Abstract

PurposeThe purpose of this paper is to focus on two major areas of concern for the Photovoltaic (PV) system, i.e. power quality and maximum power point tracking (MPPT). Novel control strategies have been proposed for both these issues, and their respective superiorities over the existing techniques have been established. On the other hand, as far as MPPT is concerned, two limitations are found in the available techniques. One is the inability of effective MPPT in dynamic conditions where the environmental parameters changes very rapidly. Second one is the ineffective tracking of global maxima under partial shading conditions.Design/methodology/approachHere, modified Kalman filtering approach has been applied for estimating the reference current of active power filter, incorporated for power quality improvement. The proposed Kalman algorithm introduces a weighted matrix, which advances the estimated values of state variables. This paper presents a simple and enhanced model-based (MB) MPPT algorithm that has the capability of tracking MPPT effectively in both these working conditions. The proposed MB algorithm uses the mathematical modelling, and based on precised estimation of parameters, it pre-determines the MPP analytically.FindingsIt has been tested successfully for dynamic variations of insolation, temperature and partial shading, where all these three parameters are rigorously varied over the full scale of practical values. The results have been also investigated experimentally and compared with the simulated one. A close matching of both the results has been shown through the plots, which validates the effectiveness of proposed algorithms.Originality/valueThis research paper is part of the original research work carried out in Lab. Simulated results are obtained in MATLAB/Simulink platform, whereas these are further validated experimentally on 2-KW panel constituted with all types of commercial products, namely, mono, poly and thin-film.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call