含高比例风光接入的输电网氢-电混合储能系统配置方法

doi:10.12204/j.issn.1000-7229.2022.11.009

电力建设 ›› 2022, Vol. 43 ›› Issue (11): 85-98.doi: 10.12204/j.issn.1000-7229.2022.11.009

• 新型电力系统背景下储能系统规划配置与运行控制·栏目主持李相俊教授级高工、帅智康教授、颜宁副教授· • 上一篇下一篇

含高比例风光接入的输电网氢-电混合储能系统配置方法

陈颖¹(), 石永富¹(), 钟鸿鸣²(), 王湘²(), 雷霞²(), 尹洪全¹(), 刘鑫¹()

1.国网内蒙古东部电力有限公司,呼和浩特市 010010
2.西华大学电气与电子信息学院,成都市 610039

收稿日期:2022-04-18 出版日期:2022-11-01 发布日期:2022-11-03
通讯作者: 雷霞 E-mail:604439278@qq.com;tl_shiyf@163.com;383182742@qq.com;xiangwang@xhu.mail.edu.cn;snow_lei246@mail.xhu.edu.cn;yinhongquan@md.sgcc.com.cn;liuxin@md.sgcc.com.cn
作者简介:陈颖(1988),女,硕士,从事电力市场模式下发电计划管理方面的研究工作,E-mail: 604439278@qq.com;
石永富(1973),男,本科,从事电网调度计划管理方面的研究工作,E-mail: tl_shiyf@163.com;
钟鸿鸣(1995),男,硕士研究生,主要研究方向为电力系统及其自动化,Email: 383182742@qq.com;
王湘(1988),男,博士,讲师,主要研究方向为电动汽车并网及新型电力系统,E-mail: xiangwang@xhu.mail.edu.cn;
尹洪全(1986), 男,硕士,高级工程师,从事调度运行管理方面的工作,E-mail: yinhongquan@md.sgcc.com.cn;
刘鑫(1983), 男,硕士,高级工程师,从事电网运行及稳定管理方面的工作,E-mail: liuxin@md.sgcc.com.cn。
基金资助:
国家自然科学基金项目资助(51877181);国家电网公司科技项目“含高比例可再生能源接入的源网荷储协同调度技术研究”(52660021000Q)

Configuration Method for Hydrogen-Electricity Hybrid Energy Storage System in Transmission Grid with High Proportion of PV and Wind Power Connection

CHEN Ying¹(), SHI Yongfu¹(), ZHONG Hongming²(), WANG Xiang²(), LEI Xia²(), YIN Hongquan¹(), LIU Xin¹()

1. State Grid East Inner Mongolia Electric Power Company Limited, Hohhot 010010, China
2. School of Electric Engineering and Electronic Information, Xihua University, Chengdu 610039, China

Received:2022-04-18 Online:2022-11-01 Published:2022-11-03
Contact: LEI Xia E-mail:604439278@qq.com;tl_shiyf@163.com;383182742@qq.com;xiangwang@xhu.mail.edu.cn;snow_lei246@mail.xhu.edu.cn;yinhongquan@md.sgcc.com.cn;liuxin@md.sgcc.com.cn
Supported by:
National Natural Science Foundation of China(51877181);State Grid Corporation of China Research Program(52660021000Q)

摘要/Abstract

摘要：

目前高比例风光接入的输电网存在弃风弃光率普遍较高的问题,配置储能设备作为一种具有潜在效用的手段在当前的研究中备受青睐。针对输电网储能配置问题,为达到综合成本减小和弃风弃光率降低的目的,提出了一种基于双层规划模型的输电网氢-电混合储能系统配置方法。首先,对氢-电混合储能系统的特性进行建模,在此基础上建立输电网氢-电混合储能系统功率与容量配置双层规划模型。上层模型以配置储能后年综合成本最小为目标;下层模型以弃风弃光率最小为目标。其后基于蓄电池和氢储能的不同特性,提出一种氢-电混合储能系统配合策略。最后,针对该模型非线性多目标的特点,采用双层迭代粒子群算法与潮流计算相结合进行模型求解。在算例仿真部分,以某含有高比例风光接入地区输电网为例,进行氢-电混合储能系统容量和选址的优化配置,验证了所建模型和所提求解算法的可行性和有效性。提高了风电光伏出力在时序上的转移能力,减少了高碳化石能源的消耗量,降低了弃风弃光率。

