Abstract:With the rapid development of wind power generation, the inherent characteristics of intermittent, fluctuating, and randomness lead to high wind curtailment rates, and power-to-hydrogen (P2H) equipment converts excess wind power into clean hydrogen energy that can be stored and reused. However, traditional P2H equipment planning research ignores external power fluctuation, only analyzing its static characteristics. As an electrical load with a fixed energy conversion efficiency, P2H equipment is too ideal to operate within any range under the rated capacity. The load range is affected by wind power fluctuation, and exceeding this allowable range will influence the safety and service life of P2H equipment. Recently, the dynamic power range has been studied, but most have yet to give specific control strategies and unified models. Therefore, this paper proposes a power range selection strategy to smoothly track the external power fluctuation by segmented response current and voltage. Firstly, an alkaline electrolysis cell (AEC) is selected as the research object, and the correlation between wind power and hydrogen production is studied by considering its hydrogen production efficiency characteristic. Then, based on realizing high-quality hydrogen production, an optimal configuration model combining operation range planning and economic planning is constructed. The range selection strategy ensures the operating ability of AEC to act as a load, realizing the stable operation of the whole system. In economic planning, the model comprehensively considers the whole life cycle cost, power purchase cost, hydrogen sales revenue, and wind curtailment penalty cost as the objective function, and uses the chaotic particle swarm optimization (CPSO) algorithm to solve it. Finally, the method proposed simultaneously has a lower wind curtailment rate and higher hydrogen production quality than the existing configuration models, thus leading to optimal economics. By selecting historical annual wind speed data at 10 min intervals, the two-parameter Weibull distribution function is applied to build typical scenarios. Simulation results show that, compared with traditional models, the proposed configuration model reduces the capacity by 22 % and the wind curtailment rate by 23 %, greatly improving the equipment investment cost. When the safety device detects that the hydrogen to oxygen (HTO) is higher than 2 %, P2H equipment will shut down automatically, thereby reducing the explosion risk of mixing hydrogen and oxygen. Furthermore, the influence of hydrogen selling price on the capacity planning results is separately analyzed. The price of 7.2 EUR/kg is a key node in this example, directly related to the curtailed wind power. The main conclusions are as follows: (1) The proposed range selection strategy can track fluctuating wind power, which ensures the safety of mixed gas and overload problems. (2) By analyzing the hydrogen production efficiency curve of AEC, the equipment can operate near the maximum efficiency point, and the marginal cost of hydrogen production is reduced. (3) Compared with traditional models, the optimal configuration model combines operating range planning and economic planning, considering equipment safety, hydrogen production quality, and economy. It greatly increases the hydrogen production revenue, reduces the total planning cost, and can better adapt to wind power fluctuation. The CPSO algorithm can also converge to a better solution with fewer iterations than the PSO algorithm. (4) The hydrogen selling price will influence the capacity configuration results of P2H equipment. As the hydrogen price rises, the equipment capacity and hydrogen quality increase linearly. However, due to curtailed wind power limitations, the configuration results remain the same after the price reaches 7.2 EUR/kg.
李军舟, 赵晋斌, 陈逸文, 毛玲, 屈克庆. 考虑动态功率区间和制氢效率的电转氢(P2H)设备容量配置优化[J]. 电工技术学报, 2023, 38(18): 4864-4874.
Li Junzhou, Zhao Jinbin, Chen Yiwen, Mao Ling, Qu Keqing. Optimal Capacity Configuration of P2H Equipment Considering Dynamic Power Range and Hydrogen Production Efficiency. Transactions of China Electrotechnical Society, 2023, 38(18): 4864-4874.
[1] 姜克隽, 冯升波. 走向《巴黎协定》温升目标: 已经在路上[J]. 气候变化研究进展, 2021, 17(1): 1-6. Jiang Kejun, Feng Shengbo.Going to the mitigation targets in Paris Agreement: the world is on the road[J]. Climate Change Research, 2021, 17(1): 1-6. [2] PACS-L: 国家能源局. 2020年可再生能源持续保持高质量发展[EB/OL]. 2021[2021-01-30]. [3] 蔡钦钦, 肖宇, 朱永强. 计及电转氢和燃料电池的电热微网日前经济协调调度模型[J]. 电力自动化设备, 2021, 41(10): 107-112. Cai Qinqin, Xiao Yu, Zhu Yongqiang.Day ahead economic coordinated dispatching model of elec-trothermal microgrid considering electricity to hydrogen and fuel cell[J]. Electric Power Automation Equipment, 2021, 41(10): 107-112. [4] 曹蕃, 郭婷婷, 陈坤洋, 等. 风电耦合制氢技术进展与发展前景[J]. 中国电机工程学报, 2021, 41(6): 2187-2200, 24. Cao Fan, Guo Tingting, Chen Kunyang, et al.Progress and development prospect of coupled wind and hydrogen systems[J]. Proceedings of the CSEE, 2021, 41(6): 2187-2200, 24. [5] 潘光胜, 顾伟, 张会岩, 等. 面向高比例可再生能源消纳的电氢能源系统[J]. 