Delta-Bar-Delta Neural Network (NN) Control of Voltage Source Converter Base Adaptive Control Scheme for Power Quality Improved Grid – Interactive Solar PV- Battery System

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Dr. N.C. Kotaiah, Veeranjaneyulu Gopu, Y.Sumanth, Yarlagadda Mallikharjuna Rao, Boppudi Sarath Chandra, Sarayu. Vunnam


These grid interaction solar PV-battery systems can handle unbalanced and balanced three-phase four-wire (3P-4W) nonlinear loads as well as single-phase loads of various types. AL-BP control is capable of automatically adjusting complex nonlinear systems including grid-interactive 3-phase, 4-wire systems that have critical imbalance, and feeding highly nonlinear loads, without requiring any additional tuning. A robust control mechanism is needed to improve performance of the system and power quality for solar array solar energy conversion systems. The module neural network management incorporates DSTATCOM functions such as minimizing harmonics, balancing of load, and improving power factor. The fuzzy logic control technique delivers superior precision due to the neural network's combinational neural structure. This validation validates that the system is capable of maintaining power quality, according to IEEE-519 requirements. This approach significantly increases the steady-state and dynamic capabilities of a grid-connected 3-phase, 4-wire (3P-4W) PV-battery system. For verification, a real-time DSP processor has been used to implement the AL-BP control technique

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