A5000403895- Probabilistic and Robust Engineering Design
- Machine Fault Diagnosis Techniques
- Energy Load and Power Forecasting
- Fault Detection and Control Systems
- Control Systems and Identification
- Wind Energy Research and Development
- Wind Turbine Control Systems
University of Southern Denmark
2015-2017
In this study, we derive an eigenvector-based multivariate model of a power grid from the wind farm's standpoint using dynamic principal component analysis (DPCA). The main advantages our over previously developed models are being more realistic and having low complexity. We show that behaviour turbines perspective can be represented with cumulative percent value larger than 95% by only 4 out 9 registered variables, namely 3 phase voltage current, frequency! active reactive power. further...
Wind turbine generators (WTGs) are required to operate at different levels of voltage fluctuations in the power grid. When exceed standard levels, i.e. over and under voltage, they affect performance WTGs. In this study, we estimate distribution voltages by utilizing Extreme Value Analysis. Assuming as a random variable, show that can be considered extreme deviations from probability median. The results approve one WTG follow Generalized distribution. Since WTGs do not necessarily experience...