In this article, an experimental study of the single-pass hybrid (PV/T) collector is conducted in the climatic conditions of Fallujah city, where the experimental results are compared with a previous research to validate the results. The effect of changing the angle of inclination of the hybrid collector (PV/T) and its effect on the electrical power in the range (20°-50°) is studied. The optimum angle of the collector is found to be 30°, which gives a maximum electrical power of 58.8 W at average solar radiation of 734.35 W/m2. In another experimental study with different air flow rates ranged from 0.04 kg/s to 0163 kg/s, where it is found that the maximum electrical power of 57.66 W at an air flow rate of 0.135 kg/s, while the maximum thermal efficiency reaches 33.53% at an air flow of 0.163 kg/s at average solar radiation of 786 W/m2.
In this article, an experimental study of the single-pass hybrid (PV/T) collector is conducted in the climatic conditions of Fallujah city, where the experimental results are compared with a previous research to validate the results. The effect of changing the angle of inclination of the hybrid collector (PV/T) and its effect on the electrical power in the range (20°-50°) is studied. The optimum angle of the collector is found to be 30°, which gives a maximum electrical power of 58.8 W at average solar radiation of 734.35 W/m2. In another experimental study with different air flow rates ranged from 0.04 kg/s to 0163 kg/s, where it is found that the maximum electrical power of 57.66 W at an air flow rate of 0.135 kg/s, while the maximum thermal efficiency reaches 33.53% at an air flow of 0.163 kg/s at average solar radiation of 786 W/m2.
These systems show great promise by converting waste heat from photovoltaic modules into additional electrical power. The study analyzes the performance and efficiency of the hybrid PV-TEG systems under varying conditions, such as different solar concentration ratios, cooling methods, and materials. While these innovations promise to improve system efficiency, the review also identifies several challenges, including increased thermal resistance, higher system costs, and the minimal temperature difference across the TEG, which significantly limits its performance. This limitation, where the temperature differential is often too small to be effectively harnessed, reduces the TEG's overall efficiency and hinders the integrated system's potential gains. The review underscores the need for urgent and extensive research to develop optimized design configurations, durable mathematical models, and further experimental validation to ensure the practical viability of these systems under diverse environmental conditions. Despite these challenges, the potential of PV-TEG systems to revolutionize solar energy technologies is undeniable.PV-TEG performance is intricately linked to environmental conditions: higher solar radiation boosts efficiency, but increased ambient temperatures reduce it. TEGs often hinder PV cooling, yielding minimal efficiency gains. Non-uniform heat and low-temperature differences across TEGs further decrease performance. While hybrids can improve power conversion, high costs limit feasibility. However, with strategies such as enhancing solar concentration, using effective cooling methods like water or nanofluids, and advanced materials like phase change materials, the efficiency and reliability of these systems can be significantly improved
Internet-based platforms such as social media have a great deal of big data that is available in the shape of text, audio, video, and image. Sentiment Analysis (SA) of this big data has become a field of computational studies. Therefore, SA is necessary in texts in the form of messages or posts to determine whether a sentiment is negative or positive. SA is also crucial for the development of opinion mining systems. SA combines techniques of Natural Language Processing (NLP) with data mining approaches for developing inelegant systems. Therefore, an approach that can classify sentiments into two classes, namely, positive sentiment and negative sentiment is proposed. A Multilayer Perceptron (MLP) classifier has been used in this document classification system. The present research aims to provide an effective approach to improving the accuracy of SA systems. The proposed approach is applied to and tested on two datasets, namely, a Twitter dataset and a movie review dataset; the accuracies achieved reach 85% and 99% respectively.