A battery energy storage system dual-layer control strategy for mitigating wind farm fluctuations

Jiang, Quanyuan; Gong, Yitao; Wang, Haijiao

doi:10.1109/pesgm.2014.6939424

Cited by 38 publications

(55 citation statements)

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“…The proposed method is compared with the conventional LPF method [12] and the conventional zero-phase low-pass filter (ZLF) method [13] in order to verify its effectiveness, while the performances of the hybrid system using each control method are shown in Fig. 11.…”

Section: Optimization Of Ess Capacitymentioning

confidence: 99%

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Optimal Power Control Strategy for Wind Farm with Energy Storage System

Nguyen¹,

Lee²

2017

Journal of Electrical Engineering and Technology

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-The use of energy storage systems (ESSs) has become a feasible solution to solve the wind power intermittency issue. However, the use of ESSs increases the system cost significantly. In this paper, an optimal power flow control scheme to minimize the ESS capacity is proposed by using the zero-phase delay low-pass filter which can eliminate the phase delay between the dispatch power and the wind power. In addition, the filter time constant is optimized at the beginning of each dispatching interval to ensure the fluctuation mitigation requirement imposed by the grid code with a minimal ESS capacity. And also, a short-term power dispatch control algorithm is developed suitable for the proposed power dispatch based on the zero-phase delay low-pass filter with the predetermined ESS capacity. In order to verify the effectiveness of the proposed power management approach, case studies are carried out by using a 3-MW wind turbine with real wind speed data measured on Jeju Island.

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Section: Optimization Of Ess Capacitymentioning

confidence: 99%

“…In the LPF-based power flow control method, both infinite and finite impulse response types have been applied to mitigate the wind power fluctuation. In the infinite impulse response LPF, the first-order filter is usually adopted [12]. However, the phase delay in the pass-band of the filter requires a high capacity ESS.…”

Section: Introductionmentioning

confidence: 99%

Optimal Power Control Strategy for Wind Farm with Energy Storage System

Nguyen¹,

Lee²

2017

Journal of Electrical Engineering and Technology

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“…Hence, the smoothing time constant, T c , must be set to a value ensuring that the fluctuation of the power dispatch does not exceed the two corresponding limitations of 1min γ and 30 min γ [16]. In this paper, we determine the smoothing time constant based on the curve expressed by the fluctuation in power with respect to the smoothing time constant.…”

Section: Determination Of the Smoothing Time Constantmentioning

confidence: 99%

“…The pitch angle is controlled to regulate the wind turbine (WT) output power following a smoothened power reference; however, this method increases system complexity, and the WT might not capture the maximum power of the wind [6]. Recently, the utilization of energy storage systems (ESSs) as an energy buffer to compensate for wind power fluctuation has been proposed and investigated in several literatures [7][8][9][10][11][12][13][14][15][16][17]. Compared with previous solutions, ESSs can help wind energy conversion systems harness the maximum available wind power; this valuable outcome is actually the most fundamental demand in renewable energy systems.…”

Section: Introductionmentioning

confidence: 99%

“…Both of these dispatching strategies require an advance wind power forecast of several hours, and they involve a complicated process to manage power dispatch in the short-term. Another dispatching method is an application of the low-pass filter, where the power dispatch is determined by smoothing the wind power through a low-pass filter [13][14][15][16][17]. This dispatching method is easy to implement and results in a small ESS power fluctuation, making it more feasible for controlling the power dispatch when compared with the aforementioned dispatching methods.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Wind Power Dispatch to Minimize Energy Storage System Capacity

Nguyen¹,

Lee²

2014

Journal of Electrical Engineering and Technology

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-By combining a wind turbine with an energy storage system (ESS), we are able to attenuate the intermittent wind power characteristic making the power derived from a wind farm dispatchable. This paper evaluates the influence of the phase delay of the low-pass filter in the conventional smoothing power control on the ESS capacity; longer phase delays require a larger ESS capacity. In order to eliminate the effect of the phase delay, we optimize the power dispatch using a zero-phase low-pass filter that results in a non-delayed response in the power dispatch. The proposed power dispatching method significantly minimizes the ESS capacity. In addition, the zero-phase lowpass filter, which is a symmetrical forward-reverse finite impulse response type, is designed simply with a small number of coefficients. Therefore, the proposed dispatching method is not only optimal, but can also be feasibly applied to real wind farms. The efficacy of the proposed dispatching method is verified by integrating a 3 MW wind turbine into the grid using wind data measured on Jeju Island.

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Scheduled Operation of Wind Farm with Battery System Using Deep Reinforcement Learning

Futakuchi

Takayama

Ishigame

2021

IEEJ Transactions Elec Engng

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With increasing amounts of wind power generation installed, the steep fluctuation of wind power generation output, called ramp events, causes serious problems for power system operation. Controlling fluctuations is an important issue for increasing the amount of wind power generation as a wind farm (WF) in the future. The authors reported the scheduled operation method of WF using a battery energy storage system (BESS) and forecast data of wind power generation output. In this paper, the authors propose a new scheduled operation method of WF. In particular, we propose the application of deep reinforcement learning to decide the output schedule of WF. Moreover, we compare the conventional method, the reinforcement learning method, and the deep reinforcement learning method in terms of the number of ramp events. In addition, we calculate the reducing effect of the storage capacity of BESS.

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A battery energy storage system dual-layer control strategy for mitigating wind farm fluctuations

Cited by 38 publications

References 0 publications

Optimal Power Control Strategy for Wind Farm with Energy Storage System

Optimal Power Control Strategy for Wind Farm with Energy Storage System

Optimization of Wind Power Dispatch to Minimize Energy Storage System Capacity

Scheduled Operation of Wind Farm with Battery System Using Deep Reinforcement Learning

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