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... For this reason, the microgrid model implemented and described in this paper utilizes a phasor representation. It is important to note that OpenIPSL does not suffer the limitations of traditional phasor domain tools, as it provides interfaces to model unbalances [22] and physics-based interfaces to couple more detailed EMT-type models [23]. In addition, because the microgrid model is being developed in Modelica, this opens up the possibility for its use in time-scales ranging from milliseconds to hours, contrary to that of power system dynamic simulators, which would restrict the use of these models to tens of seconds. ...
This paper describes the development of a phasor-based campus microgrid model utilizing the Modelica language and the OpenIPSL library. The phasor-based modeling approach was chosen because the resulting microgrid model would yield faster simulation run times when compared to models developed using electromagnetic transient (EMT) methods. Beyond the benefits of simulation performance, this becomes necessary when attempting to understand dynamic phenomena arising under emergency conditions across time scales ranging from milliseconds to hours, which will aid in developing resiliency improvement plans for the real-world campus microgrid that the model represents. Considering the increasing number of distributed energy sources (DERs) being added to power grids across the world and the paradigm shift on how electrical grids can operate with more DERs, the implementation of such a microgrid campus model can help in the development and testing new control strategies to support new operational approaches while guaranteeing system stability and resiliency. The added benefit of having the microgrid model in Modelica is that it can be simulated in any Modelica complaint tool (both proprietary or not), preserving an open-source code, unlocked for the user to explore and adjust the implementation as well as observe and edit the mathematical formulation. This enables not only nonlinear time simulation, but also linear analysis techniques and other approaches to be applied.
... The implemented options of choice related to the basic OpenIPSL models are bus, line, and generator. However, this can be easily modified and expanded by the user to include a choice of other devices such as STATCOMs [19], advanced converters [20], and renewable sources [21]. ...
This paper describes tool that is created for massive data generation employing phasor time-domain Modelica simulations and using the Open-Instance Power System Library (OpenIPSL). provides a pipeline for generating large amounts of data, considering a wide range of operating conditions and potential contingencies experienced by a power system. The need for large-scale power system dynamic data arises with the development of Machine Learning (ML) solutions in the context of the modernization of the existing power grid. implements algorithms to process different types of input data, perform steady-state computations, run dynamic simulations and linear analysis routines, and label the resulting data sets. The tool has been developed entirely in Python 3 and is compatible with the Modelica IDEs - Dymola and OpenModelica.
