The way of implementing an adaptive maximum power point tracking algorithm for photovoltaic (PV) applications in a field programmable gate array (FPGA) is described in this paper. A dual Kalman filter allows estimating the settling time of the whole system, including the PV source and the dc/dc converter controlling the operating point thereof, so that the tracking algorithm self adapts its parameters to the actual weather conditions. The real-Time identification need of this application requires an FPGA platform, so that the intrinsic algorithm parallelism is exploited and the execution time is reduced. The tradeoff solutions proposed in this paper, accounting for the algorithm complexity and the limited FPGA hardware, as well as some solutions for optimizing the implementation are described. The proposed adaptive algorithm is implemented in a low-cost Xilinx Spartan-6 FPGA and it is validated through experimental tests.
FPGA-Based Implementation of Dual Kalman Filter for PV MPPT Applications
01.01.2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
photovoltaic (PV) system , Computer Science Applications1707 Computer Vision and Pattern Recognition , Information System , field programmable gate array (FPGA) , Electrical and Electronic Engineering , dual Kalman filter (DKF) , Control and Systems Engineering , Adaptive maximum power point tracking (MPPT) controller
DDC: | 629 |
Implementation of an adaptive Kalman filter
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