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

Yao, Qi; Hu, Yang; Chen, Zhe; Liu, Jizhen; Meng, Hongming

doi:10.1049/iet-rpg.2019.0900

Cited by 8 publications

(3 citation statements)

References 23 publications

(41 reference statements)

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“…For faults of a generator, the method based on electrical signals has been proven to be more effective [9]. Most recent work about active power dispatch were proposed to maximize the power output of wind farms [10], to optimize the power-tracking performance [11,12], to alleviate the fatigue of WTs [12], and to balance the fatigue distribution of WFs [10]. However, none take the fault condition of generator into account.…”

Section: Introductionmentioning

confidence: 99%

Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault

Soltani

Hajizadeh

et al. 2021

Energies

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Inter-Turn Short Circuit (ITSC) fault in stator winding is a common fault in Doubly-Fed Induction Generator (DFIG)-based Wind Turbines (WTs). Improper measures in the ITSC fault affect the safety of the faulty WT and the power output of the Wind Farm (WF). This paper combines derating WTs and the power optimization of the WF to diminish the fault effect. At the turbine level, switching the derating strategy and the ITSC Fault Ride-Through (FRT) strategy is adopted to ensure that WTs safely operate under fault. At the farm level, the Particle Swarm Optimization (PSO)-based active power dispatch strategy is used to address proper power references in all of the WTs. The simulation results demonstrate the effectiveness of the proposed method. Switching the derating strategy can increase the power limit of the faulty WT, and the ITSC FRT strategy can ensure that the WT operates without excessive faulty current. The PSO-based power optimization can improve the power of the WF to compensate for the power loss caused by the faulty WT. With the proposed method, the competitiveness and the operational capacity of offshore WFs can be upgraded.

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Section: Introductionmentioning

confidence: 99%

Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault

Soltani

Hajizadeh

et al. 2021

Energies

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“…These agents have an autonomous ability to coordinate with each other. In multi-agent systems, the research on the system's collaboration control has mainly involved tracking [1][2][3][4], formation [5][6][7], swarm [8][9][10], rendezvous [11], distributed filtering [12], and consistency [13,14]. Collaboration consistency elucidates that the state of all agents tends toward the same tendency, and it illustrates the rule of interacting and transmitting information when agents cooperate with other agents; additionally, it describes the process of information exchange between each agent and other agents.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Gou

Deng

2021

Games

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Multi-agent collaboration is greatly important in order to reduce the frequency of errors in message communication and enhance the consistency of exchanging information. This study explores the process of evolutionary decision and stable strategies among multi-agent systems, including followers, leaders, and loners, involved in collaboration based on evolutionary game theory (EGT). The main elements that affected the strategies are discussed, and a 3D evolution model is established. The evolutionary stability strategy (ESS) and stable conditions were analyzed subsequently. Numerical simulation results were obtained through MATLAB simulation, and they manifested that leaders play an important role in exchanging information with other agents, accepting agents’ state information, and sending messages to agents. Then, with the positivity of receiving and feeding back messages for followers, implementing message communication is profitable for the system, and the high positivity can accelerate the exchange of information. At the behavior level, reducing costs can strengthen the punishment of impeding the exchange of information and improve the positivity of collaboration to facilitate the evolutionary convergence toward the ideal state. Finally, the EGT results revealed that the possibility of collaboration between loners and others is improved, and the rewards are increased, thereby promoting the implementation of message communication that encourages leaders to send all messages, improve the feedback positivity of followers, and reduce the hindering degree of loners.

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“…Reference [15] uses the consistency protocol to allocate the reactive power among WTs, which can eliminate the steady state voltage error of WFs and provide a fast response for the system. A novel active power dispatching strategy based on dynamic grouping of WTs is proposed to obtain smoother active power references in [16]. This can enable WTs to track the dispatching instruction and alleviate the fatigue of WTs in order to achieve the reactive power requirements of the power grid and decrease the losses of the WF.…”

Section: Introductionmentioning

confidence: 99%

Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine

Zhou

Rong

Ning³

2021

Energies

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This paper proposes a grouped, reactive power optimization control strategy to maximize the active power output of a doubly-fed induction generator (DFIG) based on a large wind farm (WF). Optimization problems are formulated based on established grouped loss models and the reactive power limits of the wind turbines (WTs). The WTs in the WF are grouped to relieve computational burden. The particle swarm optimization (PSO) algorithm is applied to optimize the distribution of reactive power among groups, and a proportional control strategy is used to distribute the reactive power requirements in each group. Furthermore, the proposed control strategy optimizes the reactive power distribution between the stator and the grid side converter (GSC) in each WT. The proposed control strategy greatly reduces the number of variables for optimization, and increases the calculation speed of the algorithm. Thus, the control strategy can not only increase the active power output of the WF but also enable the WF to track the reactive power dispatching instruction of the power grid. A simulation of the DFIG WF is given to verify the effectiveness of the proposed control strategy at different wind speeds and reactive power references.

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

Cited by 8 publications

References 23 publications

Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault

Wind Farm Power Optimization and Fault Ride-Through under Inter-Turn Short-Circuit Fault

Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine

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