Design of a Location Based Adaptive MPP Tracker for PV System

Abstract

As solar irradiance varies hourly from day to day throughout the year for a location the output characteristics of solar photovoltaic (SPV) also vary in accordance. The behaviour of PV systems is non linear in nature. So, in a large PV system where more numbers of PV modules are connected in strings and arrays, the effect of irradiance is not evenly distributed. Thus it's quite tough to track the maximum power point (MPP) in such a condition for a large system. The existing MPPT algorithms are also inefficient to track global maximum power point (GMPP) for such systems due to presence of lots of local maximas and hotspots. In this work, a 5 MW Spy based power plant is designed with SunPower SPR-EI9-315 modules (nominal efficiency 19.31% under STC condition) by connecting total 15,864 modules with the configuration of 12 nos. of modules per string and 1322 nos. of strings in parallel. The forecasted global horizontal irradiance (GHI) data of Agartala, Tripura, India were logged hourly basis from January to December using System Advisor Model (SAM) simulator. The system was tested under these GHI data and different $\mathbf{v}_{\mathbf{mpp}}$ and MPPs were calculated precisely. Further, a MPP tracker was designed in MATLAB and a database was developed with the data of different maximum power point voltage $(\mathbf{V}_{\mathbf{mpp}})$ under different GHI imported from SAM. This adaptive database based tracker successfully tracked the GMPPs for the $\pmb{5\text{MW}}$ plant quickly and precisely for this location time to time basis. This independent system is capable to track the GMMPs hourly for everyday basis throughout the year for this location even without tracking the GMPPs by scanning each time unlike perturb & observe method and incremental conductance method. So, this is simple, reliable and faster in performance in comparison to the existing ones.