计及EV的综合能源系统双层优化调度策略

doi:10.16180/j.cnki.issn1007-7820.2024.11.012

摘要/Abstract

摘要：

为解决规模化电动汽车入网的优化调度问题,文中提出一种计及电动汽车的综合能源系统双层优化调度策略。上层为优化调度层,电动汽车代理商按照可调度时间将电动汽车分群并将集群信息上传至系统调度中心,系统调度中心协同电动汽车集群和各能源系统,并考虑综合需求响应和阶梯型碳交易机制,以调度成本最小为目标建立经济调度模型。下层为功率分配层,电动汽车代理商以满足用户出行需求为目标构建功率分配模型,引导电动汽车有序参与系统调度。构建仿真算例并采用CPLEX求解器进行求解。仿真结果表明,所提策略不仅能够有效降低综合能源系统调度成本、平滑系统负荷曲线以及减少碳排放量,还能在保障用户出行需求的基础上显著降低用户用电成本,从而实现供需双方的共赢。

关键词: 电动汽车, 综合能源系统, 综合需求响应, 阶梯型碳交易, 有序充放电, 分时电价, 优化调度, V2G

Abstract:

In order to solve the optimal scheduling problem of large-scale electric vehicles into the network, a two-layer optimal scheduling strategy of integrated energy system with electric vehicles is proposed in this study. The upper layer is the optimal dispatching layer, in which electric vehicle agents group electric vehicles into clusters according to the dispatchable time and upload the cluster information to the system dispatching center, which cooperates with electric vehicle clusters and energy systems and builds an economic dispatching model with the goal of minimizing the dispatching cost by considering integrated demand response and ladder-type carbon trading mechanism. The lower layer is the power allocation layer, where electric vehicle agents build a power allocation model with the goal of satisfying users' travel demand, and guide electric vehicles to participate in system scheduling in an orderly manner. The simulation algorithm is constructed and solved by using CPLEX solver. The simulation results show that the proposed strategy can not only effectively reduce the scheduling cost of integrated energy system, smooth the system load curves and reduce carbon emissions, but also significantly reduce the cost of electricity consumption of customers on the basis of securing their travel demand, thus achieving a win-win situation for both supply and demand.

Key words: electric vehicles, integrated energy system, integrated demand response, stepped carbon trading, orderly charging and discharging, time-of-use electricity price, optimal dispatch, V2G

中图分类号:

TP29

邵文锋, 何宇, 温拥军, 聂祥论, 张棠茜, 阚超. 计及EV的综合能源系统双层优化调度策略[J]. 电子科技, 2024, 37(11): 85-94.

SHAO Wenfeng, HE Yu, WEN Yongjun, NIE Xianglun, ZHANG Tangqian, KAN Chao. Bi-Level Optimal Scheduling Strategy of Integrated Energy System Considering EV[J]. Electronic Science and Technology, 2024, 37(11): 85-94.

