Reactive power compensation using electric vehicles considering drivers’ reasons
Reactive power compensation using electric vehicles considering drivers’ reasons
复制标题
DOI：
10.1049/iet-gtd.2017.1114
复制
发表时间：
2018-01
影响因子：
2.5
通讯作者：
S. Su;Yong Hu;Shidan Wang;Wen Wang;Y. Ota;K. Yamashita;M. Xia;X. Nie;Lijiang Chen;Xia Mao
中科院分区：
文献类型：
--
作者：
S. Su;Yong Hu;Shidan Wang;Wen Wang;Y. Ota;K. Yamashita;M. Xia;X. Nie;Lijiang Chen;Xia Mao
随着电动汽车 (EV) 充电负载在配电网络中扩散，节点电压分布更有可能受到破坏。由于电动汽车充电负载在空间上的随机性，不同地点更灵活的无功功率补偿变得非常重要。然而，传统的无功补偿设备在空间上不具有灵活性。因此，考虑驾驶员原因，提出了两种使用电动汽车的无功补偿策略。驾驶员的原因包括充电需求、充电机会损失（时间）和利润。策略1中，电动汽车充电机在完成非稳压充电后，对无功功率进行充分补偿。因此，驾驶员的充电行为完全不受影响。在策略2中，电动汽车充电器的运行功率因数被视为优化变量。运行功率因数约束是通过分析驾驶员的充电需求和充电机会损失（时间）得出的。然后，为了激励驾驶员，引入了基于量化每个驾驶员对电压的贡献的激励方法。案例研究表明，策略 1 在电压偏差不显着的节点上表现良好，对驱动器的充电行为没有任何限制，而策略 2 在电压偏差显着的节点上表现良好。
The node voltage profile is more likely to be violated as the electric vehicles (EVs) charging load spreads in distribution network. Due to the stochastic nature of EV charging load spatially, more flexible reactive power compensation in different locations becomes important. However, the conventional reactive power compensation equipment has no flexibility spatially. Therefore, two kinds of reactive power compensation strategies using EVs considering drivers' reasons are proposed. Drivers' reasons contain charging demand, charging opportunity loss (time) and profit. In Strategy 1, EV chargers are used to fully compensate reactive power after finishing the unregulated charging. Thus, drivers' charging behaviour is not influenced at all. In Strategy 2, the operating power factors of EV chargers are treated as variables for the optimisation. The constraint of operating power factors is derived from analysing the charging demand and the charging opportunity loss (time) for drivers. Then, in order to motivate drivers, an incentive method is introduced based on the quantification of each driver's contribution to the voltage. The case study shows that Strategy 1 performs well at nodes having the non-significant voltage deviation without any constraint on driver's charging behaviour, while Strategy 2 performs well at nodes where the voltages deviation is significant.