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| An optimization scheduling method for green power self-contained systems in remote areas of China |
| YANG Zhenchen1, ZHAO Tianyu2, HOU Yongqing3, CHEN Chong2, JIA Limin2,4 |
1. Shanghai Electric Power Co., Ltd, Shanghai 201200;
2. China Institute of Energy and Transportation Integrated Development, North China Electric Power University, Beijing 102206;
3. Beijing Nego Automation Technology Co., Ltd, Beijing 100044;
4. State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing 100044 |
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Abstract To address the issue of optimization in green power self-contained energy systems in remote areas of China, an optimization scheduling method oriented towards economic objectives is proposed, based on weak grids’ varying power supply capabilities. First, energy units such as wind, solar, and energy storage are coupled to construct an energy unit model, and a self-contained system topology and its operation modes are introduced. Then, the optimization objective is set to minimize day-ahead operation costs and daily self-contained rate is taken as the evaluation objective. The Gurobi toolbox is used for optimization. Finally, using measured data from a station on the Qinghai-Tibet Railway and considering diesel price fluctuations and renewable energy output volatility, the operational costs and power generation patterns of energy units in the self-contained system are analyzed and validated across four weak-grid scenarios. The scheduling results under various scenarios shows that as the power supply reliability decreases, both operating costs and system self-contained rate increase. Minor diesel price fluctuations only impact the operational costs under Scenarios 3 and 4, without affecting system self-contained rates across all scenarios. Declines in renewable energy output negatively impact self-contained rates in all four scenarios.
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Received: 28 May 2025
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| Cite this article: |
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YANG Zhenchen,ZHAO Tianyu,HOU Yongqing等. An optimization scheduling method for green power self-contained systems in remote areas of China[J]. Electrical Engineering, 2025, 26(12): 1-8.
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| URL: |
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https://dqjs.cesmedia.cn/EN/Y2025/V26/I12/1
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[1] International Energy Agency.Renewables 2024[EB/OL]. https://www.iea.org/reports/renewables-2024.
[2] 贾利民, 师瑞峰, 马静, 等. 中国陆路交通基础设施资产能源化潜力研究[M]. 北京: 科学出版社, 2020.
[3] 贾利民, 马静, 吉莉, 等. 中国陆路交通能源融合的形态、模式与解决方案[M]. 北京: 科学出版社, 2020.
[4] 师瑞峰, 宁津, 高毓钦, 等. 含氢储能的公路交通风、光自洽微网系统优化调度策略研究[J]. 太阳能学报, 2023, 44(11): 513-521.
[5] LIAO Guangrong, YANG Xiaojuan, LOU Suhua, et al.Multi-objective capacity planning for expressway microgrid considering photovoltaic panel dust removal maintenance[J]. Journal of Physics: Conference Series, 2023, 2588(1): 012003.
[6] 王博, 杨克南, 杨迎春, 等. 基于遗传算法的电动重卡充换电站充电策略优化[J]. 电气技术, 2025, 26(3): 36-41, 48.
[7] 陈艳波, 田昊欣, 刘宇翔, 等. 计及电动汽车需求响应的高速公路服务区光储充鲁棒优化配置[J]. 中国电机工程学报, 2025, 45(5): 1752-1767.
[8] 赵天宇, 贾利民, 任利军. 高速公路典型场景自洽能源系统配置优化[J/OL]. 华北电力大学学报(自然科学版), 1-14(2025-01-24)[2025-04-25]. http://kns.cnki.net/kcms/detail/10.1999.tm.20250123.1741.007.html.
[9] 匡洪海, 徐雨淏, 李子龙, 等. 计及需求响应的海岛微电网双层优化运行[J]. 电气技术, 2025, 26(3): 15-21, 29.
[10] ZHAO Bo, ZHANG Xuesong, CHEN Jian, et al.Operation optimization of standalone microgrids con- sidering lifetime characteristics of battery energy storage system[J]. IEEE Transactions on Sustainable Energy, 2013, 4(4): 934-943.
[11] 林雨眠, 熊厚博, 张笑演, 等. 计及新能源机会约束与虚拟储能的电-热系统分布式多目标优化调度[J]. 电工技术学报, 2024, 39(16): 5042-5059.
[12] 李俊豪, 涂春鸣, 王鑫, 等. 基于“规则+优化”的电气化铁路站点实时能量管控策略[J]. 电工技术学报, 2024, 39(11): 3339-3352.
[13] 高锋阳, 宋志翔, 高建宁, 等. 计及光伏和储能接入的牵引供电系统能量管理策略[J]. 电工技术学报, 2024, 39(3): 745-757. |
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2025, Vol. 26 
