This paper presents a new version of the incremental conductance algorithm for more accurate tracking of the maximum power point (MPP). The modified algorithm is called self-predictive incremental conductance (SPInC), and it recognizes the operational region. It is capable of detecting dynamic conditions, and it detects sudden changes in power resulting from changes in the intensity of radiation or temperature. By selecting the appropriate step size, it obtains maximum power from the panel at any moment. The improved algorithm reduces output power ripple and increases the efficiency of the system by detecting the operating area and selecting the appropriate step size for each region. The SPInC algorithm divides the system’s work areas into three operating zones. It calculates the size of the appropriate step changes for each region after identifying the regions, which allows for more accurate tracking of the MPP and increases the system efficiency at a speed equal to the speed of the conventional method. These additional operations did not result in a system slowdown in the tracking maximum power. According to the MATLAB/Simulink simulation results, the SPInC algorithm is more efficient than conventional InC, and the ripple output power is reduced. SPInC is also compared to the improved perturb and observe (P&O) algorithm. In general, SPInC can compete with the popular algorithms that have been recently proposed for MPPT in the other researches.
The 3 filter based on the Kalman-like estimation scheme has been recognized as a outstanding tool for estimating the position and velocity signals of moving objects. Nevertheless, the performance of estimation heavily depends on the parameters and . In general, the choice of parameters is a trade-off optimization problem between the tracking accuracy and noise reduction capability. In order to obtain the suitable design of 3 filter for some specifications, a combined fuzzy logic and evolutionary optimization method is proposed for determining the parameter values. The simulation results are employed to illustrate the developed 3 filter which is capable of tracking the desired signals accurately and, at the same time, reducing the noise disturbance remarkably.
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