PowerModelsSE.jl
PowerModelsSE.jl is an extention package of PowerModelsDistribution.jl for Static Distribution System State Estimation.
A Distribution System State Estimator determines the most-likely state of distribution system given a set of uncertainties, e.g., measurement errors, pseudo-measurements, etc. These uncertainties may pertain to any quantity of any network component, e.g., :vm of a :bus, :pd of a :load, etc.
Currently, uncertainties may either be described by:
- a deterministic value
Float64, or - a continuous univariate distribution
ContinuousUnivariateDistribution:- a normal distribution, modeled through either WLS or LAV approach, or
- a non-normal distribution, modeled through -logpdf.
Core Problem Specification
- State Estimation (SE) as equality constrained optimization problem
Core Network Constraint Formulations
- AC Polar (exact)
- AC Rectangular (exact)
- AC IV Rectangular (exact)
- SDP (positive semi-definite relaxation)
All the formulations are three-phase unbalanced and feature accurate delta/wye load models. The exact formulations also feature delta/wye transformer models. Network constraint, load and transformer models are taken from PowerModelsDistribution.jl
Network Data Formats
- OpenDSS ".dss" files in the PowerModelsDistribution format
- CSV ".csv" file with measurement a statistical information for state estimation
Summary of State Estimation Possibilities
| - | ACP | ACR | IVR | SDP |
|---|---|---|---|---|
| BI/BF | BI | BI | BF | BF |
| Simple SE[1] | Available | Available | Available | Available |
| Advanced SE[2] | Available | Available | Available | Unavailable |
| 4-wire[3] | v0.2.0 | v0.2.0 | v0.2.0 | v0.2.0 |
Installation
The latest stable release of PowerModelsSE can be installed using the Julia package manager:
] add https://github.com/timmyfaraday/PowerModelsSE.jl.gitIn order to test whether the package works, run:
] test MultiStateSystemsAcknowledgements
This code has been developed at KU Leuven (University of Leuven). The primary developers are Tom Van Acker (@timmyfaraday) and Marta Vanin (@MartaVanin) with support for the following contributors:
- Frederik Geth (@frederikgeth), CSIRO, General PowerModelsDistribution.jl Advice.
- Sander Claeys (@sanderclaeys), KU Leuven, General PowerModelsDistribution.jl Advice.
License
This code is provided under a BSD license.
Notes
Currently, bad data detection techniques and observability considerations are out of scope.