Investigation of the effect of conversion time and average number on performance in maximum power point tracking algorithms

In order to increase the efficiency of renewable energy systems, they need to be operated at maximum power point (MPP). This method, called Maximum Power Point Tracking (MPPT), consists of an electronic circuit and an algorithm that provides control. Switch and Observe (P&O) and Increased Conductance (INC) algorithms are the most widely used MPPT algorithms based on current and voltage measurements. In this study, the effects of averaging numbers and conversion times, which affect the measurement accuracy in classical MPPT algorithms, on the performance of the algorithms were investigated. A simulation study was conducted using thermoelectric generators and experimental studies were conducted using solar panels. It was observed that the ripple factor decreased as the averaging number and conversion time increased, but the times to reach the maximum point increased. While the averaging numbers and conversion times were increased in the P&O algorithm, a decrease in the minimum value of the power was observed, while an increase occurred in the INC algorithm. The minimum power for 64/128/256 averaging numbers in the P&O algorithm at a conversion time of 1.1 ms was measured as 8.3/8.0/7.7 W, respectively, while for the INC algorithm it was 7.5/7.75/7.8 W. The same situation was observed at a conversion time of 2,116 ms. The average power values were calculated in MPP for the P&O and INC algorithms. The average power was calculated greater for 128 averaging numbers in all conversion times for both algorithms. The average power for 64/128/256 averaging numbers in the P&O algorithm at a conversion time of 1.1 ms was calculated as 12.005/12.007/11.99 W, while for the INC algorithm it was 11.70/11.78/11.78 W.