Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Power system simulation is an important tool for the planning and operation of electric
power systems. With the growth of large-scale power systems and penetration of new
technologies, the complexity of power system simulation has increased. In this back-
ground, achievement of valuable simulation results in the simulation has become one of
the important research questions in electrical power engineering eld.
The most eective solution of this question is to develop accurate models for the power
system. However, the complexity and diversity of power system components make the
accurate modelling dicult while the simulation is time consuming. To cope with the
problem, powerful modelling language which can realize not only accurate model repre-
sentation, but increase computational eciency of model simulation is required.
In this thesis, power system modelling and simulation is achieved using an object-oriented,
equation-based modelling language, Modelica. Firstly, some essential component mod-
els in power systems are developed in Modelica. The software-to-software validation
of the models are performed. To serve this purpose, dierent software environments
are exploited depending on software used for the model development. Moreover, four
dierent-scale test systems are implemented, simulated and validated with the developed
models. Through the investigation of the simulation results, the performances of Modelica
in undertaking power system simulations are evaluated.
In addition, since imprecise parameter values in the models are also problematic for accu-
rate model representation, system identication is performed to obtain accurate parame-
ter values for the models. The parameters of a model are identied based on measurement
data. This thesis also illustrates the application of Modelica on model exchange, and the
combination of Modelica and FMI technology on system identication.
Finally, examples of application of the RaPId Toolbox on measurement-based power
system identication are provided.
2014. , 128 p.