This article presents a detailed analysis of parameters that affect the optical performance of parabolic trough solar collector (PTSC) and proposes a suitable method to optimize the relevant ones. A mathematical model...
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This article presents a detailed analysis of parameters that affect the optical performance of parabolic trough solar collector (PTSC) and proposes a suitable method to optimize the relevant ones. A mathematical model is drafted and simulated for known geometry and parameters of industrial solar technology (IST) PTSC. The model was evaluated for three different configurations of IST PTSC involving distinct components. A comparison between the experimental results and model estimations indicates a maximum root-mean-square error (RMSE) of 0.7997, confirming the reliability of the proposed model. The influence of variations in absorber diameter (D-ao), length (l(rc)), width (w(rc)), and focal length of PTSC (f(rc)), along with direct normal incidence (I-n), dirt factors (xi(dm),xi(dhc)), and angle of incidence (theta) on the optical performance of PTSC has been investigated. It was established that variation in mentioned parameters exhibits both positive and negative impacts on optical performance. After careful analysis, l(rc), w(rc), f(rc), D-ao, and theta were chosen for optimization as it was perceived that by varying these in a reasonable range, an optimal set of parameters could be obtained that maximize the absorbed solar irradiation for a given PTSC. Genetic algorithm (GA), particle swarm optimization (PSO), and african vultures optimization algorithm (AVOA) are utilized to estimate the optimal values of parameters. Significant improvement in absorbed solar irradiation (similar to 16%) is registered with optimized parameters, suggesting that benefits can be obtained if a study is performed prior to producing PTSC modules for an application.
Addressing the pressing need for sustainable energy solutions, this paper proposes a novel hybrid energy system integrating wind, alkaline fuel cells and solar energies. This paper introduces a pioneering hybrid energ...
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Addressing the pressing need for sustainable energy solutions, this paper proposes a novel hybrid energy system integrating wind, alkaline fuel cells and solar energies. This paper introduces a pioneering hybrid energy system designed to produce electricity and hydrogen fuel through the integration of wind, solar energies, and an alkaline fuel cell. The proposed approach, coined as IWGAN-AVOA technique, synergizes the improved Wasserstein generative adversarial network (IWGAN) and the african vultures optimization algorithm (AVOA). The primary aim is to delineate a distinctive energy cycle reliant on renewable sources, featuring a Stirling engine, electrolyzer, alkaline fuel cell, wind turbine, and solar photovoltaic system, with the objective of generating hydrogen fuel and energy. The AVOA enhances fuel cell capabilities, simulates optimal system component sizes, and rectifies erroneous configurations based on geographical specifics. By validating the efficacy of IWGAN, the study achieves optimal configurations for device capacities and enhances power flow efficiency. Comparative analyses reveals that the IWGAN-AVOA approach surpasses existing techniques, like particle swarm optimization (PSO), wild horse optimizer (WHO), and heap based optimizer (HBO), with a remarkable efficiency rate of 98%, outperforming current methods. The last figure illustrates the effectiveness comparison, showcasing efficiencies of 62%, 79%, and 85% for HBO, PSO, and WHO, respectively, against the superior 98% efficiency achieved by the IWGAN-AVOA approach, affirming its superiority in energy system optimization.
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