图/表 24

图1

表1

图2

图3

表2

表3

表4

表5

图4

图5

图6

图7

图8

图9

图10

图11

图12

图 13

表6

表7

表8

图14

图15

图16

参考文献 20

[1]	汪飞, 龚丹丹, 郭慧, 等. 计及动态氢价和不确定性的区域综合能源系统规划—运行两阶段优化[J]. 电力系统保护与控制, 2022, 50(13):53-62.
	Wang Fei, Gong Dandan, Guo Hui, et al. Two-stage optimization of regional integrated energy system planning-operation with dynamic hydrogen pricing and uncertainties[J]. Power System Protection and Control, 2022, 50(13):53-62.
[2]	Bornapour M, Hooshmand R A, Parastegari M. An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC,WT,PV and hydrogen storage units in micro grids[J]. Renewable Energy, 2019, 130(10):1049-1066.
[3]	刘金芝, 张会林, 马立新, 等. 考虑可平移负荷的综合能源系统动态优化调度策略[J]. 电子科技, 2023, 36(4):78-83.
	Liu Jinzhi, Zhang Huilin, Ma Lixin, et al. Dynamic optimal scheduling strategy for integrated energy systems considering shiftable loads[J]. Electronic Science and Technology, 2023, 36(4):78-83.
[4]	邱彬, 宋绍鑫, 王凯, 等. 计及需求响应和阶梯型碳交易机制的区域综合能源系统优化运行[J]. 电力系统及其自动化学报, 2022, 34(5):87-95.
	Qiu Bin, Song Shaoxin, Wang Kai, et al. Optimal operation of regional integrated energy system considering demand response and ladder-type carbon trading mechanism[J]. Proceedings of the CSU-EPSA, 2022, 34(5):87-95.
[5]	宋晓通, 孙艺, 刘欣博, 等. 计及能量互济的多区域综合能源系统多目标双层优化[J]. 高电压技术, 2024, 50(4):1426-1435.
	Song Xiaotong, Sun Yi, Liu Xinbo, et al. Multi-objective bi-level programming strategy of integrated energy system considering regional interconnection[J]. High Voltage Engineering, 2024, 50(4):1426-1435.
[6]	赵鑫, 陈彦奇, 杨正军, 等. 双碳目标下园区综合能源系统长周期多阶段经济规划[J]. 电力系统及其自动化学报, 2023, 35(6):1-12.
	Zhao Xin, Chen Yanqi, Yang Zhengjun, et al. Long-term and multi-stage economic planning of park-level integrated energy system under carbon peaking and carbon neutrality goals[J]. Proceedings of the CSU-EPSA, 2023, 35(6):1-12.
[7]	Jahangir H, Gougheri S S, Vatandoust B, et al. Plugin electric vehicle behavior modeling in energy market:A novel deep learning-based approach with clustering technique[J]. IEEE Transactions on Smart Grid, 2020, 11(6):4738-4748.
[8]	崔杨, 刘柏岩, 赵钰婷, 等. 计及车辆转移机制的含BSS微网联合系统优化调度策略[J]. 高电压技术, 2022, 48(1):366-373.
	Cui Yang, Liu Baiyan, Zhao Yuting, et al. Optimal scheduling strategy for joint system with microgrid containing BSS considering vehicle transfer mechanism[J]. High Voltage Engineering, 2022, 48(1):366-373.
[9]	程杉, 杨堃, 魏昭彬, 等. 计及电价优化和放电节制的电动汽车充电站有序充放电调度[J]. 电力系统保护与控制, 2021, 49(11):1-8.
	Cheng Shan, Yang Kun, Wei Zhaobin, et al. Orderly charging and discharging scheduling of an electric vehicle charging station considering price optimization and discharge behavior control[J]. Power System Protection and Control, 2021, 49(11):1-8.
[10]	蒋成成, 朱健安, 朱成名, 等. V2G模式下的EV建模研究[J]. 电子科技, 2022, 35(2):74-78.
	Jiang Chengcheng, Zhu Jian'an, Zhu Chengming, et al. Research on EV modeling in V2G mode[J]. Electronic Science and Technology, 2022, 35(2):74-78.
[11]	陈奎, 马子龙, 周思宇, 等. 电动汽车两阶段多目标有序充电策略研究[J]. 电力系统保护与控制, 2020, 48(1):65-72.
	Chen Kui, Ma Zilong, Zhou Siyu, et al. Charging control strategy for electric vehicles based on two-stage multi-target optimization[J]. Power System Protection and Control, 2020, 48(1):65-72.
[12]	段俊东, 黄泓叶, 王帅强. 基于弹性优化机制的社区负荷EV分群优化策略[J]. 电子科技, 2022, 35(12):64-71.
	Duan Jundong, Huang Hongye, Wang Shuaiqiang. EV clustering optimization community load strategy based on flexible optimization mechanism[J]. Electronic Science and Technology, 2022, 35(12):64-71.
[13]	李咸善, 周晓岚, 姚俊伟, 等. 考虑车主多模式需求响应模糊意愿的优化调度策略[J]. 电力系统保护与控制, 2023, 51(2):89-101.
	Li Xianshan, Zhou Xiaolan, Yao Junwei, et al. Optimal dispatch strategy considering fuzzy intention of multi-mode demand response of vehicle owners[J]. Power System Protection and Control, 2023, 51(2):89-101.
[14]	李怡然, 张姝, 肖先勇, 等. V2G模式下计及供需两侧需求的电动汽车充放电调度策略[J]. 电力自动化设备, 2021, 41(3):129-135,143.
	Li Yiran, Zhang Shu, Xiao Xianyong, et al. Charging and discharging scheduling strategy of EVs considering demands of supply side and demand side under V2G mode[J]. Electric Power Automation Equipment, 2021, 41(3):129-135,143.
[15]	Zhu Y S, Gao H Y, Xiao J M, et al. Dynamic multi-objective dispatch considering wind power and electric vehicles with probabilistic characteristics[J]. IEEE Access, 2019(7):185634-185653.
[16]	章攀钊, 谢丽蓉, 马瑞真, 等. 考虑电动汽车集群可调度能力的多主体两阶段低碳优化运行策略[J]. 电网技术, 2022, 46(12):4809-4825.
	Zhang Panzhao, Xie Lirong, Ma Ruizhen, et al. Multi-player two-stage low carbon optimal operation strategy considering electric vehicle cluster schedulability[J]. Power System Technology, 2022, 46(12):4809-4825.
[17]	叶波. 计及电动汽车的综合能源系统优化调度策略研究[D]. 北京: 华北电力大学, 2021:35-36.
	Ye Bo. Study on optimal scheduling strategy of integrated energy system considering electric vehicles[D]. Beijing: North China Electric Power University, 2021:35-36.
[18]	贠保记, 张恩硕, 张国, 等. 考虑综合需求响应与“双碳”机制的综合能源系统优化运行[J]. 电力系统保护与控制, 2022, 50(22):11-19.
	Yun Baoji, Zhang Enshuo, Zhang Guo, et al. Optimal operation of an integrated energy system considering integrated demand response and a "dual carbon"mechanism[J]. Power System Protection and Control, 2022, 50(22):11-19.
[19]	胡攀. 计及不确定性的综合能源系统能量优化调度研究[D]. 贵阳: 贵州大学, 2022:26-27.
	Hu Pan. Research on energy optimal scheduling of integrated energy system considering uncertainty[D]. Guiyang: Guizhou University, 2022:26-27.
[20]	孔德政, 张靖, 何宇, 等. 区域综合能源系统IGDT-MPC双层能量优化调度[J]. 电网技术, 2022, 46(10):3970-3979.
	Kong Dezheng, Zhang Jing, He Yu, et al. IGDT-MPC Bi-layer energy optimal scheduling of regional integrated energy system[J]. Power System Technology, 2022, 46(10):3970-3979.

