Abstract
An increasing share of renewable energy sources in power systems requires ad-hoc tools to guarantee the closeness of the system’s frequency to its rated value. At present, the use of new technologies, such as battery energy storage systems, is widely debated for its participation in the service of frequency containment. Since battery installation costs are still high, the estimation of their lifetime appears crucial in both the planning and operations of power systems’ regulation service. As the frequency response of batteries is strongly dependent on the stochastic nature of the various contingencies which can occur on power systems, the estimation of the battery lifetime is a very complex issue. In the present paper, the stochastic process which better represents the power system frequency is analyzed first; then the battery lifetime is properly estimated on the basis of realistic dynamic modeling including the state of the charge control strategy. The dynamic evolution of the state of charge is then used in combination with the celebrated rain-flow procedure with the aim of evaluating the number of charging/discharging cycles whose knowledge allows estimating the battery damage. Numerical simulations are carried out in the last part of the paper, highlighting the resulting lifetime probabilistic expectation and the impact of the state of the charge control strategy on the battery lifetime. The main findings of the present work are the proposed autoregressive model, which allows creating accurate pseudo-samples of frequency patterns and the analysis of the incidence of the control law on the battery lifetime. The numerical applications clearly show the prominent importance of this last aspect since it has an opposing impact on the economic issue by influencing the battery lifetime and technical effects by modifying the availability of the frequency regulation service.
Highlights
In the last few decades, a large deployment of renewable energy sources (RESs) and the implementation of the deregulated energy market have led to larger frequency changes in power systems
The mean value of the lifetime duration is 8.20 years and the standard deviation is 1.20 years. This value is aligned with the results reported in the literature such as, for example, in [29], where experimental tests on batteries of the same technology used for primary frequency regulation showed a lifetime of eight years
The paper aims to describe the dependence of the lifetimeThe distribution characteristics on the evaluation of the probabilistic features of the battery lifetime
Summary
In the last few decades, a large deployment of renewable energy sources (RESs) and the implementation of the deregulated energy market have led to larger frequency changes in power systems. In order to allow BESSs to contribute in an effective way to the frequency regulation service, the energy capacity needs to be properly rated In this regard, BESS sizing could be roughly performed by assigning the droop value and by taking into account that the primary frequency reserve must be linearly deployed within a specified time and frequency intervals. The main contribution of this paper relies upon a rational procedure for deriving the lifetime probability distribution from the knowledge of a limited set of power system frequency samples This is a fundamental step to take into account reliability aspects in the battery design procedure, which could be considered among the most critical ones.
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