Comparison of aggregated models for CHIL validation of PV power plant controllers

Comparison of aggregated models for CHIL validation of PV power plant controllers

Venkateswaran, Srivats (TU Delft Electrical Engineering, Mathematics and Computer Science)

Cvetkovic, Milos (mentor)
Rueda Torres, Jose (mentor)

Delft University of Technology

2019-08-28

With the increase in the number of utility-scale PV power plants being integrated into the grid, there has been a rise in interest in the testing and validation of components involved in these power plants. Due to the inflexibility of the current field testing methods, there is an increased push towards validation of the involved components using Hardware-in-the-loop. However, to test components, entire power plants cannot be modelled due to computational constraints. With the help of this masters thesis, there has been an attempt to compare aggregation methods which can be used to reduce the computational burden, for certain kinds of tests such as active and reactive power response. In this study, three different types of aggregated models were compared to
the detailed model - Magnified model, Oversized model and the Frequency Dependent Network Equivalent (FDNE) model. The study modelled a 19.25 MW PV power plant as the base detailed model of which aggregated models have been derived from. These aggregated models have also been implemented in real time to understand their response. It was observed that the models, while deviating from the detailed model in terms of losses, do reach the same steady state. Magnified model can be concluded to have worked the best. However, it is also the slowest among the three aggregated models. In real time, the oversized model was able to run successfully while the magnified model proved to be too slow,computationally. These results can help design a better aggregating algorithms for validation modelling using real-time system hardware-inthe-loop systems.

PV power plant
Aggregate modelling
Control Hardware in Loop

http://resolver.tudelft.nl/uuid:7a6e09db-2e5e-43bf-8fe5-006f57557bb3

Student theses

master thesis

© 2019 Srivats Venkateswaran