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Joint expansion planning of distribution networks, EV charging stations and wind power generation under uncertainty

机译:不确定条件下的配电网,电动汽车充电站和风力发电联合扩张计划

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This paper describes the consideration of uncertainty in distribution system expansion planning (DSEP) including electric vehicles (EV) and the possibility of joint investment in EV charging stations (EVCS) and wind power generators. The charging demand necessary for EVs transportation is performed using a vehicle decision model based on travel patterns. Several alternatives are available for the installation of EVCS, feeders, transformers and wind power generators. Consequently, the optimal expansion plan selects the best alternative and location for the candidate assets considering uncertainty associated to demand, wind speed and EV charging demand. The uncertainty is characterized through a set of scenarios that explicitly capture the correlation between the uncertain sources. The problem is defined as a stochastic-programming-based model driven by the minimization of the annualized investment, maintenance, production, losses and non-supplied energy costs. The resulting associated scenario-based deterministic is formulated as a mixed-integer linear program for which infinite convergence to optimality is guaranteed. A 24-bus system case study is provided illustrating the results of the proposed approach.
机译:本文介绍了对包括电动汽车(EV)在内的配电系统扩展计划(DSEP)中不确定性的考虑,以及对EV充电站(EVCS)和风力发电机进行联合投资的可能性。使用基于行驶模式的车辆决策模型来执行电动汽车运输所需的充电需求。 EVCS,馈线,变压器和风力发电机的安装有几种选择。因此,考虑到与需求,风速和电动汽车充电需求相关的不确定性,最佳扩张计划为候选资产选择最佳替代方案和位置。不确定性的特征是通过一组场景来明确捕获不确定性源之间的相关性。该问题被定义为一种基于随机程序的模型,该模型由最小化年度投资,维护,生产,损失和未提供的能源成本驱动。结果相关联的基于场景的确定性公式化为混合整数线性程序,可确保对其进行无限收敛。提供了一个24总线系统案例研究,说明了所提出方法的结果。

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