考虑插电式电动汽车多种充放电场景的单元承诺

Zhile Yang, Kang Li, Qun Niu, A. Foley
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引用次数: 3

摘要

电动汽车提供了减少化石燃料消耗、减少运输部门温室气体和空气污染物排放的机会。然而,大量插电式电动汽车的采用,由于充电和放电模式的不确定性,对电力系统的运行产生了重大影响。本文在单元承诺问题下,对电动汽车多种充放电场景以及可再生能源并网情况进行了考察和评价。采用量子启发的二元粒子群优化方法确定各单元的开关状态。对比研究表明,非峰充峰放方案是显著降低经济成本和补充可再生能源发电的可行方案。
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Unit commitment considering multiple charging and discharging scenarios of plug-in electric vehicles
Electric vehicles provide an opportunity to reduce fossil fuel consumptions and to decrease the emissions of green-house gas and air pollutants from the transport sector. The adoption of a large number of plug-in electric vehicles however imposes significant impacts on the power system operation due to uncertain charging and discharging patterns. In this paper, multiple charging and discharging scenarios of electric vehicles together with the grid integration of renewable energy sources are examined and evaluated within the unit commitment problem. A quantum-inspired binary particle swarm optimization method is employed to determine the on/off status of each unit. Comparative studies show that the off-peak charging and peak discharging scenario is a viable option to significantly reduce the economic cost and to complement the renewable energy generation.
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Efficient conformal regressors using bagged neural nets Repeated play of the SVM game as a means of adaptive classification Unit commitment considering multiple charging and discharging scenarios of plug-in electric vehicles High-dimensional function approximation using local linear embedding A label compression coding approach through maximizing dependence between features and labels for multi-label classification
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