关键词: 输电网, 高比例风光接入, 优化配置, 氢-电混合储能系统, 双层规划模型

Abstract:

At present, the transmission grid with a high proportion of photovoltaic and wind power has a generally high rate of curtailment of wind and solar power. As a potential utility, the configuration of energy storage equipment is favored in current research. Aiming at the problem of energy storage configuration in the transmission network, this paper proposes a configuration method based on a two-layer programming model for the hydrogen-electric hybrid energy storage system in order to reduce the comprehensive cost and the curtailment rate of wind and solar energy. Firstly, the characteristics of the hydrogen-electricity hybrid energy storage system are modeled, and on this basis, a two-layer planning model for the power and capacity allocation of the hydrogen-electricity hybrid energy storage system in the transmission network is established. The upper-layer model aims to minimize the annual comprehensive cost after the energy storage is configured; the lower-layer model aims to minimize the curtailment rate of wind and solar energy. Then, according to the different characteristics of batteries and hydrogen energy storage, a hydrogen-electricity hybrid energy storage system coordination strategy is proposed. Finally, according to the nonlinear multi-objective characteristics of the model, the two-layer iterative particle swarm optimization algorithm is combined with power flow calculation to solve the model. In the simulation part, taking a transmission network with a high proportion of wind and solar power access as an example, the capacity and location of hydrogen-electricity hybrid energy storage system are optimized to verify the feasibility and effectiveness of the model and the proposed solution algorithm. Ultimately, the transfer ability of photovoltaic and wind power output in time series is improved, the consumption of high-carbon fossil energy is reduced, and the curtailment rate of wind and solar energy is reduced.

Key words: transmission grid, high proportion of photovoltaic and wind power connection, optimized configuration, hydrogen-electricity hybrid energy storage system, two-level programming model

中图分类号:

TM715

陈颖, 石永富, 钟鸿鸣, 王湘, 雷霞, 尹洪全, 刘鑫. 含高比例风光接入的输电网氢-电混合储能系统配置方法[J]. 电力建设, 2022, 43(11): 85-98.

CHEN Ying, SHI Yongfu, ZHONG Hongming, WANG Xiang, LEI Xia, YIN Hongquan, LIU Xin. Configuration Method for Hydrogen-Electricity Hybrid Energy Storage System in Transmission Grid with High Proportion of PV and Wind Power Connection[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(11): 85-98.

图/表 16

图1 氢-电HESS分配策略模式切换流程图

Fig.1 Flow chart of distribution strategy mode switching of hydrogen-electricity HESS

图2 某地区80节点输电网网架结构

Fig.2 80-node transmission grid structure in a certain area

图3 风光理想出力

Fig.3 The ideal output of photovoltaic and wind power

图4 每小时本地负荷功率

Fig.4 Local load power per hour

图5 每小时外送负荷功率

Fig.5 Delivered load power per hour

表1 不同场景的各项成本和投资回收年限

Table 1 List of costs and payback period for different scenarios

表2 各场景的弃风弃光率和年网损

Table 2 Wind and PV curtailment rate and annual network loss in various scenarios

图6 各场景月弃风弃光量

Fig.6 Amount of monthly abandoned wind and PV invarious scenarios

图7 供暖期典型日节点1—30运行工况时空分布图

Fig.7 Spatial and temporal distribution of operating conditions of node 1 to 30 on typical days during the heating period

图8 非供暖期典型日节点31—60运行工况时空分布图

Fig.8 Spatial and temporal distribution of operating conditions of node 31 to 60 on typical days during non-heating period

图9 有无配合策略的氢-电HESS充放电情况

Fig.9 Hydrogen-electricity HESS charge and discharge with or without coordination strategy

图A1 不同储能形式储能时长与储能容量对比

Fig.A1 Comparison of energy storage duration and capacity of different energy storage forms