电力系统自动化, 2020, 44(23): 1-10. Pan Guangsheng, Gu Wei, Zhang Huiyan, et al.Electricity and hydrogen energy system towards accommodation of high proportion of renewable energy[J]. Automation of Electric Power Systems, 2020, 44(23): 1-10. [6] Den R B, Smit M A.Determining the future business case for small-scale hydrogen storage of renewable energy for autonomous residential applications[J]. The Academic Research Community Publication, 2018, 1: 423-429. [7] Liu Bo, Liu Shixue, Guo Shusheng, et al.Economic study of a large-scale renewable hydrogen application utilizing surplus renewable energy and natural gas pipeline transportation in China[J]. International Journal of Hydrogen Energy, 2020, 45(3): 1385-1398. [8] 王敏. 国内外新能源制氢发展现状及未来趋势[J]. 化学工业, 2018, 36(6): 13-18. Wang Min.Development status and future trend of hydrogen production from new energy at home and abroad[J]. Chemical Industry, 2018, 36(6): 13-18. [9] 郭小强, 魏玉鹏, 万燕鸣, 等. 新能源制氢电力电子变换器综述[J]. 电力系统自动化, 2021, 45(20): 185-199. Guo Xiaoqiang, Wei Yupeng, Wan Yanming, et al.Overview of power electronic converters for hydrogen production from new energy sources[J]. Automation of Electric Power Systems, 2021, 45(20): 185-199. [10] Firtina-Ertis I, Acar C, Ertark E.Optimal sizing design of an isolated stand-alone hybrid wind-hydrogen system for a zero-energy house[J]. Applied Energy, 2020, 274: 11524. [11] 李鹏, 韩建沛, 殷云星, 等. 电转氢作为灵活性资源的微网容量多目标优化配置[J].电力系统自动化, 2019, 43(17): 28-35. Li Peng, Han Jianpei, Yin Yunxing, et al.Multi-objective optimal capacity configuration of microgrid with power to hydrogen as flexible resource[J]. Automation of Electric Power Systems, 2019, 43(17): 28-35. [12] 李奇, 赵淑丹, 蒲雨辰, 等. 考虑电氢耦合的混合储能微电网容量配置优化[J]. 电工技术学报, 2021, 36(3): 486-495. Li Qi, Zhao Shudan, Pu Yuchen, et al.Capacity allocation optimization of hybrid energy storage microgrid considering electric hydrogen coupling[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 486-495. [13] 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.Scheduling optimization strategy of coal wind hydrogen energy network considering efficiency characteristics of hydrogen production equipment[J]. Proceedings of the CSEE, 2018, 38(5): 1428-1439. [14] Nguyen T H T, Nakayama T, Ishida M. Optimal capacity design of battery and hydrogen system for the DC grid with photovoltaic power generation based on the rapid estimation of grid dependency[J]. International Journal of Electrical Power & Energy Systems, 2017, 89: 27-39. [15] Hirohisa Aki, Ichiro Sugimoto, Tokuyoshi Sugai, et al.Optimal operation of a photovoltaic generation-powered hydrogen production system at a hydrogen refueling station[J]. International Journal of Hydrogen Energy, 2018, 43(32): 14892-14904. [16] Fang R, Liang Y.Control strategy of electrolyzer in a wind-hydrogen system considering the constraints of switching times[J]. International Journal of Hydrogen Energy, 2019, 44(46): 25104-25111. [17] Attemene N S, Agbli K S, Fofana S, et al.Optimal sizing of a wind, fuel cell, electrolyzer, battery and supercapacitor system for off-grid applications[J]. International Journal of Hydrogen Energy, 2020, 45(8): 5512-5525. [18] 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 Xiaojun, Nie Congying, Lü Hong.Optimal control strategy of off grid alkaline electrolyzer array for hydrogen production from wind power con-sidering electrothermal characteristics[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 463-472. [19] 李争, 张蕊, 孙鹤旭, 等. 可再生能源多能互补制-储-运氢关键技术综述[J]. 电工技术学报, 2021, 36(3): 446-462. Li Zheng, Zhang Rui, Sun Hexu, et al.Review on key technologies of renewable energy multi energy com-plementary hydrogen generation storage transporta-tion[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 446-462. [20] 崔强, 王秀丽, 曾平良, 等. 调峰约束下考虑风电消纳的多目标尖峰电价决策模型[J]. 中国电机工程学报, 2015, 35(11): 2662-2669. Cui Qiang, Wang Xiuli, Zeng Pingliang, et al.Multi-objective peak price decision model considering wind power consumption under peak shaving constraints[J]. Proceedings of the CSEE, 2015, 35(11): 2662-2669. [21] 曹宇, 汪可友, 石文辉, 等. 风-光-海水抽蓄联合发电系统的调度策略研究[J]. 电力系统保护与控制, 2018, 46(2): 16-23. Cao Yu, Wang Keyou, Shi Wenhui, et al.Study on dispatching strategies of a wind-solar-seawater pumped storage hybrid power system[J]. Power System Protection and Control, 2018, 46(2): 16-23. [22] Shoaib M, Siddiqui I, Amir Y M, et al.Evaluation of wind power potential in Baburband (Pakistan) using Weibull distribution function[J]. Renewable & Susta-inable Energy Reviews, 2017, 70: 1343-1351. [23] Shen Xiaojun, Zhang Xiaoyun, Li Guojie, et al.Experimental study on the external electrical thermal and dynamic power characteristics of alkaline water electrolyzer[J]. International Journal of Energy Research, 2018: 1-14. [24] China Shipbuilding Heavt Industry Group Company 718 Research Institute. Company 718 Research Institute. Installation and operation instructions for KZDQ series hydrogen generation units[Z]. 2015. [25] Mónica Sánchez, Ernesto A, Lourdes Rodríguez, et al.Semi-empirical model and experimental validation for the performance evaluation of a 15kW alkaline water electrolyzer[J]. International Journal of Hydrogen Energy, 2018, 43(45): 20332-20345. [26] 王文飞, 周雒维, 李绍令, 等. 采用改进CPSO动态搜索时频原子的电能质量扰动信号去噪方法[J]. 电网技术, 2018, 42(12): 4129-4137. Wang Wenfei, Zhou Luowei, Li Shaoling, et al.Power quality disturbance signal denoising method based on improved CPSO dynamic search time-frequency atom[J]. Power System Technology, 2018, 42(12): 4129-4137.