Research On MPPT And Island Detection Method Based On State Estimation In The PV Grid Power Generation System

The interacting multiple model algorithm was a hybrid estimation method using multiple model to track the state of nonlinear systems.Through the measurement,it is verified that the photovoltaic power generation array had measurement noise.In the partial shadow cases,it had many characteristics.They are nonlinear,time-varying uncertainty and more local power peak.The improved interacting multiple model algorithm was adopted to improve the accuracy of tracking power curve.The multiple models switching probability was used to identify the multiple local power peak to avoid misjudgment problem.The new technique proposed was able to quickly and accurately track the maximum power point(MPPT),regardless of whether the shadow cases.The efficiency of photovoltaic power generation was improved.The correctness and validity of the new control strategy were verified by the simulation and the experiment.In multi-inverter PV system and network for the study,the modern state estimation theory is introduced to the detection of islanding,A passive islanding detection method based on sinusoidal estimates model of the PCC voltage is proposed.The voltage sine wave discrete state estimation model was derived,the PCC voltage state was real-timely monitored by the strong tracking filter,the real-time status parameters island phenomenon was identified by BP neural network to distinguish normal,island and pseudo-island phenomenon.The simulation and experimental results show that: the proposed islanding detection methods can be effectively and quickly detected island.