表A1 各类型电站接入节点

Table A1 Various types of power station access nodes

表A2 场景2蓄电池储能系统配置结果

Table A2 Battery storage configuration result in scenario 2

表A3 场景3氢储能配置结果

Table A3 Hydrogen energy storage configuration result in Scenario 3

表A4 场景4氢-电HESS配置结果

Table A4 Hydrogen-electric HESS configuration result in scenario 4

参考文献 22

[1]	习近平. 继往开来, 开启全球应对气候变化新征程: 在气候雄心峰会上的讲话[EB/OL]. (2020-12-12)[2022-01-15]. http://www.gov.cn/gongbao/content/2020/content_5570055.htm.
[2]	舒印彪, 张智刚, 郭剑波, 等. 新能源消纳关键因素分析及解决措施研究[J]. 中国电机工程学报, 2017, 37(1): 1-9.
	SHU Yinbiao, ZHANG Zhigang, GUO Jianbo, et al. Study on key factors and solution of renewable energy accommodation[J]. Proceedings of the CSEE, 2017, 37(1): 1-9.
[3]	HARSHA P, DAHLEH M. Optimal management and sizing of energy storage under dynamic pricing for the efficient integration of renewable energy[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1164-1181. doi: 10.1109/TPWRS.2014.2344859 URL
[4]	李笑蓉, 朱瑾, 石少伟, 等. 协调大规模风电汇聚外送的储能配置优化规划[J]. 智慧电力, 2022, 50(5): 69-76.
	LI Xiaorong, ZHU Jin, SHI Shaowei, et al. Energy storage optimal planning for coordinating large scale wind power aggregation and delivery[J]. Smart Power, 2022, 50(5): 69-76.
[5]	李建林, 牛萌, 王上行, 等. 江苏电网侧百兆瓦级电池储能电站运行与控制分析[J]. 电力系统自动化, 2020, 44(2): 28-35.
	LI Jianlin, NIU Meng, WANG Shangxing, et al. Operation and control analysis of 100 MW class battery energy storage station on grid side in Jiangsu power grid of China[J]. Automation of Electric Power Systems, 2020, 44(2): 28-35.
[6]	代倩, 吴俊玲, 秦晓辉, 等. 提升局部区域新能源外送能力的储能容量优化配置方法[J]. 电力系统自动化, 2022, 46(3): 67-74.
	DAI Qian, WU Junling, QIN Xiaohui, et al. Optimal configuration method of energy storage capacity for improving delivery ability of renewable energy in regional area[J]. Automation of Electric Power Systems, 2022, 46(3): 67-74.
[7]	刘畅, 卓建坤, 赵东明, 等. 利用储能系统实现可再生能源微电网灵活安全运行的研究综述[J]. 中国电机工程学报, 2020, 40(1): 1-18.
	LIU Chang, ZHUO Jiankun, ZHAO Dongming, et al. A review on the utilization of energy storage system for the flexible and safe operation of renewable energy microgrids[J]. Proceedings of the CSEE, 2020, 40(1): 1-18.
[8]	MICHIORRI A, LUGARO J, SIEBERT N, et al. Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation[J]. Renewable Energy, 2018, 117: 380-392. doi: 10.1016/j.renene.2017.10.070 URL
[9]	李军徽, 付英男, 李翠萍, 等. 提升风电消纳的储热电混合储能系统经济优化配置[J]. 电网技术, 2020, 44(12): 4547-4557.
	LI Junhui, FU Yingnan, LI Cuiping, et al. Economic optimal configuration of hybrid energy storage system for improving wind power consumption[J]. Power System Technology, 2020, 44(12): 4547-4557.
[10]	郭明萱, 穆云飞, 肖迁, 等. 考虑电池寿命损耗的园区综合能源电/热混合储能优化配置[J]. 电力系统自动化, 2021, 45(13): 66-75.
	GUO Mingxuan, MU Yunfei, XIAO Qian, et al. Optimal configuration of electric/thermal hybrid energy storage for park-level integrated energy system considering battery life loss[J]. Automation of Electric Power Systems, 2021, 45(13): 66-75.
[11]	梁芷睿, 宋政湘, 王建华, 等. 液态金属电池储能系统在光氢耦合微电网中的优化配置[J]. 电力系统自动化, 2018, 42(4): 64-69.
	LIANG Zhirui, SONG Zhengxiang, WANG Jianhua, et al. Optimal configuration of liquid metal battery energy storage system in photovoltaic and hydrogen coupled microgrid[J]. Automation of Electric Power Systems, 2018, 42(4): 64-69.
[12]	杨军峰, 郑晓雨, 惠东, 等. 储能技术在送端电网中促进新能源消纳的容量需求分析[J]. 储能科学与技术, 2018, 7(4): 698-704.
