Defining a degradation cost function for optimal control of a battery energy storage system

Koller, Michael; Borsche, Theodor; Ulbig, Andreas; Andersson, Göran

doi:10.1109/ptc.2013.6652329

Cited by 152 publications

(109 citation statements)

References 13 publications

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“…In terms of battery degradation models, several works have identified the need to incorporate it in economic analysis of electricity systems [9][10][11][12]. In particular, references [9][10][11] focused on battery degradation cost functions that can be included in system optimization models.…”

Section: [Mvar]mentioning

confidence: 99%

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Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage

Pérez

Moreno

Moreira

et al. 2016

IEEE Trans. Sustain. Energy

101

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Abstract-In an electricity market environment, energy storage plant owners are remunerated for the provision of services to multiple electricity sectors. Some of these services, however, may accelerate battery aging and degradation and hence this needs to be properly balanced against associated services remunerations. In this framework, we propose a combined economic-degradation model to quantify effects of operational policies (mainly focused on constraining State of Charge -SOC-to prescribed levels in order to reduce effects of aging) on gross revenue, multi-service portfolios, degradation and lifespan of distributed energy storage plants that can provide multiple services to energy and balancing market participants and Distribution Network Operators (DNO). Through various case studies based on the Great Britain (GB) system, we demonstrate that although operational policies focused on battery damage reduction will lead to a revenue loss in the shortterm, such loss can be more than compensated by long-term revenues due to a lengthier battery lifespan. We also demonstrate that operational policies to reduce battery degradation mainly affect services related to the energy (rather than balancing) market, which represents a smaller proportion of the overall revenue streams of a distributed storage plant. The model is also used to study effects of ambient temperature fluctuations.Index Terms-Distributed energy storage, multi-service portfolios, degradation, temperature control, power system economics. I. NOMENCLATURE A. Parameters

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Section: [Mvar]mentioning

confidence: 99%

“…In particular, references [9][10][11] focused on battery degradation cost functions that can be included in system optimization models. These approaches have been proposed to investigate effects of either energy arbitrage [10], peak shaving [11] and frequency control services [12] on battery degradation.…”

Section: [Mvar]mentioning

confidence: 99%

Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage

Pérez

Moreno

Moreira

et al. 2016

IEEE Trans. Sustain. Energy

101

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“…e problem we have described in section 1.1 was already underlined by some authors [7][8][9]. We can summarize some keys aspects of their contributions: Serrao et.…”

Section: Previous Work On Aging Controlmentioning

confidence: 89%

“…al [8] (wind power context) both use weighted charge counting to model cycling aging, while Koller et. al [9] (peak shaving context) use a piece-wise a ne model with quadratic cost because it enables e cient optimization solving.…”

Section: Previous Work On Aging Controlmentioning

confidence: 99%

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Energy storage control with aging limitation

Haessig

Ahmed

Multon

2015

2015 IEEE Eindhoven PowerTech

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Energy Storage Systems (ESS) are o en proposed to mitigate the uctuations of renewable power sources like wind turbines. In such a context, the main objective for the ESS control (its energy management) is to maximize the performance of the mitigation scheme.However, most ESS, and electrochemical ba eries in particular, can only perform a limited number of charge/discharge cycles over their lifetime. is limitation is rarely taken into account in the optimization of the energy management, because of the lack of an appropriate formalization of cycling aging.We present a method to explicitly embed a limitation of cycling aging, as a constraint, in the control optimization. We model cycling aging with the usual "exchanged energy" counting method. We demonstrate the e ectiveness of our aging-constrained energy management using a publicly available wind power time series. Day-ahead forecast error is minimized while keeping storage cycling just under an acceptable target level.

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Stochastic battery energy storage scheduling considering cell degradation and distributed energy resources

Tang

Sun

et al. 2019

Int Trans Electr Energ Syst

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Summary The penetration of distributed energy resources (DERs) greatly raises the risk of distribution network operation such as peak shaving and voltage stability. Battery energy storage (BES) has been widely accepted as the most potential application to cope with the challenge of high penetration of DERs. To cope with the uncertainties and variability of DERs, a stochastic BES scheduling model and its algorithm are proposed. The overall economy is achieved by fully considering the cell degradation, DERs, electricity purchasing, and active power losses. The rainflow algorithm‐based cycle counting method is incorporated in the BES scheduling model to capture the cell degradation, greatly extending the expected BES lifetime and achieving a better economy. DER power scenarios are generated to consider the uncertainties and correlations based on the Copula theory. To solve the BES scheduling model, we propose a Lagrangian relaxation‐based algorithm, which has a significantly reduced complexity with respect to the existing techniques. For this reason, the proposed algorithm enables much more scenarios incorporated in the BES scheduling model and better captures the DER uncertainties and correlations. Finally, numerical studies for the day‐ahead BES scheduling in the IEEE 123‐node test feeder are presented to demonstrate the merits of the proposed method. Results show that the actual BES life expectancy of the proposed model has increased to 4.89 times compared with the traditional ones. The problems caused by DERs are greatly alleviated by fully capturing the uncertainties and correlations with the proposed method.

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Defining a degradation cost function for optimal control of a battery energy storage system

Cited by 152 publications

References 13 publications

Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage

Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage

Energy storage control with aging limitation

Stochastic battery energy storage scheduling considering cell degradation and distributed energy resources

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