The fact that the developing world struggles to cover even the most basics of needs, in contrast to the developed world, is tangibly connected to the lack of electricity. As many developing nations, especially the ones located in rural areas, face many difficulties to access the grid, alternative stand-alone solutions such as Solar Home Systems (SHS) have been proposed and used already for a while. The main technical limitation plaguing SHSs is the necessity of including a storage device that mitigates the energy difference between production and demand. Batteries are the components that experience the shortest lifetime and highest cost in stand-alone PV systems such as SHSs.

This study aims to explore and find the most suitable and viable storage option in terms of lifetime and costs for certain load cases concerning SHS applications. In order for this to be achieved, single battery options, as well as Hybrid battery options, were examined.

For the comparison of the different battery technologies with the different Hybrid battery configurations, lifetime and costs had to be taken into account. For this purpose a non-empirical dynamic battery lifetime estimation method was modelled and applied to four different battery technologies and a variety of different Hybrid battery combinations. The battery technologies examined in this thesis are Lithium iron phosphate (LiFePO4), Sealed lead-acid (VRLA), Nickel-Cadmium (NiCd) and Flooded lead-acid. This method takes into account different DOD (Depth of Discharge) levels, Temperature effects and lifetime curves extracted from different datasheets for the different technologies, in order to be able to model the different battery behaviours as accurately as possible.

For the modelling of the different Hybrid battery configurations two different power management schemes were constructed and applied to the dynamic lifetime estimation that is proposed. This method was validated and concluded to be realistic as it was able to capture the different battery characteristics for the different technologies.

For the comparison of the different storage options, a singular function was constructed for both single and hybrid battery options. This function quantifies both upfront and lifetime battery costs while, at the same time, captures the future battery cost trends that are foreseen for different technologies. This function was used as the point of reference in the comparison of every storage option that was tested.

The optimum storage option that minimizes the battery cost function for the two sets of PV-load Case studies used in this project, was found to be a Hybrid battery that consists of LiFePO4 and Sealed lead-acid technology, with different sizes and configurations.

In conclusion, the lifetime method proposed as well as the battery cost function constructed could be easily adopted and used for a variety of different battery technologies in low-power applications. A prerequisite for the above mentioned realization is that cycle life data of the examined technology are either provided or easy to be constructed.