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Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks.

机译:低压配电网中插电式电动汽车的多目标优化控制。

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摘要

The massive introduction of plug-in electric vehicles (PEVs) into low voltage (LV) distribution networkswill lead to several problems, such as: increase of energy losses, decrease of distribution transformer lifetime, lines and transformer overload issues, voltage drops and unbalances. In this context, this paper proposes a new multi-objective optimization algorithm in order to reduce the mentioned problems. At thesame time, users’ interests in terms of charging cost and privacy have been taken into account. The proposed multi-objective optimization is based on minimizing the load variance and charging costs by using the weighted sum method and fuzzy control. The use of vehicle to grid (V2G) concept and load forecast uncertainties have been also considered. Furthermore, an innovative method for mitigating voltage unbalances has been developed. The effectiveness of this methodology has been tested using real data of a LV distribution network, located in Borup (Denmark). Simulation results show that this approachcan reduce both energy losses and charging costs as well as it allows a high PEV penetration rates(PEV-PR).
机译:将插电式电动汽车(PEV)大量引入低压(LV)配电网络将导致若干问题,例如:能量损失增加,配电变压器寿命缩短,线路和变压器过载问题,电压降和不平衡。在这种情况下,本文提出了一种新的多目标优化算法,以减少上述问题。同时,考虑了用户在收费和隐私方面的利益。所提出的多目标优化是基于使用加权和方法和模糊控制来最小化负载变化和充电成本的。还考虑了车辆到电网(V2G)概念的使用和负荷预测的不确定性。此外,已经开发了减轻电压不平衡的创新方法。已使用位于Borup(丹麦)的LV分销网络的真实数据测试了此方法的有效性。仿真结果表明,该方法可以减少能量损失和充电成本,并且可以实现较高的PEV渗透率(PEV-PR)。

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