A New Modified GWO Algorithm in PV MPPT Applications

Renewable energy resources have gained more attention in the last decades. In the category of renewable energy resources, solar energy is used more around the world as it is available almost in every region and it has no moving parts. Thus, its reliability is high. Solar irradiance can be transformed into electricity by photovoltaic (PV) technology. Solar cells are used to fulfill this purpose. The output voltage/current/power of a singular PV cell is inadequate for domestic and industrial consumptions. Hence, PV cells are connected in series and parallel to increase the output power. It is essential to get the most possible output power of the PV array(s). The goal is to detect the Maximum Power Point (MPP) in the P-V curve of the PV array(s). This process is known as Maximum Power Point Tracking (MPPT). The function of a PV cell is highly dependent on irradiance and temperature. In uniform irradiance, there is only a single MPP, however, there are some Local Maximum Power Points (LMPP) in partial shading condition and just a single Global Maximum Power Point (GMPP). It is easier to discover MPP in uniform irradiance, although detecting the GMPP between LMPPs is not a simple process. MPPT must be rapid and accurate. This paper proposes a modified Grey Wolf Optimizer (GWO) algorithm in MPPT applications.

کلیدواژه های A New Modified GWO Algorithm in PV MPPT Applications:

MPPT ، Metaheuristic ، GWO ، Partial Shading