Abstract

Solar cells formed by the combination of organic and inorganic nanoparticle semiconductors are gaining interest in today’s era because of their major features, such as being suitable for scalable solar power conversion and being of low cost to produce desirable photovoltaic devices. This work is an attempt to develop two forms of hybrid solar cells, one by the amalgamation of zinc oxide and carbon quantum dots and second, by incorporating graphene oxide into zinc oxide. In this study, optimization, validation, and comparison of the photovoltaic parameters of the two nanostructured solar cells were attempted using the Artificial Neural Network technique. The ANN was instructed using the Firefly Algorithm. The input parameters are the spectral power density and temperature. The output parameters are the short circuit current (ISC), open-circuit voltage (VOC), fill factor of the cell (FF), and maximum voltage point prediction (VMPP). The results obtained for both the hybrid solar cells were compared and it was noted that the addition of CQDs to ZnO resulted in a considerable increase in the values of ISC, VOC and FF. The output obtained by the ANN trained model was compared with the results obtained from the experimental tests. It is observed that there is considerable agreement between the results obtained from the ANN and experimental values. The optimized values of VOC, ISC, FF, VMPP, Incident Photon to Current Efficiency (IPCE), Power Conversion Efficiency (PCE) for ZnO/GO are 0.623 V, 0.546 mA, 62%, 0.509 V, 36.95%, 9.12% respectively. Similarly values of VOC, ISC, FF, VMPP, IPCE, PCE for ZnO/CQDs are 0.636 V, 0.597 mA, 68%, 0.531 V, 40.72%, 10.35% respectively. Therefore, the precise values of all the stated parameters were obtained for both the cells after optimization and hybrid cells made of CQDs proves to be a better candidate. Also, the desirable value of the coefficient of correlation (R) is obtained, approximately close to 1, which means that the fabricated samples are efficient for useful applications. Proper execution of this algorithm on any model of the hybrid solar cell can lead to an evolution in the field of solar cells, resulting in the improvement of efficiency. These optimized cells have been utilized to propose two models of solar trigeneration system used in a commercial building North Service Centre (Olefin building) of Haldia Petrochemicals Limited, Haldia, West Bengal, India. The trigeneration systems were based on photovoltaic modules, heat pump and photovoltaic-thermal collectors. The objective is to provide enough electricity, domestic hot water, heating and cooling power to meet the typical demand of a single office building. System performance has been predicted and evaluated in the work. Considerations should be made regarding the physical constraints imposed by the environment where the installation has to be performed. The location should be carefully selected to achieve maximum efficiency.

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