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• Comparison of calendar and cycling ageing models of LFP battery energy storage. • Higher temperatures and cycle depth of discharge promote cycling aging. • Higher temperatures and battery state of charge promote Calendar aging. • Low profitability conditions increase calendar contribution to overall aging. • Virtually decreasing cycling costs during optimization reduces operational losses. The growing share of renewable energy sources in the energy mix and the liberalisation of electricity markets has drastically affected the operation of electricity generators and grids. The transition from a fossil-fuel-based energy system to a renewable one has been significantly impacting the energy market, and energy storage systems have a pivotal role to play. In the coming years, a large amount of storage capacity is envisaged to be integrated into electricity grids to shave demand peaks, mitigate price volatility and face the growing demand for services to system operators. In such a situation, to properly manage these assets, and thus guarantee the economic viability of operating, it is essential to optimise their dispatch and define the best possible scheduling considering any hidden costs such as degradation. This paper focuses on Li-ion Battery Energy Storage (BES), as the fastest-deploying BES. A comprehensive literature study is carried out to provide a detailed review of ageing process modelling. Both the cycling and the calendar ageing processes are investigated considering the impacts of Depth of Discharge (DoD), State of Charge (SoC), temperature (T), C rate , number of cycles (N cycles ), and time (t). Moreover, the dependence of the efficiency of the charging and discharging phases on the current rate is remarkable. The dispatch optimisation is guaranteed by a proposed Mixed-Integer Linear Programming optimisation algorithm which considers the impact of degradation cost but is independent of the model selected from the literature. The literature review reveals that previous studies, dealing with battery dispatch optimisation, only include the cycling degradation explicitly in the objective function. In this work, the calendar degradation, impacting the battery capacity even when the battery is not in use, is also considered. This requires development of a strategy to properly weight the calendar contribution to fade, particularly when arbitrage opportunities are limited because of small daily price fluctuations. The proposed strategy involves the use of a factor R to adjust the cost associated with cycling. The optimal value of this factor is highly dependent on the economic conditions of the market, necessitating a sensitivity analysis to evaluate its impact.
Vasylyev et al. (Fri,) studied this question.