Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Abstract

The solar system characteristics are affected due to few obscure terms, causing a reduction of photovoltaic system's power output. Also, partial shaded conditions (PSCs) lead to several peaks on photovoltaic (PV) curves, which decrease conventional techniques' efficiency Also, in these (PSCs), standard equations might not be implemented entirely. Therefore, this study aims, first to modify and re-establish the mathematical model of PV array under (PSCs). Second, heuristic algorithms (Cuckoo Search Algorithm (CSA) and Modified Particle Swarm Optimization (MPSO)) have been suggested and applied with PV system to promote output power under varying weather conditions and PSCs. Moreover, these algorithms can improve the dynamic response and steady-state PV systems' performance simultaneously and effectively. Later on, the following approaches, modified (MP&O) and (ANN), are also proposed to extract the photovoltaic system's maximum power. Then, MPPT problem is modeled and optimized on MATLAB environment where it is reliable to connect the programmable optimizer with Simulink of photovoltaic cell used to validate results. Finally, proposed methods are examined under several scenarios for (PSCs) to investigate its effectiveness. The results ensure that proposed tracker based on CSA can distinguish between the global and local maximum peaks of PV system effectively comparing to others MPPT approaches.

Marine Predator Algorithm (MPA)-Based MPPT Technique for Solar PV Systems under Partial Shading Conditions

“…A crucial condition in solar PV systems is the partial shading conditions (PSCs). These occur due to varying weather conditions, shadows caused by nearby buildings, passing clouds, trees, dust, and bird waste, among other things [30]. The characteristics of the solar PV under uniform conditions as well as under PSCs are depicted in Figure 4.…”