This is a free software tool for analyzing the dynamics of power systems based on dq0 signals. It is designed to simulate and analyze power systems that include several generators and loads, and possibly a large transmission network. The software provides tools for constructing dynamic models of the system components, and enables analysis in the frequency domain or the time domain. The manual (including tutorial) and software provide simple explanations and examples that can help one get started, even if he/she has no prior knowledge on power system dynamics, or the dq0 transformation.

MANUAL/TUTORIAL | SOFTWARE |

- Download the software files from MATLAB Central, and copy them to a directory of your choice, e.g.,
*C:\DQ0 dynamics*. - Setup the directory in your MATLAB path. In the MATLAB, go to
*File*>*Set Path*... and click on*Add with Subfolders*.... Now, select the directory that contains the*DQ0 dynamics*folder. - Save the path for future MATLAB sessions (usually administrator privileges are necessary).
- For more advanced installation options please see the manual.

Several approaches exist for modeling the dynamic behavior of three-phase power systems. Transient simulations that use the abc frame of reference describe the system by means of physical quantities, and thus offer high accuracy and flexibility. This approach is often the most general, since it applies to nonsymmetric systems, and is valid over a wide range of frequencies. Another popular approach is to model the power system using time-varying phasors, often by using the network power flow equations. This approach has many benefits, one of them is that the transmission network is described by means of purely algebraic equations. However, time-varying phasors are only applicable at low frequencies, under the assumption that the system is quasi-static.

A solution that complements these two well-known approaches is to model large power systems on the basis of dq0 quantities. This approach is not as general as abc-based models, and is advantageous mainly when the network and units are symmetrically configured. However, dq0 models combine two properties of interest: similar to transient models, dq0-based models are derived from physical models, and are therefore accurate at high frequencies, so the assumption of a quasi-static network is not required. In addition, similarly to time-varying phasors, dq0 models are time-invariant. This property allows to define an operating point, and enables small-signal analysis, and stability analysis.

The software describes power systems by means of signal-flow diagrams, in which each component is modeled by dq0 quantities. Transmission networks are represented by linear state-space models with voltage inputs and current outputs. The software automatically constructs the model matrices based on the network data. This can be done using the graphical user interface, or directly from the Matlab command line. The resulting state-space models are of minimal order, and use sparse system matrices, and are therefore suitable for large power systems. The network and its components are modeled using a dq0 transformation that is based on a unified reference frame.

We kindly request that publications derived from the use of this software acknowledge this fact by citing reference(s) from the list:

- J. Belikov and Y. Levron, "A sparse minimal-order dynamic model of power networks based on dq0 signals,"
*IEEE Transactions on Power Systems*, to be published. - Y. Levron and J. Belikov, "Modeling power networks using dynamic phasors in the dq0 reference frame,"
*Electric Power Systems Research*, 144, pp. 233–242, Mar. 2017. - Y. Levron and J. Belikov, "Open-source software for modeling and analysis of power networks in the dq0 reference frame," in
*IEEE PES PowerTech Conference*, Manchester, UK, Jun. 2017, pp. 1-6. - J. Belikov and Y. Levron, "Comparison of time-varying phasor and dq0 dynamic models for large transmission networks,"
*International Journal of Electrical Power & Energy Systems*, 93, pp. 65--74, Dec. 2017. - Y. Levron and J. Belikov, "Reduction of power system dynamic models using sparse representations,"
*IEEE Transactions on Power Systems*, 32, pp. 3893-3900, Sep. 2017.

Note: full text versions can be alternatively accessed here.

Any questions?

Please contact us: Juri Belikov or Yoash Levron.