Testing the Performance of Battery Energy Storage in a Wind Energy Conversion System

Sattar, Adnan; Al‐Durra, Ahmed; Debouza, Mahdi; Muyeen, S. M.

doi:10.1109/tia.2020.2979792

Cited by 32 publications

(8 citation statements)

References 24 publications

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“…As an illustration, it is shown that the region of q preventing the overpower of the ESS. Figure 6 shows the 2D plot of Equation (24). As shown in Figure 6, the overpower on the ESS is prevented when q ≤ 1825.…”

Section: Figurementioning

confidence: 97%

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One‐sample optimal output smoothing method for wind farm with energy storage system

Koiwa

Ishii

Liu

et al. 2021

IET Renewable Power Gen

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This paper proposes a novel optimization method for energy storage systems (ESSs) to smooth wind farm output to satisfy the technical requirements and reduce the rated power (rated energy capacity) and charge/discharge loss of the ESS. The state of charge of the ESS operated by the proposed method can be regulated, guaranteeing some constraints. The proposed method has a very simple structure, does not require the wind farm output forecast and numerical optimization, such as particle swarm optimization. Therefore, a high-grade functional computation device is not needed. The effectiveness of the proposed method is verified by comparative analysis with conventional approaches through simulations. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Figurementioning

confidence: 97%

“…In the optimization block, P ref b (t ) is generated, which operates the ESS optimally. The dynamics of the ESS can be ignored because it is known that the dynamics of the ESS is fast enough and does not affect its control performance [5,24]. Moreover, the positive sign of P b (t ) implies the power charge of the ESS.…”

Section: System Configurationmentioning

confidence: 99%

One‐sample optimal output smoothing method for wind farm with energy storage system

Koiwa

Ishii

Liu

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Shi et al [4] established a wind energy storage hybrid system to analyze the fluctuation feature of wind power output in both time and frequency domains. Sattar et al [5] examined the dynamic and transient performance of an ESS connected to the output of a wind energy conversion system to smooth the short-term fluctuations in the output power. Caralis et al [6] investigated the role that energy storage can play in the further development of wind energy in microgrids and examined the solution of ESSs in curtailment exploitation.…”

Section: A Related Workmentioning

confidence: 99%

Wind Power Smoothing With Energy Storage System: A Stochastic Model Predictive Control Approach

Gao

Liu

et al. 2021

IEEE Access

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The utilization of energy storage system (ESS) is an effective method for dealing with the randomness and variability of wind power. Therefore, improving the coordination between ESS and wind power is a direction worthy of research. This study develops a two-layer stochastic model predictive control (SMPC) method for wind power smoothing on different time-scales. The proposed optimization framework smooths wind energy by adjusting the charge and discharge power of hybrid ESSs; moreover, it combines the SMPC approach and the chance constraints to address the uncertainties of wind energy. Furthermore, the previous states are taken into account, in addition to states within the rolling time horizon, to obtain optimal control of the hybrid ESSs, and capacity planning for hybrid ESSs is conducted simultaneously. The numerical results obtained through amplitude-frequency simulation comparison prove that the proposed method is superior to the conventional method in terms of minimizing the frequency fluctuation of wind power and the size of the ESS.

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“…A good review of the literature targeting different kinds of energy storage systems (e.g., battery-, supercap-, flywheel-based, etc. ), can be found always in Barra et al [11], while aspects related to the performances of battery-based energy storage systems, with the aim of power smoothing in wind farms, are investigated in Sattar et al [16]. Finally, hybrid configurations are also addressed [17,18].…”

Section: Introductionmentioning

confidence: 99%

Operating Hydrogen-Based Energy Storage Systems in Wind Farms for Smooth Power Injection: A Penalty Fees Aware Model Predictive Control

2022

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Smooth power injection is one of the possible services that modern wind farms could provide in the not-so-far future, for which energy storage is required. Indeed, this is one among the three possible operations identified by the International Energy Agency (IEA)-Hydrogen Implementing Agreement (HIA) within the Task 24 final report, that may promote their integration into the main grid, in particular when paired to hydrogen-based energy storages. In general, energy storage can mitigate the inherent unpredictability of wind generation, providing that they are deployed with appropriate control algorithms. On the contrary, in the case of no storage, wind farm operations would be strongly affected, as well as their economic performances since the penalty fees wind farm owners/operators incur in case of mismatches between the contracted power and that actually delivered. This paper proposes a Model Predictive Control (MPC) algorithm that operates a Hydrogen-based Energy Storage System (HESS), consisting of one electrolyzer, one fuel cell and one tank, paired to a wind farm committed to smooth power injection into the grid. The MPC relies on Mixed-Logic Dynamic (MLD) models of the electrolyzer and the fuel cell in order to leverage their advanced features and handles appropriate cost functions in order to account for the operating costs, the potential value of hydrogen as a fuel and the penalty fee mechanism that may negatively affect the expected profits generated by the injection of smooth power. Numerical simulations are conducted by considering wind generation profiles from a real wind farm in the center-south of Italy and spot prices according to the corresponding market zone. The results show the impact of each cost term on the performances of the controller and how they can be effectively combined in order to achieve some reasonable trade-off. In particular, it is highlighted that a static choice of the corresponding weights can lead to not very effective handling of the effects given by the combination of the system conditions with the various exogenous’, while a dynamic choice may suit the purpose instead. Moreover, the simulations show that the developed models and the set-up mathematical program can be fruitfully leveraged for inferring indications on the devices’ sizing.

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Testing the Performance of Battery Energy Storage in a Wind Energy Conversion System

Cited by 32 publications

References 24 publications

One‐sample optimal output smoothing method for wind farm with energy storage system

One‐sample optimal output smoothing method for wind farm with energy storage system

Wind Power Smoothing With Energy Storage System: A Stochastic Model Predictive Control Approach

Operating Hydrogen-Based Energy Storage Systems in Wind Farms for Smooth Power Injection: A Penalty Fees Aware Model Predictive Control

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