Energy storage capacity configuration and scheduling optimization strategy for the expressway microgrids

doi:10.3969/j.issn.2097-0706.2025.02.003

Abstract

Abstract:

To improve the utilization of clean energy for highways and achieve the scientific and economical allocation and flexible scheduling optimization of energy storage facilities， an energy storage capacity allocation and scheduling optimization model for highway photovoltaic-storage-charging microgrids is proposed. A novel solution algorithm was used to solve the model and conduct simulation analysis. Based on meteorological information along the highways and load conditions of highway service areas， a mathematical model for the highway photovoltaic-storage-charging microgrids was established. Monte Carlo simulations were conducted to analyze the charging loads of electric vehicles in the service areas. Additionally， based on the load characteristics of highway service areas， management centers， toll stations， and tunnels， a highway microgrid load model was developed. From the perspective of the economic efficiency of highway microgrids， a bi-level optimization model was established to achieve integrated optimization of energy storage system allocation and scheduling. The （Exponential Distribution Optimizer-Mixed-Integer Linear Programming， EDO-MILP） algorithm was applied to solve the model. Taking the distributed photovoltaic-storage demonstration project on the Panzhihua-Dali Expressway （Sichuan section） as an example， simulation and optimization were conducted over a period of 8 760 h. The simulation results showed that for microgrids with a photovoltaic installed capacity of 2 MW and a maximum load of approximately 800 kW， the introduction of 1 131 kW·h/283 kW of energy storage devices led to an annual increase in system revenue of 384 000 yuan， effectively improving the economic efficiency. This was a 42.8% improvement compared to the non-energy storage scheme and a 4.3% improvement over the empirical scheme. Additionally， the allocation scheme increased the microgrid system's consumption capacity for photovoltaic green electricity. Compared to the non-energy storage scheme， the consumption capacity increased by 5.7%， and compared to the traditional scheme， it improved by 3.4%.

Key words: energy integration, bi-level optimization model, exponential distribution algorithm, mixed-integer linear programming algorithm

CLC Number:

TK02：TM732

CHEN Xiaoqi, ZHANG Min, SUN Zhou, LIU Bin, MAO Yong, TAO Yongjin. Energy storage capacity configuration and scheduling optimization strategy for the expressway microgrids[J]. Integrated Intelligent Energy, 2025, 47(2): 29-40.

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场景	用电设施
服务区	监控、通信、照明、供配电、消防、公共服务设施（卫生间、便利店、加油站、餐饮、住宿等）
管理中心	监控、通信、照明、供配电、消防、管理办公楼、住宿区
收费站	监控、通信、照明、供配电、消防
隧道	监控、通信、照明、供配电、消防、通风
桥梁	监控、通信、照明、供配电
道路沿线	监控、通信、照明、供配电

场景	负荷
中坝管理处	57~65
攀枝花南服务区	17~35
太平收费站	30~40
中坝收费站	7~11
半边街隧道	14~15
平洞隧道	9~10
总发隧道	4.5~5.0
中坝隧道	14~15

方案	储能容量	建设成本/万元	年消纳绿电/（MW·h）	年上网收益/万元	年购电成本/万元	综合年费用电费降低/万元
1	无	0.0	997	66.2	44.3	26.9
2	600 kW·h/300 kW	43.2	1 019	65.3	26.2	36.8
3	1 131 kW·h/283 kW	74.6	1 054	63.9	24.2	38.4