Author:
C. I. Nnabude,,U. C. Ikediuwa,,G. A. Osuji,,I. M. Ndibe,
Abstract
Lifetime batteries are essential component of energy storage systems. These batteries are designed to store electrical energy and provide power during periods of power outages. Energy storage systems are broader solutions for storing electrical energy which often include inverter batteries (Lithium ion) as a component. Energy storage systems are becoming increasingly important for integrating renewable energy sources like solar ensuring stability and reliability. To maximize battery performance and extend lifespan, precise assessment of the batteries' state of charge, battery impedance, and remaining capacity is necessary. In this paper, Gamma Distribution (G (α, β)) and Weibull Distribution (W (α, β)) were used to model the lifetime batteries and energy storage systems in other to determine the maximum lifetime of an inverter batteries and secondly to compare the results obtained from the two distributions. The two probability distributions (The Gamma and The Weibull) were employed in the analysis of our simulated data because of their flexibility in modeling data longevity. From the results obtained, it was observed that the average lifespan of inverter batteries is seven years (7 years). Weibull distribution demonstrated superior fit when compared with Gamma distribution in handling the modeling of lifetime inverter batteries.
Publisher
African - British Journals
Reference9 articles.
1. Abdul, G. O, Onumaegbu, C., Tabbi, W, Mohamad, R., Mohammad, A.A, Abdul, H. A (2021) “Critical Review of Energy Storage Saystems” Energy (Pergamon) vol 214, pp 118987.
2. Jiajun, Chen (2013) “Recent Progress in Advanced Materials Lithiumion Batteries” Materials 2013, 6(1), 156-183; https://doi.org/10.3390/ma6010156
3. Kafetzis, A., Panopoulos, K.D., Papadopoulou, S., Seferlis, P., Voutetakis, S. (2020) “Energy Management Strategies based on Hybrid Automata for Islanded Microgrids with Renewable Sources, Batteries and Hydrogen” Renewable and Sustainable Energy Reviews. Volume 134, https://doi.org/10.1016/j.rser.2020110118.
4. Nawal, A.M.I., Syafrina, A.H., Norhaslinda, A. (2022). “Estimating Weibull Parameters Using Maximum Likelihood Estimation and Oridinary Least Squares: Simulation Study and Application on Meteorological Data” Mathematics and Statistics 10(2), 269 – 292. Doi:10.13189/ms.2022.100201.
5. Nwankwo, C. K (2017) “Comparing Methods of Estimating the Parameters of the Gamma Distribution in Modelling Rainfall Variability in Nigeria”. Unpublished manuscript.