Grid-Connected PV System Under Partial Shading Condition Using PSO Algorithm

Under both static and dynamic weather circumstances, maximum power point tracking (MPPT) is a fundamental and mandatory need for photovoltaic (PV) systems. In static weather conditions, irradiation will remain constant throughout the day, and in dynamic conditions, solar irradiation may vary which is mostly the actual scenario in everyone’s daily life. Commonly Hill climbing (HC), incremental conductance (INC), and perturb and observe (P&O) are commonly used maximum power point tracking (MPPT) technologies. These MPPT methods give an accurate output when the weather condition is static but fails during dynamic weather situations, as because in dynamic weather condition P-V curve deals with more than one number of maxima, out of these one is global maxima and the rest of them is called local maxima. MPPT needs to track the global maxima to give maximum output power to the consumer. The global maximum point (GMP) has been proposed to be tracked using particle swarm optimization (PSO). This work uses the PSO algorithm to evince the dominance of a control approach for a single-phase inverter with a grid-connected PV system in a partially shaded environment. The system consists of 4 parallel connected PV arrays when there is only partial shading, a Boost Converter, and an LCL filter, which is connected to a singlephase grid via a single-phase inverter. Here, for inner current control, the PR controller has been utilized instead of the PI controller, and the PI controller is used for outer voltage control. The primary benefit of utilizing a PR controller is that it has 0% steady-state error while tracking a sinusoidal reference current.