Charging Management of Chemical Lithium Nickel Cobalt Aluminum Oxide (LiNiCoAlO2) Batteries, Considering Battery Degradation Effects under Uncertain Operation in Multi-energy Systems

Abstract

Chemical Lithium battery energy storage (BES) systems are considered as critical assets in providing flexibility and reliability for today's power and energy systems. However, BES degradation, which is due to the electrolyte reaction in lithium batteries, introduces some challenges to smart grid operators in terms of optimal charging/discharging management strategies. Although, considering degradation in BES operation can lead to long-term benefits, the associated uncertainties of renewable generations, load, and energy prices can pose a noticeable effect on BES operation optimality and accordingly affect the associated long-term benefits, if ignored. In fact, disregarding uncertainties in BES operation can lead to nonoptimal or even infeasible charging/discharging solutions, resulting in extra costs and even higher BES degradation rates. This paper presents an adaptive robust optimization approach to optimally characterize degradation in charging/discharging management of BES at the presence of uncertainties. The model is developed for a multi-energy system with electricity and natural gas as operating energy types. A Lithium Nickel Cobalt Aluminum Oxide (LiNiCoAlO2) battery is considered as the BES in the multi-energy system. Uncertainties of load, renewable generation, and energy prices are characterized with bounded interval through polyhedral uncertainty sets. The proposed model is solved through a column-and-constraint generation approach. A post-event analysis is conducted to evaluate the long-term performance of the proposed model. According to the obtained results, the proposed adaptive robust energy management model shows 18% growth in long-term benefit recovery and 15% reduction in loss of load, compare to deterministic model, considering battery degradation effects.