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    Coordinated Control of Electric Vehicles and Renewable Energy Sources for Frequency Regulation in Microgrids
    (2020-01-01)
    Jampeethong, Phoompat
    ;
    Khomfoi, Surin
    A Control technique of electric vehicles (EVs) cooperating with ac microgrids is considered as an important role with integration of renewable energy sources (RES), i.e. wind and solar farms. As known, the intermittent power generations of these RESs can provide significant changes of the frequency in microgrids. Consequently, outputs of these generations are regarded as continuous disturbances. Previously, the ability to permit frequency stabilizing effect was usually neglected in microgrid design; thereupon, the performance of controller may be ineffective to regulate the frequency in such a microgrid. To address this problem, a new coordination of EV, wind farm (WF), and photovoltaic (PV) for microgrid frequency regulation is proposed in this article. In the control design, the proposed adaptive PI controller is developed by using practical proportional integral (PI) controllers. An effect of a small delay is also considered in input-output pairs of the adaptive PI controllers. Simulation model is developed for validating the proposed controller. Simulation results demonstrate that the proposed coordinated control technique of EVs, WF, and PV power generation provides a better frequency regulation performance than a fixed PI controller under various uncertainties such as wind and solar power fluctuations, N-1 outages, disconnection of RESs, load variations, and the number of EVs.
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    Optimal fuzzy logic-based adaptive controller equipped with DFIG wind turbine for frequency control in stand alone power system
    (2013-12-01)
    Sa-Ngawong, Nattapol
    ;
    Ngamroo, Issarachai
    This paper deals with an adaptive controller design by an optimal fuzzy logic of doubly fed induction generator (DFIG) wind turbine for frequency control in the stand alone power system. Since the DFIG wind turbine has the ability of active power control, this makes the possibility of system frequency control contribution by DFIG. The optimal fuzzy logic adapts the control parameters of the supplement controller equipped with the DFIG wind turbine so that the active power output can be controlled to alleviate the frequency deviation due to load changes. In the fuzzy logic design, the membership function and the control rules are automatically optimized by the particle swarm optimization. Simulation study confirms that the control effect and robustness of the proposed adaptive controller is superior to that of the conventional controller with fixed parameters against various random load changes and system parameters variation. © 2013 IEEE.