为解决大规模波动性风电制氢效率低的问题,提出一种结合电网购电的风氢系统电解槽阵列优化控制策略。首先研究质子交换膜电解槽制氢效率曲线,根据效率特性,针对电解槽阵列启停控制及功率分配问题,提出一种考虑制氢效率的分段调控策略;其次以系统总成本最小为目标,基于人工蜂群算法构建风氢系统日内优化调度模型,通过宁波某地实际数据进行计算分析。结果表明,所提策略较简单启停控制平均每小时提高产氢量5.93%,日均启停次数从18次降至2次,电解槽利用率从64.58%提升至98.75%;且当电价降低47.27%和氢价上调14.29%时,产氢量和购电量均提高15.56%及227.79%,但总成本分别降低5.91%和12.78%,氢气价格对系统经济性的影响更大。
Abstract
To address the issue of low efficiency in hydrogen production from large-scale fluctuating wind power, we proposed an optimized control strategy for an electrolyzer array in a wind-hydrogen system combined with grid power purchases. Firstly, we stuolied the hydrogen production efficiency curve of proton exchange membrane electrolyzer. Based on the efficiency characteristics, we proposed a segmented regulation strategy considering hydrogen production efficiency for the start-stop control and power distribution of the electrolyzer array. Secondly, aiming to minimize the total system cost, we constructed an intraday optimization scheduling model for the wind-hydrogen system based on the artificial bee colony algorithm, using actual data from Ningbo for computational analysis. The results show that the proposed strategy increases hydrogen production by an average of 5.93% per hour compared to simple start-stop control, reduces the average daily start-stop times from 18 to 2, and improves the electrolyzer utilization rate from 64.58% to 98.75%. Furthermore, when the electricity price decreases by 47.27% and the hydrogen price increases by 14.29%, hydrogen production and power purchase increase by 15.56% and 227.79%, respectively, but the total cost decreases by 5.91% and 12.78%, indicating that the hydrogen price has a greater impact on the system’s economic performance.
关键词
电解水制氢 /
电解槽阵列 /
风电 /
效率特性 /
功率分配 /
弃风 /
优化控制
Key words
hydrogen production by water electrolysis /
electrolyzer array /
wind power /
efficiency characteristics /
power distribution /
wind curtailment /
optimal control
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参考文献
[1] 黄启帆, 陈洁, 曹喜民, 等. 基于碱性电解槽和质子交换膜电解槽协同制氢的风光互补制氢系统优化[J]. 电力自动化设备, 2023, 43(12): 168-174.
HUANG Q F, CHEN J, CAO X M, et al.Optimization of wind-photovoltaic complementation hydrogen production system based on synergistic hydrogen production by alkaline electrolyzer and proton exchange membrane electrolyzer[J]. Electric power automation equipment, 2023, 43(12): 168-174.
[2] DINH V N, LEAHY P, MCKEOGH E, et al.Development of a viability assessment model for hydrogen production from dedicated offshore wind farms[J]. International journal of hydrogen energy, 2021, 46(48): 24620-24631.
[3] YU M L, WANG K, VREDENBURG H.Insights into low-carbon hydrogen production methods: green, blue and aqua hydrogen[J]. International journal of hydrogen energy, 2021, 46(41): 21261-21273.
[4] 邓智宏, 江岳文. 考虑制氢效率特性的风氢系统容量优化[J]. 可再生能源, 2020, 38(2): 259-266.
DENG Z H, JIANG Y W.Optimal sizing of a wind-hydrogen system under consideration of the efficiency characteristics of electrolysers[J]. Renewable energy resources, 2020, 38(2): 259-266.
[5] 牛萌, 洪振鹏, 李蓓, 等. 考虑制氢效率提升的风电制氢系统优化控制策略[J]. 太阳能学报, 2023, 44(9): 366-376.
NIU M, HONG Z P, LI B, et al.Optimal control strategy of wind power to hydrogen system considering electrolyzer efficiency improvement[J]. Acta energiae solaris sinica, 2023, 44(9): 366-376.
[6] 温昶, 张博涵, 王雅钦, 等. 高效质子交换膜电解水制氢技术研究进展[J]. 华中科技大学学报(自然科学版), 2023, 51(1): 111-122.
WEN C, ZHANG B H, WANG Y Q, et al.Research progress of high efficiency proton exchange membrane water electrolysis technology[J]. Journal of Huazhong University of Science and Technology (natural science edition), 2023, 51(1): 111-122.
[7] 李洋洋, 邓欣涛, 古俊杰, 等. 碱性水电解制氢系统建模综述及展望[J]. 汽车工程, 2022, 44(4): 567-582.
LI Y Y, DENG X T, GU J J, et al.Comprehensive review and prospect of the modeling of alkaline water electrolysis system for hydrogen production[J]. Automotive engineering, 2022, 44(4): 567-582.
[8] NAGASAWA K, DAVIDSON F T, LLOYD A C, et al.Impacts of renewable hydrogen production from wind energy in electricity markets on potential hydrogen demand for light-duty vehicles[J]. Applied energy, 2019, 235: 1001-1016.
