![]() ![]() (2022) proposed a disposal strategy for TPB considering electric vehicle charging stations that provide flexible ramping capacity. (2016) developed an integrated day-ahead stochastic scheduling model to dispatch resources and deploy flexible ramping, with demand–response providing the required flexibility. (2019) proposed a methodology to estimate the flexibility of a given day-ahead scheduling model. (2015) modeled the operational flexibility of the day-ahead market, which included flexible resources such as demand–response and energy storage, for managing the variability of renewable energy sources. To explore the possibility of EVs providing flexible ramping products, a novel distribution system locational marginal pricing (LMP) model has been presented ( Zhang et al., 2020). EV charging stations aggregate EVs to provide flexibility, fast response characteristics, and high social and economic benefits ( Neyestani et al., 2015). (2018) devised an integrated stochastic day-ahead dispatching model, which included EV parking lots, bulk energy storage, and demand response, to participate in the flexible ramp market. For example, electric vehicle (EV) charging stations ( Zhang and Kezunovic, 2016), energy storage ( Wang and Hodge, 2017 Khoshjahan et al., 2020), and flexible loads ( Li et al., 2022) can offer flexibility to the power system, which reduces the regulation burden on thermal units. Therefore, the exploration of system flexibility is of great significance for maintaining the secure operation of the power system.Ĭurrently, many scholars have studied offering flexibility to power systems via flexible resources as a way of enhancing system flexibility. The grid has to acquire adequate flexibility to satisfy the stochastic nature of the net load (the output of wind energy resources subtracted from the load) ( Ghaljehei and Khorsand, 2022). However, with the large-scale integration of wind energy resources, the variability and uncertainty of the wind power output seriously affect the secure operation of the system ( Khoshjahan et al., 2019 Park et al., 2022). In response to the growing energy crisis and environmental pollution problems, increasing the share of renewable energy resources has become a roadmap for many nations ( Ding et al., 2022 Han et al., 2022). The analysis results show that the proposed TPB multi-timescale disposal strategy effectively promotes the disposal level of the TPB problem. Finally, the proposed strategy is verified using a modified IEEE 118-bus system. Second, a multi-timescale disposal strategy, which includes an intra-day 4-h plan, an intra-day 1-h plan, and a real-time 15-min plan, is presented by quantifying the flexible demand at different timescales. First, the operation model of an electric vehicle charging station offering flexible ramping capacity is established. Based on the aforementioned characteristics, a TPB multi-timescale disposal strategy for wind-integrated power systems considering electric vehicle (EV) charging stations is established to address the TPB problem at different timescales. The accuracy of wind power and load forecasting increases with a decrease in the forecasting timescale. In this study, the aforementioned problem is defined as the tight power balance (TPB) problem. Once the power supply–demand balance is disrupted, system load shedding and wind spillage become inevitable. High wind power penetration and peak load pose significant challenges to the power system in maintaining the power supply–demand balance. 2College of Energy and Electrical Engineering, Hohai University, Nanjing, China.1China Electric Power Research Institute, Nanjing, China.Shengchun Yang 1, Yifan Chang 2 and Jun Xie 2* ![]()
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