###### Abstract  
Occasionally, wind curtailments may be required to avoid an oversupply when wind power, together with the minimum conventional generation, exceed load. By curtailing wind power, the forecast uncertainty and short-term variations in wind power can be mitigated so that a lower spinning reserve is sufficient to maintain the operational security of a power system. Additionally, the electric vehicle (EV) charging load can relieve the oversupply of wind power generation and avoid uneconomical wind power curtailments. This paper presents a stochastic generation scheduling method to ensure the operation security against wind power variation as well as against forecast uncertainty considering the stochastic EV charging load. In the paper, the short-term variations of wind power that are mitigated by the wind curtailment are investigated, and incorporated into a generation scheduling problem as the mixed-integer program (MIP) forms. Numerical results are also presented in order to demonstrate the effectiveness of the proposed method. wind power; wind power curtailment; electric vehicle; power system uncertainty +
Footnote †: journal: Applied Sciences  
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[PERSON], [PERSON], J.  
that it mitigates wind power uncertainties associated with the short-term variations and the forecasting errors that occur because of the limited operating range of wind generation. In the perspective of day-ahead unit commitment (UC), appropriate wind power curtailments can be one control option [7; 8; 9] for economic operations, which can reduce the requirements for ramping capability as well as spinning reserve. Despite this advantage, uneconomical wind power curtailment, which occurs regardless of uncertainty mitigation, still needs to be reduced as much as possible. An additional demand of electric vehicle (EV) charging load during off-peak hours can help in avoiding uneconomical wind power curtailment [5]. However, unregulated EV charging may not sufficiently impact on relieving the oversupply of wind power generation but can negatively impact the electricity grid by increasing peak demand [10] so that more conventional generators may be required to be turned on. In order to enhance the efficiency of power system operations, wind power curtailment needs to be scheduled by considering the mitigation of wind power uncertainty in a UC procedure while minimizing the uneconomical wind power curtailment by appropriately regulating EV charging load. In recent years, many studies have been conducted to incorporate wind power curtailment into the UC procedures. In [7], wind curtailment is incorporated into the day-ahead UC in the form of decision variables to control the wind power uncertainties. This work has found that an appropriate wind power curtailment can reduce spinning reserve requirements so that wind power generation can be accommodated. In [8], wind power curtailment is modeled as a constant reduction in wind power, and wind farms can provide the spinning reserve using curtailed wind power. In [11], wind power curtailment is used as a control option to meet the balance during uncertain wind scenarios. All the above studies have made significant contributions to incorporating the wind power curtailment into the UC problem. However, these studies have limitations in considering the effects of wind power curtailment on the mitigation of the short-term variation in wind power as well as EV charging load to reduce uneconomical wind power curtailment. Even with these approaches, it may still be required to turn on more peaking generators on a windy night to create faster reserve capacity, even though wind power is significantly curtailed. This paper presents a stochastic UC method that can minimize the generation cost and reserve cost by scheduling the appropriate wind power curtailment incorporating EV charging load.