基于多种可再生能源的多联产系统优化配置研究

兰州理工大学学报 ›› 2023, Vol. 49 ›› Issue (6): 41-49.

基于多种可再生能源的多联产系统优化配置研究

李金平^*1,2,3, 牛轶男^1,2,3, 李紫荆^1,2,3, 李天澍^1,2,3, VOJISLAV Novakovic⁴, 王春龙^1,2,3

1.甘肃省生物质能与太阳能互补供能系统重点试验室,甘肃兰州 730050;
2.西北低碳城镇支撑技术协同创新中心, 甘肃兰州 730050;
3.兰州理工大学能源与动力工程学院, 甘肃兰州 730050;
4.挪威科技大学能源与过程工程系, 挪威特隆赫姆 NO-7491

收稿日期:2021-12-24 出版日期:2023-12-28 发布日期:2024-01-05
通讯作者: 李金平(1977-),男,宁夏中宁人,博士,教授.Email:lijinping77@163.com
基金资助:
国家重点研发计划项目(2019YFE0104900),国家自然科学基金(51676094),甘肃省高等学校产业支撑引导项目(2019C-13,2021CYZC-33),兰州市人才创新创业项目(2017-RC-34)

Study on the optimal allocation of co-production system based on multi-renewable energy

LI Jin-ping^1,2,3, NIU Yi-nan^1,2,3, LI Zi-jing^1,2,3, LI Tian-shu^1,2,3, VOJISLAV Novakovic⁴, WANG Chun-long^1,2,3

1. Key Laboratory of Complementary Energy System of Biomass and Solar Energy, Lanzhou 730050, China;
2. China Northwestern Collaborative Innovation Center of Low-carbon Urbanization Technologies, Lanzhou 730050, China;
3. College of Energy and Power Engineering, Lanzhou Univ. of Tech., Lanzhou 730050, China;
4. Department of Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim NO-7491, Norway

Received:2021-12-24 Online:2023-12-28 Published:2024-01-05

摘要/Abstract

摘要： 为提升基于多种可再生能源的多联产系统整体性能,合理的容量配置至关重要.针对基于太阳能、生物质能和空气能的多联产系统,以一次能源节约率最大化、费用年值节约率最大化和二氧化碳减排率最大化作为优化目标,以光伏光热一体化组件、内燃机、空气源热泵的容量为决策变量,采用改进的多目标遗传算法,利用优劣解距离法求解系统最优容量配置.同时,通过算例验证优化模型的可行性,并研究系统经济性能对成本参数的敏感性.结果表明,优化方案在能源、经济、环境各方面都表现出很好的性能,系统的一次能源节约率为29.07%,费用年值节约率为58.15%,二氧化碳减排率为54.30%,且厌氧发酵环节的成本参数对系统经济性能影响较大.

关键词: 可再生能源, 多联产系统, 多目标优化, TOPSIS法

Abstract: In order to improve the overall performance of co-production system based on multi-renewable energy, a reasonable capacity allocation is very important. For the co-production system based on biomass, solar and air energy, the maximization of primary energy saving rate, annual cost saving rate and carbon dioxide emission reduction rate are selected as the optimization functions, and the capacity of PV/T, internal combustion engine and air source heat pump are selected as decision variables. Using the NSGA-Ⅱ algorithm and weight-TOPSIS, the optimal capacity allocation is solved. Finally, the feasibility of the optimization model is validated through illustrative examples, and the sensitivity of system economic performance to cost parameters is explored. The results show that the optimized scheme exhibits excellent performance in energy, economy and environment, with a primary energy saving rate of 29.07%, an annual cost saving rate of 58.15%, and the carbon dioxide emission reduction rate of 54.30%. Furthermore, the cost parameters of anaerobic fermentation have a substantial influence on the economic performance of the system.

Key words: renewable energy, co-production system, multi-objective optimization, TOPSIS

中图分类号:

TK519

李金平, 牛轶男, 李紫荆, 李天澍, VOJISLAV Novakovic, 王春龙. 基于多种可再生能源的多联产系统优化配置研究[J]. 兰州理工大学学报, 2023, 49(6): 41-49.

LI Jin-ping, NIU Yi-nan, LI Zi-jing, LI Tian-shu, VOJISLAV Novakovic, WANG Chun-long. Study on the optimal allocation of co-production system based on multi-renewable energy[J]. Journal of Lanzhou University of Technology, 2023, 49(6): 41-49.

