An effective hybrid approach based control for the MPPT of PV system under partial shading condition for indoor energy harvesting in smart homes

被引:0
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作者
Nilesh Mendhe
Abhay Vidyarthi
机构
[1] VIT University,Department of Electrical and Electronics Engineering
来源
关键词
PV system; Partial shading; MPPT; P&o; Aquila optimization; Bird swarm algorithm; Hybrid algorithm; Bird swarm fostered Aquila optimization;
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摘要
Renewable radiation is a natural, natural resource that is simultaneously permanent and unrenewable. The two key elements that influence the performance of a PV system are irradiation and temperature. Partial shade, on the other hand, causes a nonlinear maximum power point tracking (MPPT) issue in PV systems. The PV array’s P-V characteristics have more than one MPP when exposed to non-uniform solar irradiation. This situation makes tracking MPP more difficult and reduces the PV system’s efficiency. This article proposes a hybrid optimization of Aquila optimization (AO) and Bird Swarm Algorithm (BSA) assisted MPPT controller to monitor peak energy in various weather conditions for the MPPT of PV System under partial shading condition for Indoor energy harvesting in smart homes. Finally, the proposed Bird Swarm Fostered Aquila Optimization (BSFAO) assisted MPPT control is compared to that of the standard methods like perturb and observe (P&O), Harris Hawks Optimization (HHO), Bird Swarm Algorithm (BSA), Aquila Optimization (AO). The proposed BSFAO method displays higher MPPT performance and a rapid convergence at the global maxima. Thus, the suggested hybrid (BSFAO) formed MPPT approach provides faster MPPT. The results proved that the suggested BSFAO model has achieved enhanced power tracking efficiency of 99.61% for every shading design when compared to the existing methodology and attained a reduced computational burden (3717.63) approximately, for all shading conditions respectively.
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页码:46717 / 46740
页数:23
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