	YANG Junfeng, ZHENG Xiaoyu, HUI Dong, et al. Capacity demand analysis of energy storage in the sending-side of a power grid for accommodating large-scale renewables[J]. Energy Storage Science and Technology, 2018, 7(4): 698-704.
[13]	高赐威, 王崴, 陈涛. 基于可逆固体氧化物电池的电氢一体化能源站容量规划[J]. 中国电机工程学报, 2022, 42(17): 6155-6170.
	GAO Ciwei, WANG Wei, CHEN Tao. Capacity planning of electric-hydrogen integrated energy station based on reversible solid oxide battery[J]. Proceedings of the CSEE, 2022, 42(17): 6155-6170.
[14]	魏繁荣, 随权, 林湘宁, 等. 考虑制氢设备效率特性的煤风氢能源网调度优化策略[J]. 中国电机工程学报, 2018, 38(5): 1428-1439.
	WEI Fanrong, SUI Quan, LIN Xiangning, et al. Energy control scheduling optimization strategy for coal-wind-hydrogen energy grid under consideration of the efficiency features of hydrogen production equipment[J]. Proceedings of the CSEE, 2018, 38(5): 1428-1439.
[15]	朱凯, 张艳红. “双碳”形势下电力行业氢能应用研究[J]. 发电技术, 2022, 43(1): 65-72. doi: 10.12096/j.2096-4528.pgt.21098
	ZHU Kai, ZHANG Yanhong. Research on application of hydrogen in power industry under “double carbon” circumstance[J]. Power Generation Technology, 2022, 43(1): 65-72. doi: 10.12096/j.2096-4528.pgt.21098
[16]	刘海镇, 徐丽, 王新华, 等. 电网氢储能场景下的固态储氢系统及储氢材料的技术指标研究[J]. 电网技术, 2017, 41(10): 3376-3384.
	LIU Haizhen, XU Li, WANG Xinhua, et al. Technical indicators for solid-state hydrogen storage systems and hydrogen storage materials for grid-scale hydrogen energy storage application[J]. Power System Technology, 2017, 41(10): 3376-3384.
[17]	张昊天, 韦钢, 袁洪涛, 等. 考虑氢-电混合储能的直流配电网优化调度[J]. 电力系统自动化, 2021, 45(14): 72-81.
	ZHANG Haotian, WEI Gang, YUAN Hongtao, et al. Optimal scheduling of DC distribution network considering hydrogen-power hybrid energy storage[J]. Automation of Electric Power Systems, 2021, 45(14): 72-81.
[18]	丁明, 方慧, 毕锐, 等. 基于集群划分的配电网分布式光伏与储能选址定容规划[J]. 中国电机工程学报, 2019, 39(8): 2187-2201.
	DING Ming, FANG Hui, BI Rui, et al. Optimal siting and sizing of distributed PV-storage in distribution network based on cluster partition[J]. Proceedings of the CSEE, 2019, 39(8): 2187-2201.
[19]	张俊涛, 程春田, 申建建, 等. 考虑风光不确定性的高比例可再生能源电网短期联合优化调度方法[J]. 中国电机工程学报, 2020, 40(18): 5921-5932.
	ZHANG Juntao, CHENG Chuntian, SHEN Jianjian, et al. Short-term joint optimal operation method for high proportion renewable energy grid considering wind-solar uncertainty[J]. Proceedings of the CSEE, 2020, 40(18): 5921-5932.
[20]	吕梦璇, 娄素华, 刘建琴, 等. 含高比例风电的虚拟电厂多类型备用协调优化[J]. 中国电机工程学报, 2018, 38(10): 2874-2882.
	LÜ Mengxuan, LOU Suhua, LIU Jianqin, et al. Coordinated optimization of multi-type reserve in virtual power plant accommodated high shares of wind power[J]. Proceedings of the CSEE, 2018, 38(10): 2874-2882.
[21]	向育鹏, 卫志农, 孙国强, 等. 基于全寿命周期成本的配电网蓄电池储能系统的优化配置[J]. 电网技术, 2015, 39(1): 264-270.
	XIANG Yupeng, WEI Zhinong, SUN Guoqiang, et al. Life cycle cost based optimal configuration of battery energy storage system in distribution network[J]. Power System Technology, 2015, 39(1): 264-270.
[22]	蒲雨辰, 李奇, 陈维荣, 等. 计及最小使用成本及储能状态平衡的电-氢混合储能孤岛直流微电网能量管理[J]. 电网技术, 2019, 43(3): 918-927.
	PU Yuchen, LI Qi, CHEN Weirong, et al. Energy management for islanded DC microgrid with hybrid electric-hydrogen energy storage system based on minimum utilization cost and energy storage state balance[J]. Power System Technology, 2019, 43(3): 918-927.

