A flexible model for economic operational management of grid battery energy storage

Fares, Robert L.; Webber, Michael E.

doi:10.1016/j.energy.2014.10.072

Cited by 46 publications

(13 citation statements)

References 41 publications

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“…To verify the accuracy of proposed model and evaluate its performance compared to other conventional modeling approaches, a classical equivalent circuit second-order RC (2-RC) model [30][31][32][33] is adopted here to use as the reference.…”

Section: Accuracy Of the Proposed Fractional-order Modelmentioning

confidence: 99%

Parameter Sensitivity Analysis for Fractional-Order Modeling of Lithium-Ion Batteries

et al. 2016

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This paper presents a novel-fractional-order lithium-ion battery model that is suitable for use in embedded applications. The proposed model uses fractional calculus with an improved Oustaloup approximation method to describe all the internal battery dynamic behaviors. The fractional-order model parameters, such as equivalent circuit component coefficients and fractional-order values, are identified by a genetic algorithm. A modeling parameters sensitivity study using the statistical Multi-Parameter Sensitivity Analysis (MPSA) method is then performed and discussed in detail. Through the analysis, the dynamic effects of parameters on the model output performance are obtained. It has been found out from the analysis that the fractional-order values and their corresponding internal dynamics have different degrees of impact on model outputs. Thus, they are considered as crucial parameters to accurately describe a battery's dynamic voltage responses. To experimentally verify the accuracy of developed fractional-order model and evaluate its performance, the experimental tests are conducted with a hybrid pulse test and a dynamic stress test (DST) on two different types of lithium-ion batteries. The results demonstrate the accuracy and usefulness of the proposed fractional-order model on battery dynamic behavior prediction.

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Section: Accuracy Of the Proposed Fractional-order Modelmentioning

confidence: 99%

Parameter Sensitivity Analysis for Fractional-Order Modeling of Lithium-Ion Batteries

et al. 2016

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“…The last resistive element of the equivalent-circuit model is related to the diffusion of Li ions through the membrane. The diffusion process causes a voltage drop in the battery cell and is inversely proportional to the operating temperature (4). Similar to the membrane diffusion process, there exists an electrode diffusion mechanism (5).…”

Section: B Resistive Elementsmentioning

confidence: 99%

Non-Ideal Linear Operation Model for Li-Ion Batteries

Gonzalez-Castellanos

Pozo

Bischi

2020

IEEE Trans. Power Syst.

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Currently, the characterization of electric energy storage units used for power system operation and planning models relies on two major assumptions: charge and discharge efficiencies, and power limits are constant and independent of the electric energy storage state of charge. This approach can misestimate the available storage flexibility.This work proposes a detailed model for the characterization of steady-state operation of Li-ion batteries in optimization problems. The model characterizes the battery performance, including non-linear charge and discharge power limits and efficiencies, as a function of the state of charge and requested power. We then derive a linear reformulation of the model without introducing binary variables, which achieves high computational efficiency, while providing high approximation accuracy. The proposed model characterizes more accurately the performance and technical operational limits associated with Li-ion batteries than those present in classical ideal models.The developed battery model has been compared with three modelling approaches: the complete non-convex formulation; an ideal model typically used in the power system community; and a mixed integer linear reformulation approach. The models have been tested on a network-constrained economic dispatch for a 24bus system. Based on the simulations, we observed approximately 12% of energy mismatches between schedules that use an ideal model and those that use the model proposed in this study.

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“…In the first study [124], the effect of 1MW BESS managed by two fuzzy logic controllers on primary control reserve and energy arbitrage services was tested with real metered data from an Italian network. In [125], to maximize the daily operation revenue of a lithium-ion (Li-ion) battery, the authors tested a dynamic battery model based on optimum charging-discharging in an 11 year simulation of Texas region data. In another study [126], optimum management of a distributed battery energy storage system for energy arbitrage under dynamic pricing conditions was presented and the results showed which arbitrage policy is Pareto optimal for value lifetime performance.…”

Section: Energy Arbitragementioning

confidence: 99%

Assessment of Battery Storage Technologies for a Turkish Power Network

Kocer

Cengiz²,

Gezer³

et al. 2019

Sustainability

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Population growth has brought an increase in energy demand and cost that has a meaningful impact on personal and government expenses. In this respect, governments attach importance to investments in renewable energy resources (RER), which are a sustainable and clean energy source. However, the unpredictable characteristics of RER are a major problem for these clean sources and RER need auxiliary assets. Battery energy storage systems (BESS) are one of the promising solutions for these issues. Due to the high investment cost of BESS, governments act cautiously about accepting and implementing BESS in their power network. Recently, with the improvement of technology, the cost of BESS has been reduced, and therefore battery technologies have begun to be applied to conventional systems. In this study, first, we will review and discuss the current globally state-of-the-art BESS and their applications. Later, attention will be turned to a country-specific study for Turkey.

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A flexible model for economic operational management of grid battery energy storage

Cited by 46 publications

References 41 publications

Parameter Sensitivity Analysis for Fractional-Order Modeling of Lithium-Ion Batteries

Parameter Sensitivity Analysis for Fractional-Order Modeling of Lithium-Ion Batteries

Non-Ideal Linear Operation Model for Li-Ion Batteries

Assessment of Battery Storage Technologies for a Turkish Power Network

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