Optimal power dispatch in wind farm based on reduced blade damage and generator losses

Zhang, Jinhua; Liu, Yongqian; Tian, De; Yan, Jie

doi:10.1016/j.rser.2014.12.008

Cited by 17 publications

(10 citation statements)

References 18 publications

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“…Due to the existence of grouping strategy, traditional MASCA is not applicable, so a virtual consistency algorithm is proposed in this section. In order to make each WT obtain reasonable power reference value according to r i in (12), this paper defines two auxiliary variables:…”

Section: Virtual Consistency Algorithm For Segmental Updatementioning

confidence: 99%

“…In the principle that the WT is theoretically dispatchable, researchers proposed some solutions to solve the APD problem, and the primary objective is to meet the demand of power grid and improve the economy of WF [8][9][10][11][12][13][14]. In [8], researchers distributed the power proportionally based on the maximum available power of WTs.…”

Section: Introductionmentioning

confidence: 99%

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Active power dispatch strategy of the wind farm based on improved multi‐agent consistency algorithm

Yao

Chen

et al. 2019

IET Renewable Power Generation

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With the increase of wind power penetration in the power system, wind farm (WF) needs to limit active power and accurately track the instructions from the dispatch centre. Since a WF has many distributed wind turbines (WTs), it is a crucial issue to reasonably distribute power reference values to WTs. In this study, a novel active power dispatch (APD) strategy based on dynamic grouping of WTs is proposed. This strategy considers the characteristics and operating conditions of WTs, which can smoothen the power reference values to WTs and reduce fluctuations of key parameters of WTs. Then, a distributed dispatch strategy based on multi-agent system consistency algorithm (MASCA) is applied for APD, which provides a dispatch strategy for WTs that does not require a centralised control centre. And the segmental virtual consistency algorithm is presented as an improvement of MASCA, which innovatively allows MASCA to support the grouping strategy for APD. Finally, the simulations show that the proposed strategy can enable WTs to obtain smoother reference power to track the dispatching instruction while reducing fluctuations of rotor speed and pitch angle, which is helpful to alleviate the fatigue of WTs. The dispatch strategy also shows good robustness when some communication is interrupted.

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Section: Virtual Consistency Algorithm For Segmental Updatementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Active power dispatch strategy of the wind farm based on improved multi‐agent consistency algorithm

Yao

Chen

et al. 2019

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…This strategy includes the losses along the transmission system, as well as the losses inside the WTs, in the objective [25,47,48]. Thus, the optimization problem can be written as: This strategy considers all of the losses inside the WF in the optimization objective, which is promising for producing the lowest active power loss for the WF.…”

Section: Strategy C: Wf Total Loss Minimizationmentioning

confidence: 99%

Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm

Zhang

Hou

et al. 2017

Energies

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This paper reviews and compares the performance of reactive power dispatch strategies for the loss minimization of Doubly Fed Induction Generator (DFIG)-based Wind Farms (WFs). Twelve possible combinations of three WF level reactive power dispatch strategies and four Wind Turbine (WT) level reactive power control strategies are investigated. All of the combined strategies are formulated based on the comprehensive loss models of WFs, including the loss models of DFIGs, converters, filters, transformers, and cables of the collection system. Optimization problems are solved by a Modified Particle Swarm Optimization (MPSO) algorithm. The effectiveness of these strategies is evaluated by simulations on a carefully designed WF under a series of cases with different wind speeds and reactive power requirements of the WF. The wind speed at each WT inside the WF is calculated using the Jensen wake model. The results show that the best reactive power dispatch strategy for loss minimization comes when the WF level strategy and WT level control are coordinated and the losses from each device in the WF are considered in the objective.

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“…The conventional power command distribution model has focused mostly on reducing the error between the power output of a wind farm and the power command from the TSO without considering the fatigue load. Recently, different methods have been proposed for power command distribution to yield a reduction in COE [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

“…Zhang et al applied optimization algorithms, including the genetic algorithm and improved binary particle swarm algorithm, to their wind farm controller and verified the power output and mechanical load variation through simulation [21]. In their study, the power output of the wind farm was controlled by the shutdown and power derating of the turbines.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Effect of Closed-Loop Wind Farm Control on Power and Tower Load in Derating the TSO Command Condition

Kim

Paek

2019

Energies

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This study was conducted to analyze the impact of surrounding environmental changes on the feedback gain and performance of a closed-loop wind farm controller that reduces the error between total power output of wind farm and power command of transmission system operator. To analyze the impact of environment changes on wind farm controller feedback gain, the feedback gain was manually changed from 0 to 0.9 with a 0.1 interval. In this study, wind speed and wind direction changes were considered as environment changes; it was found by simulation code that the wind farm controller gain is in inverse proportion to wake recovery rate. In other words, the feedback gain should be higher if the distance between upstream and downstream wind turbine is not sufficient to wake recovery. Furthermore, the feedback gain should be lower when the upstream wind turbine generates a relatively weak wake by operating above the rated wind speed. The wind farm simulation was performed using reference 5 MW wind turbines from the National Renewable Energy Laboratory (NREL), which are numerically modeled for each element so that wind farm power output and tower load can be calculated according to the variation of the power command by using a modified wake model with improved accuracy. All the simulations performed in this study were carried out to review the power output accuracy of wind farms, but only if the transmission system operator’s power command was lower than the available power of wind farm. In this study, the gain of the wind farm controller was applied differently depending on the wind speed and direction to consider benefits in terms of power and tower load, especially if the wake effect of the upstream wind turbine was rapidly transferred to the downstream wind turbine. Ultimately, a simple, but more effective, power distribution method was proposed for distributing power commands to wind turbines that constitute wind farms and the study indicated the need for controller gain adjustment based on surrounding environmental changes.

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Optimal power dispatch in wind farm based on reduced blade damage and generator losses

Cited by 17 publications

References 18 publications

Active power dispatch strategy of the wind farm based on improved multi‐agent consistency algorithm

Active power dispatch strategy of the wind farm based on improved multi‐agent consistency algorithm

Review of Reactive Power Dispatch Strategies for Loss Minimization in a DFIG-based Wind Farm

A Study on the Effect of Closed-Loop Wind Farm Control on Power and Tower Load in Derating the TSO Command Condition

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