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

Abstract

A grid supportive two-stage three-phase four-wire solar photovoltaic (SPV) system is presented in this paper, wherein a boost converter is used as a first stage to serve the function of maximum power point tracking (MPPT) and a four-leg voltage source converter (VSC) is used to feed the extracted SPV energy, along with supporting distribution system for improvement in the power quality. Unlike conventional SPV inverters, the proposed solar energy conversion system provides extra functionalities such as balancing of grid currents, reactive power compensation, mitigation of harmonics, and neutral current elimination in grid side neutral conductor. An extra feed-forward term is added in the control loop to provide fast dynamic responses. The PV array voltage is continuously adjusted using a boost converter to achieve MPPT. A control approach employing decoupled adaptive noise detection (DAND) algorithm is used for controlling the four-leg grid-tied VSC. The DAND algorithm is a simple approach using two multipliers, one integrator, and one summer per phase for detection of useful component of load current. The proposed control algorithm gives features such as simple structure, fast convergence, frequency adaptive detection, and good steady-state performance. The grid currents are found adhering to an IEEE-519 standard, even under nonlinear and unbalanced loads at common point of interconnection.