[9] 袁铁江, 谭捷, 万志. 考虑下游氢负荷波动的新能源制氢系统协调控制策略[J]. 电力系统自动化, 2023, 47(6): 150-157.
YUAN T J, TAN J, WAN Z.Coordinated control strategy of hydrogen producing system powered by renewable energy considering downstream hydrogen load fluctuations[J]. Automation of electric power systems, 2023, 47(6): 150-157.
[10] 卢昕宇, 杜帮华, 赵波, 等. 基于链式分配策略的风氢耦合系统设计与控制[J]. 太阳能学报, 2022, 43(6): 405-413.
LU X Y, DU B H, ZHAO B, et al.Design and control of wind-hydrogen coupled system based on chain distribution strategy[J]. Acta energiae solaris sinica, 2022, 43(6): 405-413.
[11] 李梓丘, 乔颖, 鲁宗相. 海上风电-氢能系统运行模式分析及配置优化[J]. 电力系统自动化, 2022, 46(8): 104-112.
LI Z Q, QIAO Y, LU Z X.Operation mode analysis and configuration optimization of offshore wind-hydrogen system[J]. Automation of electric power systems, 2022, 46(8): 104-112.
[12] 沈小军, 聂聪颖, 吕洪. 计及电热特性的离网型风电制氢碱性电解槽阵列优化控制策略[J]. 电工技术学报, 2021, 36(3): 463-472.
SHEN X J, NIE C Y, LYU H.Coordination control strategy of wind power-hydrogen alkaline electrolyzer bank considering electrothermal characteristics[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 463-472.
[13] 杨紫娟, 田雪沁, 吴伟丽, 等. 考虑电解槽组合运行的风电-氢能-HCNG耦合网络容量优化配置[J]. 电力系统自动化, 2023, 47(12): 76-85.
YANG Z J, TIAN X Q, WU W L, et al.Optimal capacity configuration of wind-hydrogen-HCNG coupled network considering combined electrolyzer operation[J]. Automation of electric power systems, 2023, 47(12): 76-85.
[14] 张潇桐, 戈阳阳, 姚红雨, 等. 基于粒子群算法的制氢电解槽运行控制策略[J]. 热力发电, 2023, 52(11): 115-122.
ZHANG X T, GE Y Y, YAO H Y, et al.Operation control strategy of hydrogen production electrolytic cell based on particle swarm optimization algorithm[J]. Thermal power generation, 2023, 52(11): 115-122.
[15] HONG Z P, WEI Z X, HAN X J.Optimization scheduling control strategy of wind-hydrogen system considering hydrogen production efficiency[J]. Journal of energy storage, 2022, 47: 103609.
[16] 郑博, 白章, 袁宇, 等. 多类型电解协同的风光互补制氢系统与容量优化[J]. 中国电机工程学报, 2022, 42(23): 8486-8496.
ZHENG B, BAI Z, YUAN Y, et al.Hydrogen production system and capacity optimization based on synergistic operation with multi-type electrolyzers under wind-solar power[J]. Proceedings of the CSEE, 2022, 42(23): 8486-8496.
[17] 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 F R, SUI Q, LIN X N, 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.
[18] 梁涛, 孙博峰, 谭建鑫, 等. 基于深度强化学习算法的风光互补可再生能源制氢系统调度方案[J]. 高电压技术, 2023, 49(6): 2264-2275.
LIANG T, SUN B F, TAN J X, et al.Scheduling scheme of wind-solar complementary renewable energy hydrogen production system based on deep reinforcement learning[J]. High voltage engineering, 2023, 49(6): 2264-2275.
[19] HAN B, STEEN S M, MO J K, et al.Electrochemical performance modeling of a proton exchange membrane electrolyzer cell for hydrogen energy[J]. International journal of hydrogen energy, 2015, 40(22): 7006-7016.
[20] 戴凡博. PEM电解水制氢催化剂及直接耦合光伏发电系统建模研究[D]. 杭州: 浙江大学, 2020.
DAI F B.Study of catalyst in PEM water electrolysis and directly coupling photovoltaic system simulation[D]. Hangzhou: Zhejiang University, 2020.
[21] 郭力, 杨书强, 刘一欣, 等. 风光储微电网容量规划中的典型日选取方法[J]. 中国电机工程学报, 2020, 40(8): 2468-2479.
GUO L, YANG S Q, LIU Y X, et al.Typical day selection method for capacity planning of microgrid with wind turbine-photovoltaic and energy storage[J]. Proceedings of the CSEE, 2020, 40(8): 2468-2479.
[22] 何尧, 刘建华, 杨荣华. 人工蜂群算法研究综述[J]. 计算机应用研究, 2018, 35(5): 1281-1286.
HE Y, LIU J H, YANG R H.Survey on artificial bee colony algorithm[J]. Application research of computers, 2018, 35(5): 1281-1286.
基金
国家重点研发计划(2021YFB2601601)