考虑电动汽车聚合调控的配电网储能优化配置

doi:10.19799/j.cnki.2095-4239.2023.0310

摘要/Abstract

摘要：

灵活负荷如电动汽车的调控是增强电网运行灵活性的新兴手段，然而在储能规划阶段常被忽视。对此，本文提出考虑电动汽车聚合调控的配电网储能优化配置方法。首先，计及抵达时间、离开时间和期望电量等特征参数刻画单个电动汽车的运行域，进而基于电动汽车闵可夫斯基和得到充电站的二阶近似实用模型，用于刻画电动汽车聚合调控特性；然后，建立采用支路虚拟电阻表征充放电损耗的储能运行模型；进一步，提出基于K-Medoids场景生成算法与Benders分解算法的储能规划-运行两阶段随机优化方法。最后，算例以改进IEEE-33节点配电系统为例进行分析，结果表明电动汽车可控比例升高，储能配置的总容量会随之增大，碳排放量会显著减少，光伏利用率会明显提高。

关键词: 储能配置, 电动汽车, 聚合调控, 两阶段随机优化

Abstract:

The regulation of flexible loads, such as electric vehicles, is an emerging means of enhancing the power grid operation flexibility; however, it is often overlooked in the energy storage planning stage. Therefore, this article proposes an optimized configuration method for energy storage in distribution networks that considers the aggregation regulation of electric vehicles. First, the operation domain of a single electric vehicle was characterized by taking into account the arrival time, departure time, expected electricity, and other characteristic parameters. Then, a second-order approximate practical model of the charging station was obtained based on the Hermann-Minkowski sum of electric vehicles, which was used to characterize the aggregation regulation characteristics of electric vehicles. An energy storage operation model that used branch virtual resistors to characterize charging and discharging losses was established. Furthermore, a two-stage stochastic optimization method for energy storage planning operation was proposed based on the K-Medoids scene generation and Bender's decomposition algorithms. The results based on the improved IEEE-33 node distribution system showed that as the controllable proportion of electric vehicles increased, the total capacity of energy storage configuration would increase, carbon emissions be significantly reduced, and photovoltaic utilization efficiency be significantly improved.

Key words: energy storage configuration, electric vehicles, aggregation control, two-stage stochastic optimization

中图分类号:

TM 73

罗世刚, 滕婕, 谭庄熙. 考虑电动汽车聚合调控的配电网储能优化配置[J]. 储能科学与技术, 2023, 12(11): 3395-3405.

Shigang LUO, Jie TENG, Zhuangxi TAN. Optimal allocation of energy storage in distribution network considering aggregate regulation of electric vehicles[J]. Energy Storage Science and Technology, 2023, 12(11): 3395-3405.

图/表 14

图1

图2

图3

图4

图5

图6

图7

表1

各电源的CO2 当量值"

电源类型	$t C O 2 e q / M W h$
光伏	0.01
上级主网(视为火电)	0.82

表1

图8

表2

图9

图10

图11

图12

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储能建设位置	变流器容量/MW	电池容量/MWh
16	0.56	2.25
21	0.83	3.32
31	0	0

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