Maximum power point tracking algorithms for single-stage photovoltaic power plants under time-varying reactive power injection

Abstract

The power electronic interface of traditional grid-connected photovoltaic (PV) systems includes a boost dc/dc converter and an inverter. In large PV power plants, the boost converter is usually eliminated by connecting an appropriate number of PV panels in series to achieve the desired voltage. This architecture, referred to as single-stage topology, is the subject of this paper. The paper presents a unified dynamic model which is able to reproduce the behavior of any single-stage PV power plant with an arbitrary PV array configuration through a single circuital representation. A methodology based on this unified model is developed to enhance the performance of standard iterative maximum power point tracking (MPPT) algorithms under time-varying reactive power injection. In particular, enhanced versions of the perturb & observe and incremental conductance algorithms are discussed. Furthermore, a predictive MPPT algorithm based on a neural network is proposed to improve the dynamic of the dc-link voltage. The unified model and MPPT control schemes are validated via detailed PSCAD/EMTDC computer simulations in a 450kW PV system, designed according to a typical “1000V dc” architecture. Real solar irradiance and cell temperature data collected in a partially cloudy day are utilized in the simulations, providing comparative performance under rapidly changing atmospheric conditions.