| 引用本文: | 李昊,黄文焘,余墨多,王杰,樊飞龙,邰能灵.海上风电场充电平台与电动化航运协同规划方法[J].电力自动化设备,2025,45(12):41-48. |
| LI Hao,HUANG Wentao,YU Moduo,WANG Jie,FAN Feilong,TAI Nengling.Collaborative planning method of offshore wind farm charging platforms and electrified shipping[J].Electric Power Automation Equipment,2025,45(12):41-48. |
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| 海上风电场充电平台与电动化航运协同规划方法 |
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李昊1,2, 黄文焘2,3, 余墨多2,3, 王杰1,2, 樊飞龙1,2, 邰能灵1,2
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1.上海交通大学 国家电投智慧能源创新学院，上海 200240;2.上海交通大学 电力传输与功率变换控制教育部重点实验室，上海 200240;3.上海交通大学 电气工程学院，上海 200240
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| 摘要: |
| 海上风电通过配储可提供一定的灵活性支撑，但同时面临利用率低的困境，亟需探索新的利用模式以最大化发挥储能与海上风电的协同效应。考虑海运电气化、海上风电、储能的时空耦合特性，提出以海上风电场作为电动船舶海上补能节点的充电平台-电动化航运协同规划方法。考虑新能源出力与海况的不确定性，建立大流量电动化航运海上充电鲁棒优化模型，并采用嵌套列和约束生成算法迭代求解海上储能与充电平台的最优容量配置。以中国东南沿海海上风电场为对象，基于船舶自动识别系统数据进行案例分析。结果表明：基于海上风电场作为充电节点为电动船舶进行海上补能，可有效降低船载带电量，增加运载空间；海上风电场较低的度电成本可降低船舶补能成本，同时提升海上新能源消纳水平，二者具有显著的协同效应。 |
| 关键词: 海上风电场 电动船舶 海上充电平台 协同规划 嵌套列和约束生成算法 |
| DOI：10.16081/j.epae.202510024 |
| 分类号:TK89;TM614 |
| 基金项目:国家重点研发计划项目(2024YFE0209800,2024YFB4206500) |
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| Collaborative planning method of offshore wind farm charging platforms and electrified shipping |
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LI Hao1,2, HUANG Wentao2,3, YU Moduo2,3, WANG Jie1,2, FAN Feilong1,2, TAI Nengling1,2
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1.College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China;2.Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China;3.School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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| Abstract: |
| Offshore wind power can provide certain flexibility support by configuring energy storage, but it also faces the challenge of low utilization rate. So it is urgent to explore new utilization modes to maximize the collaborative effect of energy storage and offshore wind power. Considering the spatio-temporal coupling characteristics of maritime electrification, offshore wind power and energy storage, a collaborative planning method of charging platforms and electrified shipping is proposed, with offshore wind farms serving as the marine energy replenishment nodes for electric ships. Considering the uncertainty of renewable energy output and sea condition, a robust optimization model for large-flow electrified shipping offshore charging is established. A nested column and constraint generation algorithm is applied to iteratively solve the optimal capacity configuration of offshore energy storage and charging platforms. Taking an offshore wind farm in the southeast coast of China as the object, a case study is conducted based on the data from the automatic identification system of ships. The results show that taking offshore wind farms as the charging nodes for electric ships can effectively reduce the onboard battery capacity and increase the cargo space. The relatively lower cost of offshore wind power can reduce the energy replenishment cost of ships and simultaneously enhance the consumption level of offshore renewable energy. The two systems have a significant collaborative effect. |
| Key words: offshore wind farm electric ship offshore charging platforms collaborative planning nested column and constraint generation algorithm |
