用于车联网 (V2G) 负载频率控制的高木-菅野模糊增益控制器

Marayati Marsadek , Farrukh Nagi , Navinesshani Permal , Agileswari AP Ramasamy , Aidil Azwin
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引用次数: 0

摘要

随着可再生能源(RES)与电网连接管制的放松,负载频率控制(LFC)变得更加重要。电动汽车(EV)可以以车对网(V2G)模式向电网回馈电力,以保持电网稳定。然而,越来越多的电动汽车进入电网会导致电力系统频率不稳定。如果需要,电动汽车可以利用双向充电器,在充电或并网状态下以 V2G 模式将电力输送回电网,从而恢复电网的频率不稳定性。频率恢复响应时间对于在最短时间内重置电网频率波动以避免关闭电力系统非常重要。本文提出了一种高木-菅野(Takagi-Sugeno,T-S)模糊线性输出控制器,用于双区系统中的 LFC,并采用连接线控制。这项工作将电动汽车电池作为大容量电池储能系统的单体进行建模。电动汽车电池系统为两区电力系统提供辅助电源,使其在负载扰动后重置为稳定状态。T-S 模糊控制器的线性输出依赖于其输入,使其能够对非线性双区电力系统中的负载变化做出有效响应。通过稳定性分析对所提出的控制器参数进行了评估,并通过灵敏度分析对其鲁棒性进行了测试。该控制器与其他模糊控制器进行了比较,结果表明,该控制器具有较快的平稳时间和较低的频率偏差响应。
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Takagi-Sugeno fuzzy gain controller for Vehicle-to-Grid (V2G) load frequency control
Load Frequency Control (LFC) has gained more importance with the introduction of deregulated Renewable Energy Sources (RES) connectivity with the grid. Electrical Vehicles (EVs) can feed electricity back into the grid in Vehicle-to-Grid (V2G) mode to maintain stability. However, the increasing number of EVs penetrating the grid causes frequency instability in the power system. If required, EVs may utilize bi-directional chargers to transfer power back to the grid in the V2G mode while they are charging or in a grid-connected state, restoring the frequency instability of the grid. The frequency restoration response time is important to reset the grid frequency fluctuations in the shortest time possible to avoid shutting down the power system. This paper presents a Takagi-Sugeno (T-S) fuzzy linear output controller for LFC in two-area systems with tie-line control. This work models EV batteries as a single lump of large-capacity battery energy storage systems. The EV's battery system provides ancillary power to the two-area power system to reset it to a steady state after a load disturbance. The T-S fuzzy controller's linear output dependency on its inputs enables it to respond efficiently to load variations in the nonlinear two-area power systems. The proposed controller parameters are evaluated from stability analyses and its robustness is tested with sensitivity analysis. It is compared with other fuzzy controllers, and it demonstrates a fast-settling time and reduced frequency deviation response.
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