This paper elaborates a comprehensive overview of a photovoltaic (PV) system model, and compares the attributes of various conventional and improved incremental conductance algorithms, perturbation and observation techniques, and other maximum power point tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system. Following a discussion of the MPPT algorithms in each category, a table is drawn to summarize their key specifications. In the performance evaluation section, the appropriate PV module technologies, atmospheric effects on PV panels, design complexity, and number of sensors and internal parameters of the PV system are outlined. In the last phase, a comparative table presents performance-evaluating parameters of MPPT design criterion. This paper is organized in such a way that future researchers and engineers can select an appropriate MPPT scheme without complication.

When a photovoltaic (PV) system is exposed to physical objects and cloud coverage and connected to bypass diodes, a partial shading condition (PSC) occurs, which causes a global maximum power point (GMPP) and numerous local maximum power points (LMPPs) on the power-voltage (P-V) curve. Unlike conventional MPPT techniques that search for multiple LMPPs on the P-V curve, it is possible to track GMPP straightaway by designing a simple but robust MPPT technique that results in faster tracking speed and low power oscillations. Hence, in this study, an improved proportional-integral (PI) coordinated Maximum Power Point Tracking (MPPT) algorithm is designed to enhance the conversion efficiency of a PV system under PSC with fast-tracking speed and reduced power oscillations. Here, PI controllers are used to mitigating the steady-state errors of output voltage and current of PV system that later on passed through an incremental conductance (INC) algorithm to regulate the duty cycle of a dc–dc boost converter in order to ensure fast MPPT process. The PV system is integrated with the grid through an H-bridge inverter, which is controlled by a synchronous reference frame (SRF) controller. Tracking speed and steady-state oscillations of the proposed MPPT are evaluated in the MATLAB/Simulink environment and validated via a laboratory experimental setup using Agilent solar simulator and dSPACE (DS1104) controller. Results show that the proposed MPPT technique reduces the power fluctuations of PV array significantly and the tracking speed of the proposed method is 13% and 11% faster than the conventional INC and perturb and observe (P&O) methods respectively under PSCs.