Comparison of Lead-Acid and Li-Ion Batteries Lifetime Prediction Models in Stand-Alone Photovoltaic Systems
Source abstract
Abstract
Several models for estimating the lifetimes of lead-acid and Li-ion (LiFePO4) batteries are analyzed and applied to a photovoltaic (PV)-battery standalone system. This kind of system usually includes a battery bank sized for 2.5 autonomy days or more. The results obtained by each model in different locations with very different average temperatures are compared. Two different locations have been considered: the Pyrenees mountains in Spain and Tindouf in Argelia. Classical battery aging models (equivalent full cycles model and rainflow cycle count model) generally used by researchers and software tools are not adequate as they overestimate the battery life in all cases. For OPzS lead-acid batteries, an advanced weighted Ah-throughput model is necessary to correctly estimate its lifetime, obtaining a battery life of roughly 12 years for the Pyrenees and around 5 years for the case Tindouf. For Li-ion batteries, both the cycle and calendar aging must be considered, obtaining more than 20 years of battery life estimation for the Pyrenees and 13 years for Tindouf. In the cases studied, the lifetime of LiFePO4 batteries is around two times the OPzS lifetime. As nowadays the cost of LiFePO4 batteries is around two times the OPzS ones, Li-ion batteries can be competitive with OPzS batteries in PV-battery standalone systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Advanced Battery Materials and Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento de Ingeniería Eléctrica, Universidad de Zaragoza, C/María de Luna, 3, 50018 Zaragoza, Spain
Escuela Universitaria Politécnica de La Almunia, EUPLA, Universidad de Zaragoza, C/Mayor, s/n, La Almunia, 50100 Zaragoza, Spain
Funding
Universidad de Zaragoza
References (52)
Show source-provided references
1. Overview of the off-grid photovoltaic diesel batteries systems with AC loads10.1016/j.apenergy.2015.07.073 ↗
2. Coupling small batteries and PV generation: A review10.1016/j.rser.2020.109835 ↗
3. A comparison of lead-acid and lithium-based battery behavior and capacity fade in off-grid renewable charging applications10.1016/j.energy.2013.08.029 ↗
4. The potential of Li-ion batteries in ECOWAS solar home systems10.1016/j.est.2019.02.021 ↗
5. García-Vera, Y.E., Dufo-López, R., and Bernal-Agustín, J.L. (2020). Optimization of isolated hybrid microgrids with renewable energy based on different battery models and technologies. Energies, 13.10.3390/en13030581 ↗
6. Operating conditions of batteries in off-grid renewable energy systems10.1016/j.solener.2006.12.009 ↗
7. Operating conditions of lead-acid batteries in the optimization of hybrid energy systems and microgrids10.1016/j.apenergy.2016.07.018 ↗
8. Life prediction of batteries for selecting the technically most suitable and cost effective battery10.1016/j.jpowsour.2004.11.045 ↗
9. Simulation based size optimization of a PV/wind hybrid energy conversion system with battery storage under various load and auxiliary energy conditions10.1016/j.apenergy.2008.12.015 ↗
10. Economic and environmental impact of lead-acid batteries in grid-connected domestic PV systems10.1016/j.apenergy.2012.11.016 ↗
11. Optimal sizing for UPS systems based on batteries and/or fuel cell10.1016/j.apenergy.2012.12.058 ↗
12. Huld, T., Moner-Girona, M., and Kriston, A. (2017). Geospatial analysis of photovoltaic mini-grid system performance. Energies, 10.10.3390/en10020218 ↗
13. Dolara, A., Grimaccia, F., Magistrati, G., and Marchegiani, G. (2017). Optimization Models for islanded micro-grids: A comparative analysis between linear programming and mixed integer programming. Energies, 10.10.3390/en10020241 ↗
14. Techno-economic analysis of a grid-connected PV/battery system using the teaching-learning-based optimization algorithm10.1016/j.solener.2020.04.007 ↗
15. Degrees of displacement: The impact of household PV battery prosumage on utility generation and storage10.1016/j.apenergy.2020.115466 ↗
16. Optimization of residential off-grid PV-battery systems10.1016/j.solener.2020.08.023 ↗
17. Micro-economic assessment of residential PV and battery systems: The underrated role of financial and fiscal aspects10.1016/j.apenergy.2020.115667 ↗
18. Component degradation in small-scale off-grid PV-battery systems operation in terms of reliability, environmental impact and economic performance
19. Power to the people: Evolutionary market pressures from residential PV battery investments in Australia10.1016/j.enpol.2019.110977 ↗
20. Customer economics of residential PV–battery systems in Thailand. Renew
21. Design and control strategies of PV-diesel systems using genetic algorithms10.1016/j.solener.2004.10.004 ↗
22. Design of isolated hybrid systems minimizing costs and pollutant emissions10.1016/j.renene.2012.01.011 ↗
23. Feasibility analysis of stand-alone renewable energy supply options for a large hotel. Renew
24. Feasibility study for a standalone solar–wind-based hybrid energy system for application in Ethiopia10.1016/j.apenergy.2009.06.006 ↗
25. Optimum battery depht of discharge for off-grid solar PV/battery system10.1016/j.est.2019.100999 ↗
26. Influence of mathematical models in design of PV-Diesel systems10.1016/j.enconman.2007.06.027 ↗
27. Multi-objective design and control of hybrid systems minimizing costs and unmet load10.1016/j.epsr.2008.05.011 ↗
28. Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV-wind-diesel systems with batteries storage10.1016/j.apenergy.2011.04.019 ↗
29. A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems10.1016/j.apenergy.2013.02.049 ↗
30. Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems10.1016/j.jpowsour.2006.11.092 ↗
31. Dufo-López, R. (2021, January 10). iHOGA (improved Hybrid Optimization by Genetic Algorithms) Software. Available online: https://ihoga.unizar.es/en.
