Abstract
The quest for a green renewable energy source in replacement of conventional energy such as fossil fuel, diesel generator, or electric grid has taken important aspects in industrial sectors to alleviate their economy and comply with global warming reduction. In the information and telecommunication (IT) sector, base stations generate more than 90% of energy used in a network. Green energy from photovoltaic (PV) systems can be used to tackle base station energy consumption, however, non-exhaustive analyses are required to meet the demand while kee** the cost of energy production at minimum. Therefore, how can PV systems alleviate the cost of conventional energy usage while meeting the load demand for LTE base station’s equipment. This paper presents a sizing and optimization solution for a stand-alone PV (SAPV) system. A stochastic method based on an iterative numerical algorithm is used to define the size of the PV, meanwhile, the optimum size is chosen from the lowest loss of energy supply probability (LLP) percentage and the least cost of energy (LCE). The outputs demonstrate from an LLP of 1%, the LCE is 0,305 $/kWh using 13 PV panels and 408750 Wh of battery capacity over a duration of 25 years.
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Ondo-Ekogha, E., Owolawi, P.A. (2023). SAPV Sizing Optimization: A Numerical Iterative Method Using LTE Base Station Profile in SA. In: Pandit, M., Gaur, M.K., Kumar, S. (eds) Artificial Intelligence and Sustainable Computing. ICSISCET 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-1431-9_55
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DOI: https://doi.org/10.1007/978-981-99-1431-9_55
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