Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2022-10-18 DOI:10.1049/stg2.12092
Andrés Felipe Cortés Borray, Kalle Rauma, Esther Torres
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引用次数: 3

Abstract

This study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.

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不平衡低压电网中电动汽车充电与光伏弃电的优化协调:一个实验案例
提出了一种基于二次规划的优化方法来协调不平衡低压电网中电动汽车(EV)充电和光伏(PV)弃电。所提出的模型被定义为一个凸模型,它保证了问题的最优全局解,避免了非线性模型的复杂性,并超越了文献中报道的由元启发式算法导出的局部解的局限性。协调是通过安装在低压馈线头部的中央控制器进行的。所提出的策略的目标是在不超出网络限制的情况下,在每个时间步优化光伏单元的合适设定值和每辆连接的电动汽车的充电率,从而最大限度地减少所有光伏系统的电力损耗,并最大限度地提高向所有电动汽车输送的电力。为了满足所有电动汽车的能量需求,提出了一种新的能量边界模型,该模型基于依赖于车辆到达和期望能量状态的递归函数,以最优地计算其充电轨迹。通过在实验室环境中使用两辆商用电动汽车和一个光伏逆变器的三种场景,成功验证了所提出的协调策略的有效性。
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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
期刊最新文献
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