The new maximum power point tracking algorithm using ANN-based solar PV systems

In grid connected photovoltaic (PV) systems, maximum power point tracking (MPPT) algorithm plays an important role in optimizing the solar energy efficiency. In this paper, the new artificial neural network (ANN) based MPPT method has been proposed for searching maximum power point (MPP) fast and exactly. For the first time, the combined method is proposed, which is established on the ANN-based PV model method and incremental conductance (IncCond) method. The advantage of ANN-based PV model method is the fast MPP approximation base on the ability of ANN according the parameters of PV array that used. The advantage of IncCond method is the ability to search the exactly MPP based on the feedback voltage and current but don't care the characteristic on PV array. The effectiveness of proposed algorithm is validated by simulation using Matlab/ Simulink and experimental results using Card DSPACE 1104. © 2010 IEEE. Author Keywords: Artificial neural network (ANN); Incremental conductance (IncCond); Maximum power point tracking (MPPT); Photovoltaic (PV) Index Keywords: Artificial Neural Network; Combined method; D-space; Feedback voltages; Grid- connected photovoltaic system; Incremental conductance; Incremental conductance (IncCond); Maximum power point; Maximum power point tracking; Maximum Power Point Tracking algorithms; Model method; Photovoltaic (PV); PV arrays; Simulink; Solar PV systems; Algorithms; Energy efficiency; Optical flows; Photovoltaic cells; Photovoltaic effects; Pumps; Solar energy; Solar power generation; Neural networks