A Decoupled Adaptive Noise Detection Based Control Approach for Grid Supportive SPV System - 2017

PROJECT TITLE :

A Decoupled Adaptive Noise Detection Based Control Approach for Grid Supportive SPV System - 2017

ABSTRACT:

A grid supportive 2-stage 3-part four-wire solar photovoltaic (SPV) system is presented in this paper, wherein a boost converter is used as a 1st stage to serve the perform of most power point tracking (MPPT) and a four-leg voltage supply converter (VSC) is employed to feed the extracted SPV energy, along with supporting distribution system for improvement in the ability quality. Unlike conventional SPV inverters, the proposed solar energy conversion system provides additional functionalities like balancing of grid currents, reactive power compensation, mitigation of harmonics, and neutral current elimination in grid aspect neutral conductor. An extra feed-forward term is added in the control loop to supply fast dynamic responses. The PV array voltage is continuously adjusted using a boost converter to achieve MPPT. A control approach using decoupled adaptive noise detection (DAND) algorithm is employed for controlling the four-leg grid-tied VSC. The DAND algorithm is a simple approach using 2 multipliers, one integrator, and one summer per part for detection of helpful element of load current. The proposed control algorithm provides features like simple structure, quick convergence, frequency adaptive detection, and good steady-state performance. The grid currents are found adhering to an IEEE-519 normal, even below nonlinear and unbalanced masses at common point of interconnection.

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