A Case Study of an Optimal Detailed Analysis of a Standalone Photovoltaic/Battery System for Electricity Supply in Rural and Remote Areas

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Abstract

This paper focused on a techno-economic study of a standalone PV/battery system for electrical energy supply. For a particular case study in Cameroon, the system is optimally designed thanks to a double-objective firefly optimization algorithm, based on a defined operational strategy. The two objective functions simulated simultaneously using FA are: the cost of energy (COE) function and the function defining the loss of power supply probability (LPSP). Different optimal configurations of the system have been obtained on the Pareto front with respect to their LPSP. For a total load demand of 20196.7 kWh, the lowest cost configuration with LPSP of 0% is composed by a number of 63 modules and a battery capacity of 370.295 kWh. The related COE is 0.2587 $/kWh, corresponding to a total net present cost of 87422 $. However with this configuration, the energy of batteries could not be able solely to respond to the energy demand for 3 continuous days. In that case, the increase of the PV power production (by increasing the number of PV modules) could allow to the batteries to fulfil this deficiency. But this solution increases the investment cost to up to 11.17%, considering a system with 80 PV modules. Another solution consists in reducing the size of the battery bank to avoid its unnecessary oversizing. In this case, the COE and the system investment cost reduce to up to 28.77% for 1 day batteries' autonomy considered. The obtained results have demonstrated that the cost of a PV/battery system is mostly influenced by the batteries' size, while the system reliability is mostly related to the PV size.

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Zieba Falama, R., Yaouba, Menga, F. D., Hamda Soulouknga, M., Kwefeu Mbakop, F., & Ben Salah, C. (2022). A Case Study of an Optimal Detailed Analysis of a Standalone Photovoltaic/Battery System for Electricity Supply in Rural and Remote Areas. International Transactions on Electrical Energy Systems, 2022. https://doi.org/10.1155/2022/7132589

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