Modelling of Lithium-ion Battery Ageing for a Local Energy Community

Abstract

As we are inching towards a deregulated environment, the residential consumers are stepping up to play the role of prosumers with the growing usage of solar rooftop PV in the modern day microgrid. These PV arrays are generally equipped with battery energy storage systems (BESS) to increase the system reliability. This PV-BESS combination ensures reduced electricity bill, maximized self-consumption and little environmental impact. The challenges faced by the PV-BESS at residential level is their optimal sizing and optimal operation as their cost is far high when compared to that of other components in the system. To perform above tasks, accurate forecasts of load as well as PV power are required. To address the above issues, this paper presents the solar PV power and load demand forecasting using long-short term memory (LSTM) networks followed by modeling of lithium-ion battery for residential prosumers. These are used to find out the optimal size of the battery. The impact of various factors affecting battery ageing such as temperature, state-of charge and charge/discharge rate (C-rate) are discussed. A severity factor index is used to study the sensitivity of these factors on capacity fade of a lithium-ion battery. Finally, an objective function to minimize the battery degradation cost is formulated using the battery ageing model.