key features for advanced operations with OpenDSS:

Parallel operations – Julia supports several ways to process data in parallel. This includes parallel operations on multiple CPU cores and parallel operations on processes in a cluster. See examples/8760_pmap.jl for an example of an annual simulation split among local CPU cores.
Optimization – Julia has strong support for optimization.
Custom solutions and custom models – Because Julia compiles to codes that run as quickly as C programs, it is possible to implement custom solutions, and these custom solutions can contain custom models implemented in Julia. The basic idea is to run a custom solution as described in OpenDSS Solution Interface.pdf. Custom control or power control elements can be implemented between each model iteration. See examples/low-level-solver.jl for an example with a custom solver, including a case with an alternate sparse matrix solver.

Example

The dss function is the main function for passing commands to OpenDSS. After that, a number of modules are available to access different data structures in OpenDSS. Here is an example summing the kW and kvar from loads using the Loads module:

using OpenDSSDirect.DSS
filename = Pkg.dir("OpenDSSDirect", "examples", "8500-Node", "Master.dss")
dss("""
    clear
    compile $filename
    solve
""")

loadnumber = Loads.First()
kWsum = 0.0
kvarsum = 0.0
while loadnumber > 0
    kWsum += Loads.kW()
    kvarsum += Loads.kvar()
    loadnumber = Loads.Next()
end

OpenDSSDirect

Installation

Features

Example

Contents