An improved adjustable step adaptive neuron based control approach for grid supportive SPV system

This paper deals with a three phase grid supportive kind of PV generation system. The proposed system is said grid supportive as it not only feeds the energy generated by solar PV system intro the grid but also helps at power quality improvement front of distribution system. A two stage topology is proposed, wherein the first stage is a boost converter which extracts the energy from the PV array and the second stage is a grid interfaced VSC (Voltage Source Converter). The VSC feeds extracted solar energy into the grid along with harmonics elimination, reactive power compensation and grid currents balancing. An improved adjustable step adaptive neuron based control approach is used for estimation of average power consuming component of load current. Moreover, a feed forward term is added as PV array contribution to grid currents, which helps in fast dynamic response due to ambience changes. The DC link voltage is regulated using a PI controller on DC link of the VSC. The output of PI controller is designated as loss component of system. In the proposed approach, the load, PV array and loss contributions are kept decoupled. The experimental results confirm the feasibility of the proposed control algorithm. The THD (Total Harmonics Distortion) of grid currents has been found well under IEEE-519 standard even under nonlinear loads at CPI (Common Point of Interconnection).