Optimized Operation Strategy of Wind-Solar-Storage Integrated Charging Station Considering Power-to-Hydrogen and Demand Response

doi:10.12096/j.2096-4528.pgt.24090

Abstract

Abstract:

Objectives To meet the charging demands of new energy vehicles and promote the utilization of renewable energy, an optimized operation strategy of a wind-solar-storage integrated charging station, considering power-to-hydrogen conversion and demand response is proposed. Methods Firstly, an optimized model for electricity price at energy charging stations is developed based on the Logistic function response mechanism. This model is then solved using the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ), thereby guiding users to reasonably shift the charging load. Secondly, based on the optimized electricity price and load distribution, and by comprehensively considering energy procurement costs, operational and maintenance expenses, and constraints such as power balance at energy charging stations, an optimized operational model is established for a wind-solar-storage integrated charging station equipped with a power-to-hydrogen conversion device. This model aimed to minimize daily operational costs. Finally, simulation research is conducted on the MATLAB platform. Results Considering the power-to-hydrogen conversion and demand response, the daily operational costs of the charging stations are reduce by 34.74%, and the utilization rates of the wind and solar power increased by 25.84% and 61.60% respectively. Conclusions Through the implementation of power-to-hydrogen conversion and demand response measures, the operational costs of the charging stations can be significantly reduced, and the utilization of wind and solar power can be improved.

Key words: new energy vehicles, wind-solar-storage integrated charging station, power-to-hydrogen, demand response, electricity price, optimized operation, renewable energy consumption, non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)

CLC Number:

TK 01

Lu CUI, Shilin LIU, Wan MIAO, Qing WANG. Optimized Operation Strategy of Wind-Solar-Storage Integrated Charging Station Considering Power-to-Hydrogen and Demand Response[J]. Power Generation Technology, 2025, 46(1): 31-41.

Figures/Tables 16

Fig. 1 Structure of wind-solar-storage integrated charging station

Fig. 2 Optimized operation process

Fig. 3 Demand response mechanism model based onLogistic function

Fig. 4 Electric/hydrogen loads and predicted wind-solar power

Tab. 1 Parameters of traditional peak-valley time-of-use electricity price

11:00—14:00

22:00—23:00

Tab. 2 Operation and maintenance coefficients of equipment

运维系数	参数值
$c P V$ /[元/(kW⋅h)]	0.05
$c W T$ /[元/(kW⋅h)]	0.07
$c E L$ /[元/(kW⋅h)]	0.15
$c E S$ /[元/(kW⋅h)]	0.05
$c H S$ /(元/m³)	0.05

Tab. 2 Operation and maintenance coefficients of equipment

运维系数	参数值
$c P V$ /[元/(kW⋅h)]	0.05
$c W T$ /[元/(kW⋅h)]	0.07
$c E L$ /[元/(kW⋅h)]	0.15
$c E S$ /[元/(kW⋅h)]	0.05
$c H S$ /(元/m³)	0.05

Tab. 3 Parameters of each energy storage device

设备	容量	充放功率上限	容量下限约束/%	容量上限约束/%	充放效率/%
电储	250 kW⋅h	125 kW	20	90	95
氢储	200 m³	100 m³/h	20	90	95

Tab. 4 Time-of-use electricity price of the grid

08:00—10:00;16:00—18:00;

22:00—23:00

0.634 6

峰时段

11:00—15:00

19:00—21:00

0.944 0

Fig. 5 Pareto optimal solution set of charging costs

Fig. 6 Electricity price and load variation curves

Tab. 5 Comparison of user demand response results

情景	负荷波动率	平均电价/[元/(kW⋅h)]	电车用户充电费用/元
1	1.817 0	1.35	1 230.73
2	1.780 0	1.21	1 268.72
3	1.802 8	1.19	1 231.00

Fig. 7 Results of optimized power scheduling in Scenario 1

Fig. 8 Results of optimized power scheduling in Scenario 2

Fig. 9 Results of optimized power scheduling in Scenario 3

Tab. 6 Operational costs of energy charging stations in different scenarios

项目	场景1	场景2	场景3
购电费用	0	562.82	382.23
购氢费用	1 088.66	0	0
设备运维费用	64.22	356.57	370.10
售电收益	1 230.73	1 230.73	1 231.00
售氢收益	1 687.42	1 687.42	1 687.42
日运行成本	1 152.87	919.39	752.33
售能收益	2 918.15	2 918.15	2 918.42

Tab. 7 Wind and solar utilization in different scenarios

项目	场景1	场景2	场景3
风机发电量/(kW⋅h)	940.20	940.20	940.20
弃风量/(kW⋅h)	276.04	53.60	33.10
光伏发电量/(kW⋅h)	1 123.50	1 123.50	1 123.50
弃光量/(kW⋅h)	862.85	334.02	170.77
风电消纳率/%	70.64	94.30	96.48
光伏消纳率/%	23.20	70.27	84.80

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