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Stochastic programming of vehicle to building interactions with uncertainty in PEVs driving for a medium office building

机译:对中型办公楼的电动汽车行驶中具有不确定性的车辆与建筑物之间的相互作用进行随机编程

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The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained with the stochastic formulation of the problem.
机译:电动汽车(EV)的大规模普及将给配电网带来技术挑战,但也为车辆到电网服务带来了潜力。即,如果可用的电动汽车数量足够多,则可以将其用作分布式能源(DER),并且它们的存在会影响微电网中最佳DER投资和调度决策。在这项工作中,在DER-CAM [1]的随机表述中引入了一种新颖的EV车队聚合模型,这是一种用于解决DER投资和调度问题的优化工具。考虑到电动汽车行驶时间表的不确定性,这可用于评估电动汽车互连对最佳DER解决方案的影响。优化结果表明,电动汽车会对DER投资产生重大影响,尤其是考虑到较短的投资回收期时。此外,结果表明,驾驶计划中的不确定性对总能源成本意义不大,这是由问题的随机表述所获得的结果所证实的。

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