A simple methodology for estimating battery lifetimes in Solar Home System design

Conference Paper (2017)
Author(s)

N.S. Narayan (TU Delft - DC systems, Energy conversion & Storage)

Thekla Papakosta (External organisation)

Victor Vega Garita (TU Delft - DC systems, Energy conversion & Storage)

J Popovic-Gerber (TU Delft - DC systems, Energy conversion & Storage)

Pavol Bauer (TU Delft - DC systems, Energy conversion & Storage)

M Zeman (TU Delft - Electrical Sustainable Energy)

Research Group
DC systems, Energy conversion & Storage
DOI related publication
https://doi.org/10.1109/AFRCON.2017.8095652
More Info
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Publication Year
2017
Language
English
Related content
Research Group
DC systems, Energy conversion & Storage
Pages (from-to)
1195-1201
ISBN (electronic)
978-1-5386-2775-4

Abstract

The proliferation of Solar Home Systems (SHS) in recent times hopes to provide an alleviating solution to the global problem of energy poverty. Battery is usually the most expensive but important part of an SHS; it is also normally the first part to fail. Estimating the battery lifetime can help make informed system design choices, and it is therefore an important exercise for an SHS designer. Battery lifetime modelling is often a complex task requiring empirical data or reliance on modelling cell level electrochemical phenomena. This paper presents a simple battery lifetime estimation method specific to the application and candidate battery choices at hand. An SHS application specific simulation is carried out for a year and the effect of microcycles on the battery activity is analyzed. The concept of active Depth-of-Discharge (DOD) is introduced. Cyclic ageing of the battery is thus quantified and relative cycle lives of 2 battery technologies are compared. A delicate trade-off is demonstrated between battery sizing and lifetime. The described methodology is also compared with an empirical model and the lifetime results are found to be within 3.85%. The methodology described in this paper can potentially help SHS designers in making quick, reasonable estimations of battery lifetimes based on the intended application and battery manufacturer's data.

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