Abstract
The output power of a photovoltaic (PV) system depends on the external solar irradiation and its own temperature. In order to obtain more power from the PV system, the maximum power point tracking (MPPT) is necessary. However, when the PV is partially shaded, there will be multiple peaks in the power-current (P-I) curve. The conventional MPPT methods may be invalid due to falling into the local peak. In addition, in a photovoltaic-thermal (PV/T) system, the non-uniform temperature distribution on PV will also occur, which complicates the situation. This paper presents a MPPT method with glowworm swarm optimization (GSO) for PV in a PV/T system under non-uniform solar irradiation and temperature distribution. In order to study the performance of the proposed method, the conventional methods including the perturbation and observe algorithm (P and O), and the fractional open-circuit voltage technique (FOCVT) are compared with it in this paper. Simulation results show that the proposed method can rapidly track the real maximum power point (MPP) under different conditions, such as the gradient temperature distribution, the fast variable solar irradiation and the variable partial shading. The outcome indicates the proposed method has obvious advantages, especially the performance being superior to the conventional methods under the partial shading condition.
Highlights
With the sharp increasing global demand for energy, the shortage of the conventional fossil fuels and environmental pollution are becoming more and more serious
The results indicate that the novel algorithm glowworm swarm optimization (GSO) is suitable for PV/T maximum power point tracking (MPPT) applications under non-uniform solar irradiation and temperature distribution
A novel MPPT method based on the GSO algorithm is proposed and its
Summary
With the sharp increasing global demand for energy, the shortage of the conventional fossil fuels and environmental pollution are becoming more and more serious. There will be multiple peaks in the P-I characteristic curve under the partial shading condition in actual applications These conventional methods reach the local MPP, but cannot analyze and compare all peaks to determine the true MPP [11]. Kofinas proposed an intelligent MPPT control scheme based on a direct neural control (DNC), which consists of a single adaptive neuron and a hybrid learning mechanism [17] These methods usually need an enormous volume of data for training, professional experience, or a complex leaning process. Considering the characteristic of multiple peaks in a P-I curve caused by the non-uniform solar irradiation conditions, GSO may be very suitable for MPPT. The results indicate that the novel algorithm GSO is suitable for PV/T MPPT applications under non-uniform solar irradiation and temperature distribution
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