Abstract
The rapid increase in the adoption of Solar Home Systems (SHS) in recent times hopes to ameliorate the global problem of energy poverty. The battery is a vital but usually the most expensive part of an SHS; owing to the least lifetime among other SHS components, it is also the first to fail. Estimating battery lifetime is a critical task for SHS design. However, it is also a complex task due to the reliance on experimental data or modelling cell level electrochemical phenomena for specific battery technologies and application use-case. Another challenge is that the existing electrochemical models are not application-specific to Solar Home Systems. This paper presents a practical, non-empirical battery lifetime estimation methodology specific to the application and the available candidate battery choices. An application-specific SHS simulation is carried out, and the battery activity is analyzed. A practical dynamic battery lifetime estimation method is introduced, which captures the fading capacity of the battery dynamically through every micro-cycle. This method was compared with an overall non-empirical battery lifetime estimation method, and the dynamic lifetime estimation method was found to be more conservative but practical. Cyclic ageing of the battery was thus quantified and the relative lifetimes of 4 battery technologies are compared, viz. Lead-acid gel, Flooded lead-acid, Nickel-Cadmium (NiCd), and Lithium Iron Phosphate (LiFePO4) battery. For the same SHS use-case, State-of-Health (SOH) estimations from an empirical model for LiFePO4 is compared with those obtained from the described methodology, and the results are found to be within 2.8%. The relevance of this work in an SHS application is demonstrated through a delicate balance between battery sizing and lifetime. Based on the intended application and battery manufacturer’s data, the practical methodology described in this paper can potentially help SHS designers in estimating battery lifetimes and therefore making optimal SHS design choices.
Highlights
An estimated 1.2 billion people around the world lacked access to electricity as of 2016, with almost 85% of this population living in the rural areas
This paper presents a practical, non-empirical battery lifetime estimation methodology specific to the application and the available candidate battery choices
A Solar Home System is defined as a Photovoltaic (PV)-based generator usually rated between 50 Wp and 250 Wp, accompanied by a
Summary
An estimated 1.2 billion people around the world lacked access to electricity as of 2016, with almost 85% of this population living in the rural areas. Most of these unelectrified regions and communities have not received grid-based electricity [1]. In the absence of a central grid as an imminent solution [2], Solar Home Systems (SHS) seem to be a promising route to address immediate electricity needs in the off-grid areas [3]. A Solar Home System is defined as a Photovoltaic (PV)-based generator usually rated between 50 Wp and 250 Wp, accompanied by a Applied Energy 228 (2018) 1629–1639 Nomenclature Variables. DOD Depth of discharge I Current t Time C Battery capacity Temperature n
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