32. Comparison of off-grid power supply systems using lead-acid and lithium-ion batteries10.1016/j.solener.2017.12.049 ↗
33. Comparison of different lead–acid battery lifetime prediction models for use in simulation of stand-alone photovoltaic systems10.1016/j.apenergy.2013.11.021 ↗
34. Armand, M., Axmann, P., Bresser, D., Copley, M., Edström, K., Ekberg, C., Guyomard, D., Lestriez, B., Novák, P., and Petranikova, M. (2020). Lithium-ion batteries—Current state of the art and anticipated developments. J. Power Sources, 479.10.1016/j.jpowsour.2020.228708 ↗
35. Zubi, G., Dufo-López, R., Carvalho, M., and Pasaoglu, G. (2018). The lithium-ion battery: State of the art and future perspectives. Renew. Sustain. Energy Rev., 89.10.1016/j.rser.2018.03.002 ↗
36. Energy storage for electricity generation and related processes: Technologies appraisal and grid scale applications10.1016/j.rser.2018.06.044 ↗
37. Astaneh, M., Roshandel, R., Dufo-López, R., and Bernal-Agustín, J.L. (2018). A novel framework for optimization of size and control strategy of lithium-ion battery based off-grid renewable energy systems. Energy Convers. Manag.10.1016/j.enconman.2018.08.107 ↗
38. Deterministic models of Li-ion battery aging: It is a matter of scale10.1016/j.est.2018.09.002 ↗
39. Astaneh, M., Dufo-López, R., Roshandel, R., and Bernal-Agustin, J.L. (2018). A novel lifetime prediction method for lithium-ion batteries in the case of stand-alone renewable energy systems. Int. J. Electr. Power Energy Syst., 103.10.1016/j.ijepes.2018.05.034 ↗
40. Empirical Li-ion aging model derived from single particle model10.1016/j.est.2019.01.005 ↗
41. Cortés-Arcos, T., Dufo-López, R., and Bernal-Agustín, J.L. (2020). Estimating degradation costs for non-cyclic usage of lithium-ion batteries. Appl. Sci., 10.10.3390/app10155330 ↗
42. Oyarbide, M., Arrinda, M., Sánchez, D., Macicior, H., McGahan, P., Hoedemaekers, E., and Cendoya, I. (2020). Capacity and impedance estimation by analysing and modeling in real time incremental capacity curves. Energies, 13.10.3390/en13184855 ↗
43. Cycle-life model for graphite-LiFePO4 cells10.1016/j.jpowsour.2010.11.134 ↗
44. Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime10.1016/j.apenergy.2016.03.119 ↗
45. Arnieri, E., Boccia, L., Amoroso, F., Amendola, G., and Cappuccino, G. (2019). Improved efficiency management strategy for battery-based energy storage systems. Electronics, 8.10.3390/electronics8121459 ↗
46. International Electrotechnical Commission (1987). IEC 60896-1:1987 Stationary Lead-Acid Batteries. General Requirements and Methods of Test. Vented Types, International Electrotechnical Commission.
47. Simple Rainflow Counting Algorithms10.1016/0142-1123(82)90018-4 ↗
48. (2021, January 17). Commercial OPzS Battery. Available online: http://inversolar.es/wp-content/uploads/2019/12/EN-PS-TS-RS-005_0814.pdf.
49. Design of primary and secondary cells II. An equation describing battery discharge10.1149/1.2423659 ↗
50. On the complex ageing characteristics of high-power LiFePO4/graphite battery cells cycled with high charge and discharge currents10.1016/j.jpowsour.2015.04.001 ↗
51. Analysis and modeling of calendar aging of a commercial LiFePO4/graphite cell10.1016/j.est.2018.01.019 ↗
52. (2020, September 13). European Commission, PVGIS. Available online: https://ec.europa.eu/jrc/en/pvgis.