A wake interaction model for the coordinated control of Wind Farms

Pan, Lin; Voos, Holger; Li, Yu Mei; Xu, Yuhua; Darouach, Mohamed; Hu, Shujun

doi:10.1109/etfa.2015.7301420

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…Due to the location optimization caused by operation in the unsteady flow condition and dynamic loading exerted on the Wind Turbine (WT), one of its main problems is how to increase performance of the control system as decision-making, which makes the most effective use of the WT controller. The WT location optimization is an interesting topic, which provides a predominant approach to increase the total WP of the Wind Farm (WF) and decreases the wake effect of WTs [13][14][15]. In recent years, the size of WTs has been more extensive from a few kilowatts to several megawatts.…”

Section: Introductionmentioning

confidence: 99%

Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms

Xiao

Pan

et al. 2019

Energies

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This paper reports a novel frandsen generalized wake model and its variation model-frandsen generalized normal distribution wake model for off-shore wind farms. Two different new wake models in off-shore wind farms have been studied comparatively. Their characteristics have been analyzed through mathematical modeling and derivation. Meanwhile, simulation experiments show that the proposed two new wake models have different properties. Furthermore, the distributions of wind speed and wind direction are modeled by the statistical methods and Extreme Learning Machine through the off-shore wind farms of Yangshan Deepwater Harbor in the Port of Shanghai, China. In addition, the data of wind energy are provided to verify and test the correctness and effectiveness of the proposed two models. Wind power has been demonstrated by wind rose and wind resources with real-time data. These techniques contribute to enhance planning, utilization and exploitation for wind power of off-shore wind farms.

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Section: Introductionmentioning

confidence: 99%

Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms

Xiao

Pan

et al. 2019

Energies

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“…nuclear power, thermal power, hydropower, etc. [1][2][3][4][5][6][7], these wind devices and equipment are expected to operate and provide high quality power (Such as: Safe, Stable, Controllable and Predictable (SSCP)) at the lowest possible cost.…”

Section: Introductionmentioning

confidence: 99%

A generalized interaction Wake Model with its variation for control in Wind Farms

Pan

Voos

Darouach

2016

2016 35th Chinese Control Conference (CCC)

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In this paper, an Improved Frandsen Wake Model(IFWM) and its variation model-Improved Frandsen Normal Distribution Wake Model(IFNDWM) for Wind Farms(WFs) have been presented and analyzed exhaustively with mathematic forms. The comparisons of these two different wake models of WFs also have been expounded. Meanwhile, experimental comparisons of both Wake Models are studied. Further, focused on the WFs of Luxembourg, the statistical methods are used to model the distribution of Wind Speed(WS) and Wind Direction(WD). Finally, some simulations are provided to test and verify their effectiveness and correctness of these models. Wind Rose(WR) and wind resources demonstrate Wind Power (WP) in full. These assessments are expected to enhance WP exploitation and utilization in WFs of Luxembourg.

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“…In the processes of Wind Energy (WE) utilization, Wind Power (WP) assessment is a critical step. In order to enhance the effective utilization of WE, the best way is to utilize existing WFs through improving control techniques and algorithms [1,2,3,4,5]. Nowadays, many researches and developments of WE harvesting systems are focused on optimizing different aspects of WTs in order to improve its Cost of Energy(CoE), such as optimal placements of WTs in a specific area.…”

Section: Introductionmentioning

confidence: 99%