参考文献

[1] 李高潮,卢怀宇,孙启德,等.基于可再生能源的冷热电联供系统集成配置与运行优化研究进展[J].电网与清洁能源,2021,37(3):106-119.
[2] 王江江,王壮,杨颖,等.分布式冷热电联供系统集成设计与优化研究进展[J].分布式能源,2017,2(2):1-10.
[3] WU D,HAN Z H,LIU Z J,et al.Study on configuration optimization and economic feasibility analysis for combined cooling, heating and power system[J].Energy Conversion and Management,2019,190(7):91-104.
[4] YOUSEFI H,GHODUSINEJAD M H,NOOROLLAHI Y.GA/AHP-based optimal design of a hybrid CCHP system considering economy, energy and emission[J].Energy and Buildings,2017,138(3):309-317.
[5] LI G Z,WANG R,ZHANG T,et al.Multi-objective optimal design of renewable energy integrated CCHP system using PICEA-g[J].Energies,2018,11(4):1-26.
[6] WANG J J,LIU Y,REN F K,et al.Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility[J].Energy,2020,197:117313.
[7] REN F K,WANG J J,ZHU S T,et al.Multi-objective optimization of combined cooling, heating and power system integrated with solar and geothermal energies[J].Energy Conversion and Management,2019,197:111866.
[8] ZHANG L,ZHANG L Z,SUN B,et al.Nested optimization design for combined cooling, heating, and power system coupled with solar and biomass energy[J].International Journal of Electrical Power and Energy Systems,2020,123:106236.
[9] LI C B,YANG H Y,SHAHIDEHPOUR M,et al.Optimal planning of islanded integrated energy system with solar-biogas energy supply[J].IEEE Transactions on Sustainable Energy,2020,11(4):2437-2448.
[10] WU N Y,ZHAN X Y,ZHU X Y,et al.Analysis of biomass polygeneration integrated energy system based on a mixed-integer nonlinear programming optimization method[J].Journal of Cleaner Production,2020,271:122761.
[11] HASHIMOTO A G.Methane from cattle waste: Effects of temperature, hydraulic retention time, and influent substrate concentration on kinetic parameter (k)[J].Biotechnology and Bioengineering,1982,24(9):2039-2052.
[12] CHEN Y R,HASHIMOTO A G.Substrate utilization kinetic model for biological treatment process[J].Biotechnology and Bioengineering,1980,22(10):2081-2095.
[13] 刘建禹,邓斯文,杨胜明,等.寒区低能耗厌氧发酵反应器热工性能参数确定[J].农业工程学报,2019,35(17):248-255.
[14] 李娜.太阳能辅助沼气生产和综合利用系统数值仿真[D].青岛:青岛大学,2015.
[15] WANG J J,MAO T Z,SUI J,et al.Modeling and performance analysis of CCHP (combined cooling, heating and power) system based on co-firing of natural gas and biomass gasification gas[J].Energy,2015,93:801-815.
[16] HE X H,CAI R X.Typical off-design analytical performances of internal combustion engine cogeneration[J].Frontiers of Energy and Power Engineering in China,2009,3(2):184-192.
[17] FLORSCHUETZ L W.Extension of the Hottel-Whillier model to the analysis of combined photovoltaic/thermal flat plate collectors[J].Solar Energy,1979,22(4):361-366.
[18] DEB K,PRATAP A,AGARWAL S,et al.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Neural Networks,2002,6(2):182-197.
[19] LUO Z Y,YANG S,XIE N,et al.Multi-objective capacity optimization of a distributed energy system considering economy, environment and energy[J].Energy Conversion and Management,2019,200:112081.
[20] 杨天麟,朱能.北方地区部分小城镇建筑能耗状况调查与分析[C]//全国暖通空调制冷2006年学术年会论文集.北京:中国建设科技出版社,2006:18-19.
[21] 李宝山,张榕林.沼气灶与柴灶利用效率测试及可比条件探讨[J].中国能源,1983,4:25-27.
[22] 王江江,杨昆,刘娟娟.生物质燃气冷热电联供系统性能分析[J].农业机械学报,2014,45(3):196-205.
[23] 吴进,闵师界,朱立志,等.养殖场沼气工程商业化集中供气补贴分析[J].农业工程学报,2015,24:269-273.
[24] 黄宇.分布式能源系统燃气内燃机国产化现状及应用[J].煤气与热力,2016,36(3):19-24.
[25] 张东.多能互补的热电沼气联供系统动态特性与地域适应性研究[D].兰州:兰州理工大学,2017.
[26] YOUSEFI H,GHODUSINEJAD M H,KASAEIAN A.Multi-objective optimal component sizing of a hybrid ICE plus PV/T组件 driven CCHP microgrid[J].Applied Thermal Engineering,2017,122:126-138.
[27] 张昌爱.沼液的定价方法及其应用效果[J].生态学报,2011,31(6):1735-1741.
[28] 王革华.农村能源建设对减排SO₂和CO₂贡献分析方法[J].农业工程学报,1999,15(1):169-172.