Abstract
Backgrounds: Solar photo-voltaic (PV) arrays have non-linear characteristics with distinctive maximum power point (MPP) which relies on ecological conditions such as solar radiation and ambient temperature. In order to obtain continuous maximum power (MP) from PV arrays under varying ecological conditions, maximum power point tracking (MPPT) control methods are employed. MPPT is utilized to extract MP from the solar PV array, high-performance soft computing techniques can be used as an MPPT technique. Results: In order to show the feasibility and performance of the proposed Artificial Intelligence based Perturbe and Observe (AIAPO) MPPT controller, a simulation analysis has been carried out using the PV system. Combined results with different MPPT systems for power, voltage and current waveforms are the output values increase to 272.4W, 157V and 1.74A respectively. Using proposed AIAPO MPPT provides more accurate and stable result as compared to Perturbe and Observe (PO), Fuzzy Logic (FL) and Artificial Neural Network (ANN) based MPPT Technique. As per the experimentation performed by various MPPT techniques are carried out for PV system which are clearly indicating that the comparative analysis of power, voltage and current performance of PV system (i.e. have been recorded 272.4W, 157V and 1.74A) using proposed MPPT method which is better than the PO based MPPT (i.e. 169.1W, 127V, 1.43A), FL based MPPT technique (i.e. 256.9W, 152V, 1.69A) and ANN based MPPT technique (i.e. 265W, 154V, 1.71A) correspondingly. Conclusions: The aim of this paper is to track MPP from the solar PV array by the proposed hybrid controller for irradiation changes and comparing results with PO, FL and ANN based MPPT controllers. Different MPPT techniques have been used to compute MPP and improved efficiency of the PV panel. AIAPO, ANN, FL and PO MPPT methods have been chosen to obtain this objective. Simulation results showing that the system in which proposed control method has been used gives better performance and reduce fluctuations of the MPP as compared to PO, FL and ANN based MPPT technique at rapid changes of irradiation. In order to fabricate a reliable and real time hybrid system, there is a massive scope of research to develop multi-input renewable energy systems.
A Novel Artificial Intelligence based Hybrid Maximum Power Point Tracking Technique for Solar Photovoltaic System
