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Impact of Electric Vehicles on the Expansion Planning of Distribution Systems considering Renewable Energy, Storage and Charging Stations

机译:考虑可再生能源,储能和充电站的电动汽车对配电系统扩展规划的影响

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Energy storage systems (ESS) have adopted a new role with the increasing penetration of electric vehicles (EVs) and renewable energy sources (RES). EVs introduce new charging demands that change the traditional demand profiles and RES are characterized by their high variability. This paper presents a new multistage distribution expansion planning model where investments in distribution network assets, RES, ESS and EV charging stations (EVCS) are jointly considered. The charging demand necessary for EVs transportation is performed using a vehicle model based on travel patterns. The variability associated with RES along with the demand requires the incorporation of uncertainty, which is characterized through a set of scenarios. These scenarios are generated by the k-means++ clustering technique that allows keeping the correlation in the information of the uncertainty sources. The resulting stochastic program is driven by the minimization of the present value of the total expected cost including investment, maintenance, production, losses and non-supplied energy. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program, which can be solved by commercial software. Numerical results are presented for an illustrative 54-node test system.
机译:随着电动汽车(EV)和可再生能源(RES)的日益普及,储能系统(ESS)发挥了新的作用。电动汽车引入了新的充电需求,从而改变了传统的需求状况,而RES的特点是其高可变性。本文提出了一种新的多阶段配电扩展计划模型,该模型结合了对配电网络资产,RES,ESS和EV充电站(EVCS)的投资。使用基于行驶模式的车辆模型来执行电动汽车运输所需的充电需求。与RES相关的可变性以及需求需要结合不确定性,这通过一系列方案来表征。这些场景是由k-means ++聚类技术生成的,该技术允许保持不确定性源信息中的相关性。最终的随机程序是由总预期成本的现值(包括投资,维护,生产,损失和未供应的能源)的最小化驱动的。相关的基于场景的确定性等式被公式化为混合整数线性程序,可以通过商业软件来解决。给出了示例性54节点测试系统的数值结果。

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