Improvement of Self-Predictive Incremental Conductance Algorithm with the Ability to Detect Dynamic Conditions

Abstract

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.

Performance Analysis of an Incremental Conductance MPPT Algorithm for Photovoltaic Systems Under Rapid Irradiance Changes

“…This happens until the slope becomes zero, and the adjustment of the voltage value will stop, indicating that the MPP has been reached [23]. Mathematically, it can be seen in equations (6) to equations (8) [23], [24]. The InC algorithm, as shown in Figure 6, is a conventional algorithm widely used nowadays because of its simple characteristics and cheaper financing and application [25], [26].…”

Benefits of Fuzzy Logic on MPPT and PI Controllers in the Chain of Photovoltaic Control Systems

“…Under these conditions, by substituting ( 4)- (7) in Equation ( 2), the following relations can be expressed [15]:…”

“…Jalali Zand and Hsia [7] developed a PV system with MPPT based on self-predictive incremental conductance (SPInC) and applied a DC-DC boost converter. According to these authors' Matlab/Simulink simulation results, the SPInC algorithm outperforms the classical InC, and the output power has a minimal ripple.…”

Design of an On-Grid Microinverter Control Technique for Managing Active and Reactive Power in a Microgrid

“…Therefore, the maximum power point tracking (MPPT) of the panel must be monitored. For this, various MPPT techniques have been developed [21][22][23][24][25][26]. In this research, the incremental conductance algorithm is implemented to achieve this objective, and the scheme is shown in Figure 8.…”