Sequence extraction-based low voltage ride-through control of grid-connected renewable energy systems

Various faults can cause voltage sag in the power grid at different voltage levels across the network. Balanced or unbalanced voltage sags lead to grid instability by tripping off a large number of wind or solar power plants from the electric power network. This is particularly problematic to maintain the stability of renewable energy-rich converter-dominated modern power systems. To mitigate the adverse effects of voltage sag, grid-connected converters (GCCs) need to be capable of operating in self-healing and fault-tolerant mode by embedding low voltage ride-through (LVRT) capability into the control system of GCCs. In order to facilitate the implementation of LVRT capabilities for unbalanced faults, fast and accurate frequency-adaptive sequence extraction of grid voltages and currents is essential. This motivated the present work of making a systematic comparison of adaptive observer-based sequence extraction techniques to provide LVRT capabilities into the control system of GCCs. In order to show the effectiveness of each observer, various comparative analyses were performed through Matlab-based numerical simulation. Different observers were benchmarked by the dynamic performance improvement during the low-voltage fault period. Experimental results using a laboratory-scale prototype GCC show that adaptive observers are a suitable choice of sequence extractors for LVRT operation of grid-connected converters in unbalanced and distorted grids. The results obtained in this work will contribute to enhancing the stability of modern power systems that are getting more and more converter-dominated.