Modeling of condensation is important to estimating the

residual water in small channels. The residual water that

forms becomes a water source for permeable materials

such as wooden structure or insulation. A model has been

implemented in Modelica that will predict the amount of

residual moisture after a period of water build up. This

model includes parameters to relate droplet physics to a

control volume. The parameters provide an macroscopic

means of varying droplet adhesion force, droplet velocity,

and drainage dynamics. Using CFD data as an example of

real world data, this model has been correlated to demonstrate

the effects of the parameters.

The North American Electric Reliability Corporation (NERC) is expected to mandate model validation of power plant equipment in the near future. This will create a need to validate models for a large fleet of existing and future power plants. Historically, model validation of synchronous generators, excitation system, turbine governor, and other power system equipment has been conducted in diverse platforms. As a contribution to the power system model implementation using Modelica language and validation against commercial tools this work continues to develop power system component models and enriching the Open-Instance Power System Library (OpenIPSL). As a part of the development of OpenIPSL this paper describes the development of models used by North American utilities that follow NERC modeling requirements, including models of a synchronous generator, an excitation system, a turbine and governor using Modelica language in Dymola. The component implementation process is described and the validation of the models implemented in Modelica against PSS/E using both a single machine infinite bus (SMIB) and multi-machine system models is illustrated.

Degradation of the catalyst layer is a major challenge for the commercialization of polymer electrolyte membrane fuel cells (PEMFCs). Numerical modeling helps to understand and analyse the degradation phenomena, to transfer results from accelerated stress tests (ASTs) to real applications and to optimize operating conditions regarding degradation. We implemented a typical catalyst degradation model for platinum used in literature in Modelica. A numerical analysis shows the problem of “stiffness” for these models, meaning the tremendous difference in time constants. Assuming the platinum ion concentration in the ionomer to be in quasi-equilibrium helps to reduce the “stiffness”, increases simulation speed and numerical robustness without any relevant inaccuracy. For a typical AST, the simulation speed can be more than doubled ending in a real-time factor of over 1,000. Thus, 500 hours of AST can be simulated within less than 30 minutes, which gives room for extensive analysis with the model.