集群	不可调度时段	占比/%
1	7∶00~8∶00,17∶00~18∶00	12
2	7∶00~8∶00,18∶00~19∶00	18
3	7∶00~8∶00,19∶00~20∶00	23
4	8∶00~9∶00,17∶00~18∶00	10
5	8∶00~9∶00,18∶00~19∶00	21
6	8∶00~9∶00,19∶00~20∶00	16

设备	容量/kWh	充能效率	放能效率
蓄电池	1 000	0.95	0.95
蓄热槽	1 000	0.98	0.98

设备	功率上限/kW	功率下限/kW	爬坡限制/kW·h^-1
GT	800	0	160
GB	1 500	0	300
ER	150	0	-
AR	500	0	250
蓄电池	200	-200	200
蓄热槽	200	-200	200

设备	运维成本/元·(kWh)^-1
GT	0.168 50
GB	0.001 80
ER	0.010 40
AR	0.015 60
WT	0.012 60
PV	0.013 29

时段	购电价格/元·(kWh)^-1		售电价格/ 元·(kWh)^-1	购气价格/ 元·m^-3
时段	电网	EV	售电价格/ 元·(kWh)^-1	购气价格/ 元·m^-3
00∶00~07∶00	0.42	—	0.27	3.2
08∶00~11∶00 17∶00~20∶00	1.20	0.90	0.80	3.9
12∶00~16∶00 21∶00~23∶00	0.80	0.78	0.60	3.5