为了最大化消纳源侧可再生能源及更好地满足荷侧负荷需求,提出关于电制氨多元利用环节和混合储能装置容量配置的双层优化调度策略。首先,在上层根据自适应粒子群（APSO）算法,以储能容量为决策变量,实现对储能装置最小运行成本;然后,在下层中为提高系统的灵活性,引入考虑灵活热电比的燃气轮机组和氨燃料电池,解决电热出力调节能力不足的问题,并为减少系统发电成本,考虑分时电、气价,建立需求响应机制、阶梯型碳交易制度,以系统总运行成本最小为目标确定各机组最优出力,采用CPLEX求解器对其求解。最后,通过对比不同方案,验证所提方法的碳排放量、运行成本和风光消纳率达到最优。
Abstract
To maximize the consumption of renewable energy on the source side and better meet the demand on the load side, a bi-level optimal scheduling strategy is proposed for the multi-use pathways of power-to-ammonia and the capacity allocation of hybrid energy storage systems. In the upper level, the adaptive particle swarm optimization （APSO） algorithm is used to determine the optimal storage capacities with the objective of minimizing operational costs. In the lower level, to enhance system flexibility, gas turbine units with flexible heat-to-power ratios and ammonia fuel cells are introduced to address the limitation of adjustable power-to-heat output. Additionally, to reduce power generation costs, time-of-use electricity and gas prices, a demand response mechanism, and a tiered carbon trading scheme are incorporated. The objective is to minimize total system operating cost, and the model is solved using the CPLEX solver. Finally, comparative analysis of different scenarios demonstrates the proposed method's effectiveness in reducing carbon emissions, lowering operating costs, and improving wind and solar energy utilization.
关键词
可再生能源 /
储能 /
综合能源系统 /
调度 /
电制氨 /
灵活热电比
Key words
renewable energy /
energy storage /
integrated energy system /
scheduling /
power-to-ammonia /
flexible heat-to-power ratio
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 张鹏, 吴昊, 张佳丽, 等. 中国风光大型基地与氢储能高比例耦合发展研究: 以“三北” 地区为例[J]. 水力发电, 2023, 49(11): 16-23.
ZHANG P, WU H, ZHANG J L, et al.Research on high proportion coupling development between large-scale wind power and photovoltaic bases and hydrogen energy storage in China: taking the Three-North regions as example[J]. Water power, 2023, 49(11): 16-23.
[2] 袁文腾, 陈亮, 王春波, 等. 基于氨储能技术的电转氨耦合风-光-火综合能源系统双层优化调度[J]. 中国电机工程学报, 2023, 43(18): 6992-7003.
YUAN W T, CHEN L, WANG C B, et al.Bi-level optimal scheduling of power-to-ammonia coupling wind-photovoltaic-thermal integrated energy system based on ammonia energy storage technology[J]. Proceedings of the CSEE, 2023, 43(18): 6992-7003.
[3] MEWAFY A, ISMAEL I, KADDAH S,et al.Optimization design of green hydrogen ammonia multi-purpose hybrid microgrid[J]. Renewable and sustainable energy review,2024, 192: 114174.
[4] WANG S, LI T X, WANG S Y, et al.Performance assessments of an integrated system for post-combustion CO2 capture and NH4HCO3 production in a biomass power plant based on green ammonia[J]. Energy conversion and management, 2024, 315: 118752.
[5] JI M M, ZHANG W, XU Y F, et al.Optimisation of multi-period renewable energy systems with hydrogen and battery energy storage: a P-graph approach[J]. Energy conversion and management, 2023, 281: 116826.
[6] ALONSO A M, COSTA D, MESSAGIE M, et al.Techno-economic assessment on hybrid energy storage systems comprising hydrogen and batteries: a case study in Belgium[J]. International journal of hydrogen energy, 2024, 52: 1124-1135.
[7] WEN D, AZIZ M.Flexible operation strategy of an integrated renewable multi-generation system for electricity, hydrogen, ammonia, and heating[J]. Energy conversion and management, 2022, 253: 115166.
[8] 夏鑫, 蔺建民, 李妍, 等. 氨混合燃料体系的性能研究现状[J]. 化工进展, 2022, 41(5): 2332-2339.
XIA X, LIN J M, LI Y, et al.Research progress on performance and application of ammonia fuel on engines[J]. Chemical industry and engineering progress, 2022, 41(5): 2332-2339.
