Decentralized Coordinated Voltage Control for VSC-HVDC Connected Wind Farms Based on ADMM

Guo, Yifei; Gao, Houlei; Xing, Hao; Wu, Qiuwei; Lin, Zongli

doi:10.1109/tste.2018.2848467

Cited by 66 publications

(37 citation statements)

References 26 publications

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“…P PD j is the j-th units power set-point under a conventional PD strategy. For the entire cluster, (14) guarantees that the power set-point of all units equals to the cluster power demand, and (15) restricts the power set for each unit within a feasible interval that each unit has the ability to track its power setting. Moreover, the upper bound is a higher than the proportional distribution method and the lower bound is a lower.…”

Section: Constraintsmentioning

confidence: 99%

“…Some corresponding decentralized strategies are also investigated in wind farm power and voltage control process to reach an acceptable control effect. Related researches can be referred to [14,15]. With the increasing proportion of the wind power in the power system, wind power gradually begins to assume the task of peak load and frequency regulation of the power system as an important part of the power supply side [16].…”

Section: Introductionmentioning

confidence: 99%

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Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss

et al. 2018

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In this paper, a receding-horizon optimization strategy is introduced to optimize the wind farm active power distribution with power tracking error and transmission loss. Based on the wind farm transmission connections, a wind farm can be divided into clusters, in which the wind turbine generator systems connected to one booster station can be taken as one cluster, and different clusters connected from booster stations to the farm-level main transformer output the electric power to the grid. Thus, in the proposed strategy, the power tracking characteristic of the wind turbine generator system is modeled as a first-order system to quantify the power tracking error during the power tracking dynamic process, where the power transmission losses from wind turbine generator systems to booster stations are also modeled and considered in the optimization. The proposed strategy is applied to distribute the active power set-point within a cluster while the clusters' set-point still follows the conventional strategy of the wind farm. Simulation results show significant improvement for both optimization targets of the proposed strategy.

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Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss

et al. 2018

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“…In conventional wind farm control strategies, wind farm controller dispatches active and reactive power references to WTs according to their available wind power, which has the advantage of simple implementation. In recent years, the optimization-based control strategies have been developed to improve the control performance [17]. The reduction of fatigue loads is one of the important issues in wind farm control.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Active Power Control of DFIG-Based Wind Farm With Distributed Energy Storage Systems Based on ADMM

Guo

Rong

2020

IEEE Trans. Sustain. Energy

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A hierarchical active power control (HAPC) scheme based on the alternating direction method of multipliers (ADMM) is proposed for doubly-fed induction generator (DFIG)-based wind farms with distributed energy storage systems (ESSs). The wind farm controller optimizes the active power references for DFIG-based wind turbines (WTs) and ESSs inside the wind farm, and the aim is to minimize fatigue loads by minimizing variations of thrust force and shaft torque of WTs while tracking the dispatch command from the transmission system operator (TSO). Moreover, ESSs management is considered in the central controller and WT controllers. The solution method based on the ADMM with fast convergence is used to solve the model predictive control (MPC) optimization problem in a hierarchical manner without loss of optimality. With the ADMM, the control task is distributed to WT controllers, and the computation burden of the central wind farm controller can be efficiently reduced. A wind farm with 30 DFIG WTs was used to validate the control performance of the proposed HAPC scheme.

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“…Nonlinear constraints or additional control variables could be involved in the cost function of the MPC techniques [15]. The proposed MPC strategy in [16] could minimize the voltage variations and fluctuation in reactive power output. In [17], the proposed MPC controller was used to optimize the reactive power distribution in order to maximize the reactive power reserve.…”

Section: Introductionmentioning

confidence: 99%

Leader-Following Diffusion-Based Reactive Power Coordination and Voltage Control of Offshore Wind Farm

Nguyen

Kim

2020

IEEE Access

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This paper proposed a distributed reactive power coordination and voltage control of offshore wind farm based on the leader-following diffusion algorithm. Designating several wind turbine generators (WTGs) as the leaders to receive the information of voltage at point of common coupling (PCC), the reactive power generations required to minimize the voltage deviation could be computed by these leaders. The required reactive power generations are diffused throughout all WTGs by the diffusion algorithm, resulting in the coordinated operation of WTGs to regulate the PCC voltage. The proposed offshore wind farm controller is based on the hierarchical control strategy, which consists of primary and secondary layers. The primary layer is responsible for the inner current, voltage or power regulations whereas the secondary layer is based on the proposed diffusion algorithm to achieve the coordinated operation among WTGs. The proposed strategy could maintain accurate reactive power sharing among WTGs and regulate the PCC voltage. A comparison study with the conventional consensus-based control is presented to show the effectiveness of the proposed diffusion controller. The comparison results show the better performance of the proposed method in terms of dynamic responses of PCC voltage and reactive power coordination. Simulation scenarios of constant wind speed, variable wind speed, and voltage sag in the utility grid are carried out to evaluate the performance of proposed method. The proposed diffusion control is tested either in a small or large offshore wind farm systems. Effect of communication delay on the performance of proposed diffusion control is also described. An experiment of the small-scale wind farm system is conducted to show the feasibility of proposed diffusion strategy. INDEX TERMS Distributed control, diffusion algorithm, voltage control, wind farm control.

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Decentralized Coordinated Voltage Control for VSC-HVDC Connected Wind Farms Based on ADMM

Cited by 66 publications

References 26 publications

Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss

Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss

Hierarchical Active Power Control of DFIG-Based Wind Farm With Distributed Energy Storage Systems Based on ADMM

Leader-Following Diffusion-Based Reactive Power Coordination and Voltage Control of Offshore Wind Farm

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