Abstract
The characteristics of photovoltaic (PV) are directly affected by partial shading (PS) conditions due to the non-uniform irradiance. The PV system can be compromised based on the shading pattern as well as the shading area. Thus, the need for a solution that can deal with non-uniform irradiance has increased significantly. Consequently, this paper proposes a thorough analysis of the impact of PS patterns on different PV array configurations such as SP, TCT, and BL. The five optimization algorithms PSO, DA, MLS-SPA, IGWO, and BWO, were used to tune the variable step of the conventional P&O technique to extract the maximum power point. The proposed PV array is 4×4 with a fixed location, yet changing electrical connections. The main objective and novelty of this paper is to locate the Global Maximum Power Point (GMPP) of a PV array while the occurrence of different PSC with fast change of hybrid load e.g., (resistive and pump load). The results showed the superior performance of the IGWO algorithm regarding the maximum power tracking and disturbance rejection.
Highlights
During the past decade, renewable energy has been grown rapidly around the globe as an essential resource for electricity
This section will represent the comparative analysis for the maximum powers generated under the Partial Shading (PS) cases with dynamical load variation
The study consists of two main objectives, analysis of the solar array reconfiguration performance to get G Maximum Power Point (MPP) Maximum Power Point Tracking (MPPT) performance and tracking efficiency
Summary
Renewable energy has been grown rapidly around the globe as an essential resource for electricity. Recognizing the stated limitations for the conventional algorithms, many researchers tried to apply artificial intelligence methods such as ANN for MPPT application, the results showed ANN requires a huge data set for training which in return consumes a relatively huge memory space This disadvantage increases the complexity and total cost for such systems [18]. The authors used a Marine Predator Algorithm (MPA) along with a novel objective function instead of the conventional weighted objective functions Different optimization algorithms such as PSO were used as reconfiguration techniques. The selected optimization algorithms have proven to have superior behavior in the field of optimization based on their computational ability and fast convergence [24] Methods such as PSO and GWO have been proven to have a robust and adaptive behavior in Electrical Array Reconfiguration (EAR) to perform shade dispersion [25].
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