In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers.
Solar charge controllers will play a crucial role in the prediction that solar power could account for up to 25% of global electricity production by 2050. Furthermore, they aid in the reduction of expenses. Although solar power systems may require a considerable initial investment, they offer substantial long-term savings.
As a result, it ensures that SPV modules respond quickly and work at their best regardless of the weather. A controller with improved accuracy, robustness, and efficiency is produced by this special fusion of neural networks and fuzzy logic, making it an appealing option for managing solar photovoltaic systems.
Battery damage resulting from unregulated power fluctuations becomes substantially more probable in the absence of these devices. An upsurge in the need for solar charge controllers has resulted from the increasing recognition of the advantages associated with solar energy and the ongoing progress in technology.
The comprehensive analysis of conventional and artificial intelligence-based controllers provides valuable insights into the nuanced trade-offs between performance and cost across various MPPT algorithms, aiding in informed decision-making for solar power systems. Further analysis of all controllers is given in Table 2.
The integration of AI-based controllers contributes to improved performance, adaptability, and robustness, positioning them as pivotal tools in the quest for enhanced solar energy harvesting.
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Design and implementation of a new adaptive MPPT controller for solar PV systems. December 2023; Energy Reports 9(16):1818-1829 ... The proposed controller''s average tracking efficiency is 99.77 ...
Online Services Email ContactUtilization of a solar charge controller (SCC) with pulse width modulation (PWM) and maximum power point tracking (MPPT) functionality is imperative to enhance the effectiveness and …
Online Services Email ContactAs a result, AI-based approaches for MPPT, including Artificial Neural Network (ANN) and Fuzzy Logic Controller (FLC), have surfaced as potent controllers in PV systems. …
Online Services Email ContactExploring solar energy systems: A comparative study of optimization algorithms, MPPTs, and controllers. Aykut Fatih Güven, Corresponding Author. ... Moreover, potential changes in the loads were considered by varying the load. The efficacy of the controllers was examined by altering both the environment and load. The effectiveness of the ...
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Online Services Email ContactThe configuration of a fuzzy cell: (a) configuration with a fuzzy sensor, a fuzzy actuator or an inference component; (b) implementations of a fuzzy sensor in cell 1 and a fuzzy controller in cell 2.
Online Services Email ContactThis comparative analysis aimed to evaluate the efficacy of two solar photovoltaic control methods—SAPV direct coupling and Maximum Power Point Tracking control—in optimizing energy harvesting...
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Online Services Email ContactThis study elucidates the use of optimization algorithms to identify the controller parameters employed in adjusting the current and voltage values of loads powered by …
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Online Services Email ContactThe efficiency of the conventional controller (PI) and FLC are compared, with FLCs being better at handling nonlinearities in the system due to changes in solar radiation, …
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Online Services Email ContactThis study delves into the efficacy of a fuzzy logic controller compared to conventional controllers designed for tracking the maximum power point.
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Online Services Email Contact2.2 Maximum power point tracking. Figures 4-6 present the flow diagrams for the P&Q, IC, and OCV techniques, respectively. In the P&Q technique, it is necessary to adjust …
Online Services Email ContactSolar charge controllers (SCC) are vital components in PV systems designed to improve the operational efficiency of solar panels by controlling voltage and current fluctuations. ... The efficacy of an AI-driven MPPT algorithm and optimizes the power output of the PV system is reported in [165, 166]. 7.3 Prospects for advanced SSC technologies ...
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