[1]李林锋,钟 鸣,赵浩威,等.考虑运输需求与能源负荷优度耦合的港口自洽新能源系统多场景规划方法[J].长安大学学报(自然科学版),2024,44(5):177-193.[doi:10.19721/j.cnki.1671-8879.2024.05.015]
　LI Lin-feng,ZHONG Ming,ZHAO Hao-wei,et al.A planning method for self-sufficiency renewable energy systems of ports under multiple scenarios considering optimal coordination of waterway transportation demand and energy loading[J].Journal of Chang’an University (Natural Science Edition),2024,44(5):177-193.[doi:10.19721/j.cnki.1671-8879.2024.05.015]
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考虑运输需求与能源负荷优度耦合的港口自洽新能源系统多场景规划方法()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第44卷
期数:
2024年5期
页码:
177-193
栏目:
交通能源融合技术专题
出版日期:
2024-10-10

文章信息/Info

Title:
A planning method for self-sufficiency renewable energy systems of ports under multiple scenarios considering optimal coordination of waterway transportation demand and energy loading
文章编号:
1671-8879(2024)05-0177-17
作者:
李林锋1; 2; 钟 鸣1; 2; 赵浩威1; 2; 马晓凤1; 2; 刘长俭3; 徐先峰4
(1. 武汉理工大学 智能交通系统研究中心,湖北 武汉 430063; 2. 武汉理工大学国家水运安全工程技术研究中心,湖北 武汉 430063; 3. 交通运输部规划研究院,北京 100028; 4. 长安大学 能源与电气工程学院,陕西 西安 710064)
Author(s):
LI Lin-feng1; 2;  ZHONG Ming1; 2;  ZHAO Hao-wei1; 2;  MA Xiao-feng1; 2; LIU Chang-jian3;  XU Xian-feng4
(1. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063,Hubei, China; 2. National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, Hubei, China; 3. Transport Planning and Research Institute,Ministry of Transport, Beijing 100028, China; 4. School of Energy and Electrical Engineering,Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程;  港口运输与能源融合;  多场景规划;  港口自洽新能源系统;  混合整数规划模型
Keywords:
traffic engineering;  ports transportation and energy integration;  multi-scenario planning;  PSRES;  MIPM
分类号:
U653.95
DOI:
10.19721/j.cnki.1671-8879.2024.05.015
文献标志码:
A
摘要:
为了促进港口运输与能源融合发展,合理利用港口有限空间,配置新能源相关基础设施,最大程度实现港口的能源自洽,提出一种考虑运输需求与能源负荷优度耦合的港口自洽新能源系统多场景规划方法。首先,建立港口运输需求和能源负荷优度耦合关系,实现规划期内港口以小时为单位的分时负荷需求预测; 然后,构建考虑系统设备配置和运行优化的双层混合整数规划模型,上层子模型以规划期内总利润最大化为目标,确定新能源设备的配置方案,下层子模型以能源供给可靠性最大化为目标,优化储能设备充放电运行策略; 最后,针对港口接入中国国家电网的强、弱、无供给特征和系统并、离网运行模式以及有、无储能设备所形成的组合场景,应用所构建模型得到相关场景下港口自洽新能源系统规划方案并进行分析。研究表明:在强电网并、离网,弱电网并网和无网条件下,系统投资回报率均为正值,分别为113.89%、69.21%、33.64%和38.68%; 弱电网离网条件下系统投资回报率仅为-10.70%; 强电网并、离网,弱电网并、离网和无网条件下,年平均二氧化碳减排率分别为58.15%、58.59%、62.86%、66.11%和73.26%; 在强电网并网和弱电网并网条件下,不需要配置储能设备,弱电网并网的供电可靠性为96.15%; 在弱电网离网和无网条件下,分别配置9.69、11.20 MW的储能设备,供电可靠性达到100%。
Abstract:
To promote the integrated development of port transportation and energy systems, rationally use limited port space, and configure renewable energy infrastructure to maximize port self-sufficiency rate, a multi-scenario planning method for port self-sufficiency renewable energy systems(PSRESs)was researched which considering the optimal coordination of transportation demand and energy load. The relationship between port transportation demand and energy load was coupled, achieving hourly load demand prediction during the planning period. A two-layer mixed integer planning model(MIPM)was developed, considering system equipment configuration and operation optimization. The upper sub-model aims to maximize total profit over the planning period by determining a “best” configuration scheme of renewable energy equipment, while the lower sub-model focuses on maximizing power supply reliability(PSR)by optimizing the charging and discharging strategies for energy storage equipment. Finally, the MIPM was applied to obtain and analyze the PSRES planning scheme under various scenarios formed by three national power grid(NPG)characteristics(strong, weak, or not available)and two operating modes(on-grid or off-grid)with or without energy storage equipment. The results show that under strong NPG on-grid, strong NPG off-grid, weak NPG on-grid, and not available NPG scenarios, the system return on investment(ROI)is 113.89%, 69.21%, 33.64% and 38.68%, respectively. Under the weak NPG off-grid scenario, the system ROI is only -10.70%. The average annual reduction rate of carbon dioxide emissions under strong NPG on-grid, strongNPG off-grid, weak NPG on-grid, weak NPG off-grid and not available NPG scenarios is 58.15%, 58.59%, 62.86%, 66.11% and 73.26%, respectively. Under strong NPG on-grid and weak NPG on-grid scenarios, there is no need to configure energy storage equipment, and the PSR of the weak NPG on-grid is 96.15%. Under weak NPG off-grid and not available NPG scenarios, the PSR reaches 100% by configuring 9.69 and 11.20 MW of energy storage equipment, respectively.9 tabs, 14 figs, 36 refs.

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备注/Memo

备注/Memo:
收稿日期:2024-08-12
基金项目:国家重点研发计划项目(2021YFB2601300)
作者简介:李林锋(1992-),男,江西瑞昌人,工学博士研究生,E-mail:lilinfeng11@whut.edu.cn。
通讯作者:钟 鸣(1971-),男,内蒙古赤峰人,教授,博士研究生导师,E-mail:mzhong@whut.edu.cn。
更新日期/Last Update: 2024-10-20