Considerations on the impact of battery ageing estimation in the optimal sizing of solar home battery systems

Abstract

The exponential reduction in cost of photovoltaic panels and the forecasts projecting a similar behaviour for battery-based energy storage systems are driving increasing attention on residential energy systems based on photovoltaic (PV) panels and batteries. Such systems, if combined with demand electrification, could help decarbonising the sector and foster the adoption of distributed energy systems. In this work, a modular tool for the techno economic analysis of smart energy systems is applied to a case study in the residential sector. The considered system is composed by PV panels, battery, heat pump and air conditioning system. The tool integrates a method for the estimation of cyclic and calendric ageing of the battery. The effects of varying battery capacity and its maximum depth of discharge on its lifetime have been investigated. An optimization algorithm has been employed to find the battery capacity that maximizes net present value (NPV) for given battery prices and PV panels areas. Results have highlighted the impact of using ageing models on the economics of residential energy systems, suggesting that discontinuities might arise in the functions to be optimized, hence requiring more robust optimization algorithms. Results also suggest that not accounting for battery aging could lead to incorrect predictions regarding the economics of the system. The breakeven price for the introduction of batteries in residential energy systems is lower when using ageing algorithms, while, at the same time, higher optimal capacities have been obtained for lower battery prices.