Simulation Studies of Reconfigurable Communication Network for Southwest Offshore Wind Farm South Korea

Hussain, Shahid; Kim, Young-Chon; Jan, Qasim; Ali, Zakir

doi:10.1109/c-code.2019.8681006

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…16 need to be performed. Since the communication technology represented by Ethernet communication is applied in the control of WFs [25], the command sending and receiving time can generally be controlled within 10 ms [26]. This meets the time requirements of fault ride-through operation.…”

Section: ⅳ Cooperative Control For Multi-paralleled Dfig Wind Farmsmentioning

confidence: 94%

Dynamic Coupling and Cooperative Control for Multi-Paralleled Doubly Fed Induction Generator Wind Farms During Symmetrical Low Voltage Ride-Through in a Weak Grid

Guan,

Yao

2024

Prot. Control Mod. Power Syst.

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In multi-fed grid-connected systems, there are complex dynamic interactions between different pieces of equipment. Particularly in situations of weak-grid faults, the dynamic coupling between equipment becomes more pronounced. This may cause the system to experience small-signal instability during the fault steady-state. In this paper, multi-paralleled doubly fed induction generator (DFIG)-based wind farms (WFs) are taken as an example to study the dynamic coupling within a multi-fed system during fault steady-state of symmetrical low voltage ride-through (LVRT) in a weak grid. The analysis reveals that the dynamic coupling between WFs will introduce a damping shift to each WF. This inevitably affects the system's dynamic stability and brings the risk of small-signal instability during fault steady-state in LVRT scenarios. Increasing the distance to fault location and fault severity will exacerbate the dynamic coupling between WFs. Because of the dynamic coupling, adjusting the control state of one WF will affect the stability of the remaining WFs in the system. Hence, a cooperative control strategy for multi-paralleled DFIG WFs is proposed to improve dynamic stability during LVRT. The analysis and the effectiveness of the proposed control strategy are verified by modal analysis and simulation.

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Section: ⅳ Cooperative Control For Multi-paralleled Dfig Wind Farmsmentioning

confidence: 94%

Dynamic Coupling and Cooperative Control for Multi-Paralleled Doubly Fed Induction Generator Wind Farms During Symmetrical Low Voltage Ride-Through in a Weak Grid

Guan,

Yao

2024

Prot. Control Mod. Power Syst.

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“…The proposed charging cost optimization algorithm (CCOA) considered various factors such as driving habits (i.e., arrival and departure times), battery characteristics (i.e., SoC and battery capacity), and real-time electricity market price pattern along with a proper communication network system [12][13][14]. An EV initiates a charging request after being plugged into the charging station.…”

Section: Introductionmentioning

confidence: 99%

A Heuristic Charging Cost Optimization Algorithm for Residential Charging of Electric Vehicles

et al. 2022

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The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charging costs. Besides, the random nature of EV users restricts them from following fixed charging times. Consequently, the real-time pricing scenarios are natural and can support optimizing the charging load and cost for EV users. This paper aims to develop charging cost optimization algorithm (CCOA) for residential charging of EVs. The proposed CCOA coordinates the charging of EVs by heuristically learning the real-time price pattern and the EV’s information, such as the battery size, current state-of-charge, and arrival & departure times. In contrast to the holistic price, the CCOA determines a threshold price value for each arrival and departure sequence of EVs and accordingly coordinates the charging process with optimizing the cost at each scheduling period. The charging cost is captured at the end of each charging activity and the cumulative cost is calculated until the battery’s desired capacity. Various charging scenarios for individual and aggregated EVs with random arrival sequences of EVs against the real-time price pattern are simulated through MATLAB. The simulation results show that the proposed algorithm outperforms with a low charging cost while avoiding the overloading of the grid compared to the conventional uncoordinated, flat-rate, and time-of-use systems.

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Simulation Studies of Reconfigurable Communication Network for Southwest Offshore Wind Farm South Korea

Cited by 2 publications

References 11 publications

Dynamic Coupling and Cooperative Control for Multi-Paralleled Doubly Fed Induction Generator Wind Farms During Symmetrical Low Voltage Ride-Through in a Weak Grid

Dynamic Coupling and Cooperative Control for Multi-Paralleled Doubly Fed Induction Generator Wind Farms During Symmetrical Low Voltage Ride-Through in a Weak Grid

A Heuristic Charging Cost Optimization Algorithm for Residential Charging of Electric Vehicles

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