[9] EDMONDS L, PFROMM P, AMANOR-BOADU V, et al.Green ammonia production-enabled demand flexibility in agricultural community microgrids with distributed renewables[J]. Sustainable energy, grids and networks, 2022, 31: 100736.
[10] WANG H C, PALYS M, DAOUTIDIS P, et al.Optimal design of sustainable ammonia-based food-energy-water systems with nitrogen management[J]. ACS sustainable chemistry & engineering, 2021, 9(7): 2816-2834.
[11] 张晓虎, 倪景源. 考虑柔性负荷的联合发电系统低碳经济优化调度[J/OL]. 太阳能学报, 2024, 1-9[2024-10-16]. https://doi.org/10.19912/j.0254-0096.tynxb.2024-0231.
ZHANG X H,NI J Y. Optimal low-carbon and economic dispatch of conbined power system considering flexible loads[J/OL]. Acta energiae solaris sinica, 2024, 1-9[2024-10-16]. https://doi.org/10.19912/j.0254-0096.tynxb.2024-0231.
[12] 潘婷, 许彦斌, 王雨晴, 等.考虑广义综合需求响应的综合能源系统调度优化[J/OL]. 现代电力, 1-10[2024-10-16]. https://doi.org/10.19725/j.cnki.1007-2322.2023.0173.
PAN T, XU Y B, WANG Y Q, et al. Integrated energy system dispatch optimization considering generalized integrated demand response[J/OL]. Modern electric power, 1-10[2024-10-16].https://doi.org/10.19725/j.cnki.1007-2322.2023.0173.
[13] 于晓凤, 周恩泽, 丁雪峰, 等. 基于TRNSYS的污水厂沼气热电联产系统优化分析和性能评价[J]. 太阳能学报, 2021, 42(10): 324-330.
YU X F, ZHOU E Z, DING X F, et al.Optimization analysis and performance evaluation of biogas cogeneration system of sewage treatment plant based on trnsys[J]. Acta energiae solaris sinica, 2021, 42(10): 324-330.
[14] PALYS M J, KUZNETSOV A, TALLAKSEN J, et al.A novel system for ammonia-based sustainable energy and agriculture: concept and design optimization[J]. Chemical engineering and processing-process intensification, 2019, 140: 11-21.
[15] PALYS M J, DAOUTIDIS P.Using hydrogen and ammonia for renewable energy storage: a geographically comprehensive techno-economic study[J]. Computers & chemical engineering, 2020, 136: 106785.
[16] GONG C Y, XU Y H, CAI S S, et al.Comparative study on thermodynamic analysis of solid oxide fuel cells supplied with methanol or ammonia[J]. International journal of hydrogen energy, 2024, 50: 1293-1301.
[17] BROWN T. Industrial demonstrations of ammonia fuel in Japan[EB/OL]. Ammonia Energy, 2017. [2025-05-13]. https://www.ammoniaenergy.org/articles/industrial-demonstrations-of-ammonia-fuel-in-japan/.
[18] 陈登勇, 刘方, 刘帅. 基于阶梯碳交易的含P2G-CCS耦合和燃气掺氢的虚拟电厂优化调度[J]. 电网技术, 2022, 46(6): 2042-2054.
CHEN D Y, LIU F, LIU S.Optimization of virtual power plant scheduling coupling with P2G-CCS and doped with gas hydrogen based on stepped carbon trading[J]. Power system technology, 2022, 46(6): 2042-2054.
[19] 刘秋华, 王明康,杨圣城. 基于全寿命周期内经济收益最大化的退役电池储能容量配置方法研究[J]. 太阳能学报, 2024, 45(7): 143-152.
LIU Q H, WANG M K, YANG S C.Research on configuration method of energy storage capacity for retired batteries based on maximizing economic benefits throughout life cycle[J]. Acta energiae solaris sinica, 2024, 45(7): 143-152.
[20] 周鑫, 韩肖清, 李伊竹林, 等. 基于可调热电比和两阶段阶梯式碳交易的多主体综合能源系统低碳经济调度策略[J]. 电力系统及其自动化学报, 2023, 35(11): 10-21.
ZHOU X, HAN X Q, LI Y Z L, et al. Low-carbon economic dispatch strategy for multi-agent integrated energy system based on adjustable thermoelectric ratio and two-stage stepped carbon trading[J]. Proceedings of the CSU-EPSA, 2023, 35(11): 10-21.
基金
国家自然科学基金黄河水科学研究联合基金重点项目（U2243216）
PDF(2903 KB)
