State estimation on stand-alone DC microgrids through distributed intelligence

The development of stand-alone microgrids brings about different challenges in the efficient coordination of sources, storage and loads. State estimation is especially challenging as these types of applications require robust and low-cost methods that can produce fast and accurate estimates without the provision of topology information or data communications across the network. This research aims to address such challenges for stand-alone DC microgrids. The Recursive Least Squares (RLS) parameter estimation method is used together with local measurements to obtain the Thevenin equivalent parameters required for autonomous coordination of the microgrid´s components. The presented on-line estimation method is simulated using Matlab/Simulink. The performance of the estimator is also tested using an experimental setup.