含高比例风光接入的输电网氢-电混合储能系统配置方法

Configuration Method for Hydrogen-Electricity Hybrid Energy Storage System in Transmission Grid with High Proportion of PV and Wind Power Connection

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 16

参考文献 22

相关文章 15

编辑推荐

Metrics

本文评价

[1]	潘思宇, 刘宝柱. 面向配电网故障快速处理的边缘计算单元优化配置方法[J]. 电力建设, 2022, 43(3): 31-41.
[2]	丁曦, 姜威, 郭创新, 奚增辉, 高洁. 考虑需求响应的电/热/气云储能优化配置策略[J]. 电力建设, 2022, 43(3): 83-99.
[3]	初壮, 孙健浩, 赵蕾, 孙旭. 考虑风光与负荷时序特性的主动配电网分布式电源优化配置[J]. 电力建设, 2022, 43(11): 53-62.
[4]	孟珺遐, 蒋利民, 谢佳妮, 汪颖. 考虑用户投资意愿的电压暂降治理设备优化配置[J]. 电力建设, 2021, 42(8): 55-62.
[5]	江卓翰, 刘志刚, 许加柱, 伍敏, 谢欣涛, 侯益灵. 计及风光储的冷热电联供系统双层协同优化配置方法[J]. 电力建设, 2021, 42(8): 71-80.
[6]	刘帅, 孔亮, 刘自发, 李玉文, 陈逸轩. 基于深度强化学习的输电网网架规划方法[J]. 电力建设, 2021, 42(7): 101-109.
[7]	方朝雄，吴晓升，江岳文. 考虑暂态稳定性的网储多目标双层优化[J]. 电力建设, 2020, 41(7): 58-66.
[8]	沈青文，程若发，付鑫. 一种计及脆弱性指标的分布式电源优化配置方法[J]. 电力建设, 2020, 41(3): 54-61.
[9]	韩正一, CRESPI Giulia, 黄涛, 谭新, 马志远, 杨方, 黄瀚. 欧洲电网的发展及其与全球能源互联网的兼容性[J]. 电力建设, 2020, 41(11): 60-70.
[10]	王俊丰, 孔令生, 范心明, 彭元泉, 陈昊, 宋关羽. 面向有源配电网运行经济性的智能储能软开关规划[J]. 电力建设, 2020, 41(10): 63-70.
[11]	耿晓红, 文俊，谈萌2 贺冬珊1 王思超，韩民晓. 高电缆化率对直流受端输电网谐波传递特性的影响[J]. 电力建设, 2020, 41(1): 106-113.
[12]	吴金城，董树锋，张舒鹏，韩荣杰，寿挺，李建斌. 基于分布式计算技术的火电厂辅助调频储能系统容量及功率规划方法[J]. 电力建设, 2019, 40(6): 57-64.
[13]	方金涛，龚庆武. 考虑运行风险的主动配电网分布式电源多目标优化配置[J]. 电力建设, 2019, 40(5): 128-.
[14]	王晞，苟竞，苏韵掣，杨新婷，欧阳雪彤，李奥，樊金柱，李华强. 基于联合加权熵的高比例可再生能源电网适应性扩展规划[J]. 电力建设, 2019, 40(12): 45-54.
[15]	贺继锋, 杜治，黄家祺，方仍存，周玉洁，刘源，杨军. 考虑储能站投资收益的配电网规划模型 [J]. 电力建设, 2017, 38(6): 92-.