考虑补偿激励的电动汽车多区域优化调度策略

doi:10.16183/j.cnki.jsjtu.2022.348

摘要/Abstract

摘要：

针对充电区域内分布式新能源(DRE)与电动汽车负荷供需不均的问题,提出一种考虑补偿激励的电动汽车多区域优化调度策略,引导电动汽车前往不同充电区域充电,以促进DRE就地消纳.首先,基于需求价格弹性及用户时间焦虑建立电动汽车用户需求电量模型.其次,基于剩余电量可达原则和空闲时间冗余原则将电动汽车划分为可响应和不可响应集群,利用基于后悔理论的充电区域决策模型对可响应集群按区域作进一步划分.最后,建立电动汽车多区域优化调度模型,从最大化充电服务商经济效益及DRE消纳程度两个方面对充电价格进行优化.通过仿真验证证明所提优化策略能够充分考虑时间焦虑和价格弹性对电动汽车用户的影响,充分挖掘用户的响应潜力,在降低DRE消纳偏差量和提高充电服务商经济效益方面具有明显效果.

关键词: 电动汽车, 分布式新能源, 充电补偿, 时间焦虑

Abstract:

Aimed at the problem of uneven supply and distributed renewable energy (DRE) in charging regions and electric vehicle (EV) loads, a multi-region optimal scheduling strategy for EVs considering compensation incentives is proposed to guide EVs to choose different charging regions, so as to promote local consumption of distributed energy. First, an EV charging response model is established based on the price elasticity of demand and users’ time anxiety. Then, based on the principle of remaining power availability and idle time redundancy, EVs are divided into responsive cluster and non-responsive cluster. A charging area decision model based on regret theory is used to further divide the responsive cluster by region. Finally, a multi-region optimal scheduling model for EVs is established, and the charging price is optimized in terms of maximizing the economic benefits of charging service providers and the consumption of DRE. Simulation cases show that the proposed optimization strategy can fully consider the impact of time anxiety and price elasticity on EV users, fully tap the users’ response potential, and has obvious effects in reducing the deviation of distributed new energy consumption and improving the economic benefits of charging service providers.

Key words: electric vehicle (EV), distributed renewable energy (DRE), charging compensation, time anxiety

中图分类号:

TM732

孙毅, 葛明洋, 王献春, 鲍荟谕, 杨泓玥, 姚陶. 考虑补偿激励的电动汽车多区域优化调度策略[J]. 上海交通大学学报, 2024, 58(5): 636-646.

SUN Yi, GE Mingyang, WANG Xianchun, BAO Huiyu, YANG Hongyue, YAO Tao. Multi-Region Optimal Scheduling Strategy for Electric Vehicles Considering Compensation Incentives[J]. Journal of Shanghai Jiao Tong University, 2024, 58(5): 636-646.

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EV位置信息	距离区域1的路程/km	距离区域2的路程/km	距离区域3的路程/km
靠近区域1	2~4	4~6	6~8
靠近区域2	4~6	2~4	4~6
靠近区域3	6~8	4~6	2~4

时段	外购电价	DRE电价	充电单价
峰 8:00—12:00 17:00—21:00	0.65	0.45	1.082
平 12:00—17:00 21:00—24:00	0.40	0.30	0.649
谷 0:00-8:00	0.30	0.22	0.316

调度策略	服务商收益/ 万元	DRE消纳偏差	用户单位充电成本/元
对比策略1	1.3976	60.54	0.8704
对比策略2	1.4003	35.68	0.8536
对比策略3	1.4334	24.46	0.8246
对比策略4	1.4218	31.57	0.8378
本文策略	1.5387	20.76	0.8084

EV编号	策略	时间后悔值			价格后悔值			总后悔值			决策结果
EV编号	策略	区域1	区域2	区域3	区域1	区域2	区域3	区域1	区域2	区域3	决策结果
1	对比策略4	1.53	0.89	0.00	0.00	1.50	3.18	0.00	0.86	1.65	1
1	本文策略	1.53	0.89	0.00	0.00	1.77	3.66	0.00	1.13	2.13	1
6	对比策略4	1.91	1.20	0.00	0.00	0.92	1.28	0.63	0.84	0.00	3
6	本文策略	1.91	1.20	0.00	0.00	1.02	1.71	0.20	0.51	0.00	3
7	对比策略4	1.58	0.88	0.00	0.00	0.97	1.27	0.31	0.58	0.00	3
7	本文策略	1.58	0.88	0.00	0.00	1.53	3.21	0.00	0.83	1.63	1
15	对比策略4	1.12	0.56	0.00	0.00	0.73	0.91	0.21	0.38	0.00	3
15	本文策略	1.12	0.56	0.00	0.00	1.13	2.57	0.00	0.57	1.45	1

EV 数量	调度策略	充电服务商收益/万元	消纳偏差	用户单位充电成本/元
1倍	对比策略3	1.4274	25.16	0.8198
1倍	对比策略4	1.4178	30.27	0.8343
1倍	本文策略	1.5167	21.36	0.8041
1.25倍	对比策略3	1.6629	26.79	0.8218
1.25倍	对比策略4	1.6332	31.36	0.8378
1.25倍	本文策略	1.7976	22.08	0.8112
1.5倍	对比策略3	1.9175	35.32	0.8234
1.5倍	对比策略4	1.8654	41.78	0.8402
1.5倍	本文策略	1.9821	32.45	0.8175