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This article offers a detailed investigation into the technical, economic along with environmental performance of four configurations of hybrid renewable energy systems (HRESs), aiming at supplying renewable electricity to a remote location, Henry Island in India. The study explores combinations involving photovoltaic (PV) panels, wind turbines, biogas generators, batteries, and converters, while evaluating their economic, technical, and environmental performance. The economic analysis yield that among all the systems examined, the PV, wind turbine, biogas generator, battery, and converter integrated configuration stands out with highly favourable results, showcasing the minimal value of levelized cost of electricity (LCOE) at $0.4224 per kWh and the lowest net present cost (NPC) at $6.41 million. However, technical analysis yield that the configuration comprising wind turbines, PV panels, converters, and battery yields a maximum excess electricity output of 2,838,968 kWh/yr. Additionally, machine learning techniques are employed to analyse economic and environmental performance data. The study shows Bilayered Neural Network model achieves exceptional accuracy in predicting LCOE, while the Medium Neural Network model proves to be the most accurate in predicting environmental performance. These findings provide valuable perception into the design and optimisation of HRES systems for off-grid applications in remote regions, taking into account their technical, economic, and environmental aspects. • Four different configurations of hybrid renewable energy systems are considered. • The configuration that integrated PV, wind turbine, biogas generator, battery, and converter is best. • Machine learning techniques are used to assess economic and environmental performances. • The bilayered neural network, with ReLU activation function, outperforms other models in predicting LCOE with R2 = 1 • The medium neural network, using ReLU activation, outperforms other models in predicting CO 2 emissions with R2 = 1. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, energy metrics (energy pay back time, electricity production factor and life cycle conversion efficiency) of hybrid photovoltaic (PV) modules have been analyzed and presented for the composite climate of New Delhi, India. For this purpose, it is necessary to calculate (1) the energy consumption in making different components of the PV modules and (2) the annual energy (electrical and thermal) available from the hybrid-PV modules. A set of mathematical relations have been reformulated for computation of the energy metrics. The manufacturing energy, material production energy, energy use and distribution energy of the system have been taken into account, to determine the embodied energy for the hybrid-PV modules. The embodied energy and annual energy outputs have been used for evaluation of the energy metrics. For hybrid PV module, it has been observed that the EPBT gets significantly reduced by taking into account the increase in annual energy availability of the thermal energy in addition to the electrical energy. The values of EPF and LCCE of hybrid PV module become higher as expected. [Copyright &y& Elsevier]