计及负荷分级和电池退化成本的高速公路服务区交通能源自洽系统柔性优化调度方法

柯吉; 叶培; 王海洋; 刘状壮; 蒋玮; 王飚

doi:10.3963/j.jssn.1674-4861.2024.05.008

计及负荷分级和电池退化成本的高速公路服务区交通能源自洽系统柔性优化调度方法

doi: 10.3963/j.jssn.1674-4861.2024.05.008

柯吉^1,,
叶培¹,
王海洋¹,
刘状壮²,
蒋玮²,
王飚^1, ,

1.
长安大学能源与电气工程学院西安 710000
2.
长安大学公路学院西安 710000

基金项目:

国家重点研发计划项目 2021YFB1600200

详细信息

作者简介:
柯吉（1982—），博士，讲师. 研究方向：交通新型电力系统、综合能源系统优化调度等. E-mail：keji@chd.edu.cn

通讯作者:
王飚（1969—），博士，副教授. 研究方向：交通能源融合、新型电力系统分析与优化等. E-mail：wangbiao@chd.edu.cn

中图分类号: U495
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- 被引次数: 0
出版历程
- 收稿日期: 2024-01-31
- 网络出版日期: 2025-01-22

Flexible Optimal Scheduling of Transportation Energy Self-consumption System for Highway Service Area Based on Load Classification and Degradation Costs of Storage Batteries

1.
School of Energy and Electrical Engineering, Chang'an University, Xi'an 710000, China
2.
Highway School, Chang'an University, Xi'an 710000, China

摘要

摘要: 针对高速公路服务区交通能源自洽系统优化运行，研究了1种综合考虑分级负荷和储能电池退化成本的交通能源自洽系统优化调度模型。根据负荷分级原则对系统负荷进行分级；分析储能电池寿命退化的影响因素，建立了储能电池全寿命退化成本模型；形成了包括系统购电成本、光伏运行和维护成本、储能电池运行成本、负荷调度补偿成本、碳交易成本及储能退化成本的综合成本函数，以其最小为目标函数，并基于可控分级负荷的柔性特征建立了其调度模型与相关约束条件。通过在新疆克拉美丽高速公路服务区交通能源自洽系统考虑电池退化成本、可控分级负荷因素的多场景中进行仿真对比，分析了电池退化成本对系统调度的影响。结果表明：提出的优化模型可以有效缓解高速公路服务区能源自洽系统的用电压力并提升储能电池的使用寿命；通过对可控分级负荷的柔性调控，系统的峰谷负荷差降低17.11%，系统总成本相比于未优化系统总成本降低7.67%。
- 交通能源自洽系统 /
- 高速公路服务区 /
- 柔性优化调度 /
- 负荷分级 /
- 储能退化成本
Abstract: For the optimal operation of the transportation energy self-consumption system in highway service areas, a transportation energy self-consumption system optimal scheduling model with careful consideration of load classification and energy storage degradation cost is proposed. First, the system load is graded according to the load classification principle; the influencing factors of the life degradation of storage batteries are analyzed, and the whole-life storage degradation costs are modeled; a comprehensive cost function including the system power purchase costs, photovoltaic operation, and maintenance costs, storage batteries operation costs, load scheduling compensation costs, carbon trading costs, and storage degradation costs is formed, and the minimum of which is used as the objective function, and based on the controllable flexible characteristics of the classification loads to establish its flexiable optimal scheduling model with relevant constraints. Finally, a multi-scenario simulation is conducted to compare and analyze the traffic energy self-consideration system for the Xinjiang Kelameili highway service area, considering the storage degradation costs and the controllable load classification factors. The results show that the proposed optimization model can effectively alleviate the power consumption pressure of the microgrid system in the highway service area and improve the service life of the energy storage battery; the peak-to-valley load difference of the system can be reduced by 17.11% through the flexible regulation of the controllable load classification, and the total cost of the system can be reduced by 7.67% compared with the total cost of the nominal system.
- transportation energy self-consumption system /
- highway service area /
- flexible optimal scheduling /
- load classification /
- energy storage degradation cost

HTML全文

图 1 磷酸铁锂电池的使用寿命与DOD的关系^[29]

Figure 1. Relationship between service life and DOD of lithium iron phosphate batteries^[29]

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图 2 服务区单日负荷需求、光伏发电量曲线

Figure 2. Service area single day load demand, PV generation curve

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图 3 优化调度前系统的电力负荷分布

Figure 3. Optimization of power load distribution in the pre-dispatch system

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图 4 场景1各能源设备调度情况

Figure 4. Scenario 1 dispatch of each energy equipment

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图 5 场景2各能源设备调度情况

Figure 5. Scenario 2 dispatch of each energy equipment

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图 6 场景1和场景2储能电池的SOC曲线

Figure 6. SOC curves for scenario 1 and scenario 2 energy storage batteries

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图 7 场景3各能源设备调度情况

Figure 7. Scenario 3 dispatch of each energy equipment

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图 8 优化调度后系统的电力负荷分布

Figure 8. Power load distribution in the system after optimal dispatch

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图 9 优化前后系统电力负荷需求曲线

Figure 9. System power load demand curve before and after optimization

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表 1 高速公路服务区负荷分级

Table 1. Load classification of highway service areas

负荷分级	具体负荷
一级负荷	服务区内的消防设施系统、安防设施系统、应急处理系统以及各类监测数据传感器等
二级负荷	污水处理设备、净水处理设备、雷达车辆检测器、智能停车指示诱导屏、服务区内照明系统等
三级负荷	洗衣机、电饭煲、洗碗机、拖地机、空调、热水器、消毒柜等

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表 2 能源设备参数

Table 2. Energy equipment parameters

类型	功率上下限/kW	运行费用/（元/kW）
电网		分时电价
光伏	$ 0 \sim $预测功率值	0.4
储能	$ \pm 50 $	0.5

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表 3 新疆克拉美丽地区的分时电价

Table 3. Time-of-use electricity tariff for the Kelameili, Xinjiang

时段	时间	电价/元
高峰	$ 09: 00-12: 00, 20: 00-24: 00 $	0.603831
平段	$ 00: 00-05: 00, 12: 00-14: 00, $	0.414845
低谷	$ 05: 00-20: 00 $

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表 4 优化调度模型成本系数

Table 4. Optimal scheduling model cost factor

成本系数	价格/（元/kW）	成本系数	价格/（元/kW）
$ K_{\mathrm{PVm}} $	0.20	$ K_{\mathrm{PVo}} $	0.20
$ K_{\mathrm{Batteryo}} $	0.50	$ K_{\mathrm{Tra}} $	0.05
$ K_{\mathrm{Sub}} $	0.15	$ K_{\mathrm{Shi}} $	0.10

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表 5 系统能源设备碳排放系数^[32]

Table 5. Carbon emission factor for system energy equipment^[32]

类型	总碳排放系数$ /(\mathrm{g} /\mathrm{kW}) $	配额系数$ /(\mathrm{g} /\mathrm{kW}) $
电网	1303	798
光伏	154.5	78
储能	91.3	0

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表 6 各个场景优化调度结果

Table 6. Optimal scheduling results for each scenario

场景	运行成本/元	储能电池退化成本/元	总成本/元
1	3684.80		3684.80
2	3689.02	8.68	3697.70
3	3406.19	11.21	3417.40

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