Abstract
A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exploration and exploitation phases is one of its main advantages. Therefore, the SFS algorithm has been selected to extract the global maximum power point (MPP) under partial shading conditions. To prove the superiority of the proposed global MPPT–SFS based tracker, several shading scenarios have been considered. The idea of changing the shading scenario is to change the position of the global MPP. The obtained results are compared with common optimizers: Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), Firefly-Algorithm (FA), Invasive-Weed-Optimization (IWO), JAYA and Gravitational Search Algorithm (GSA). The results of comparison confirmed the effectiveness and robustness of the proposed global MPPT–SFS based tracker over ALO, CS, FPA, FA, IWO, JAYA, and GSA.
Highlights
Due to the environmental impact of fossil fuels that currently act as our main energy source [1], there is a rapid growth in the usage of renewable energy as an alternative energy source [2,3,4]
To illustrate illustrate the the supremacy supremacyof of the the proposed technique, the obtained results are compared with those obtained via Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), FA, IWO, proposed technique, the obtained results are compared with those obtained via ALO, CS, FPA, FA, JAYAJAYA
The maximum value of 99.88% is achieved by stochastic fractal search (SFS), followed by FPA and JAYA, whereas the minimum value of 94.8% is assigned to ALO
Summary
Due to the environmental impact of fossil fuels that currently act as our main energy source [1], there is a rapid growth in the usage of renewable energy as an alternative energy source [2,3,4]. MJSCs used in concentrated PV systems are different from silicon type cells, they are capable of capturing and converting large amounts of sunlight into electrical energy with high efficiency [13]. The voltage versus power curve contains a unique maximum power point (MPP) This point can be extracted using different conventional tracking methods like perturb and observe (P&O), hill-climbing, and incremental conductance (INC). The partial shading generates multiple peaks in the curve of output power and has negative effects on the conventional MPPT methods’ efficiency [21]. Several shading scenarios were considered to prove the reliability of the presented global MPPT. A novel algorithm called Stochastic Fractal Search (SFS) is proposed to extract the global power of a partially shaded PV system employing a triple-junction solar cell.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
