Optimization of capacity configuration for multi-energy complementary systems using wind, solar, and energy storage

doi:10.19799/j.cnki.2095-4239.2024.0377

Abstract

Abstract:

The multi-energy complementary system integrating wind, solar, and energy storage technologies optimizes the use of renewable energy resources, enhancing both economic and environmental benefits. This study proposes a multi-energy complementary system model that incorporates wind, solar, and energy storage. The objective is to minimize the system's overall cost and carbon emissions, addressing both economic and environmental concerns. An improved non-dominated genetic algorithm is developed to obtain the Pareto optimal solution set for the multi-objective optimization problem. The optimal capacity configuration and operation scheme are determined using the technique for order preference by similarity to ideal solution. The system's operation scheduling is optimized using the CPLEX solver, a linear programming software, to validate the effectiveness and accuracy of the proposed system framework and scheduling model. Results demonstrate that the proposed optimization method significantly enhances renewable energy utilization, minimizes economic costs and carbon emissions, and improves the system's economic and environmental performance. This research offers valuable insights for the sustainable, stable, and reliable energy supply of renewable energy systems and supports the low-carbon transition of industrial parks.

Key words: multi-energy complementary, wind solar and energy storage, capacity configuration, scheduling strategy, multi-objective optimization

CLC Number:

TM 91

Junyi ZHI, Haoshu LING, Hao WU, Yilin ZHU, Haotian SHEN, Yujie XU, Haisheng CHEN. Optimization of capacity configuration for multi-energy complementary systems using wind, solar, and energy storage[J]. Energy Storage Science and Technology, 2024, 13(11): 3874-3888.

Figures/Tables 24

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Table 1

Carbon emission factor parameter table[33]"

碳排放因子	数值/(g/kWh)
$μ c, g$	220
$μ c, e$	968

Table 1

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References 36

1	李红霞, 李建林, 米阳. 新能源侧储能优化配置技术研究进展[J]. 储能科学与技术, 2022, 11(10): 3257-3267. DOI: 10.19799/j.cnki. 2095-4239.2022.0102.
	LI H X, LI J L, MI Y. Summary of research on new energy side energy storage optimization configuration technology[J]. Energy Storage Science and Technology, 2022, 11(10): 3257-3267. DOI: 10.19799/j.cnki.2095-4239.2022.0102
2	王一珺, 杜文娟, 王海风. 大规模风电汇集系统小干扰稳定性研究综述[J]. 电网技术, 2022, 46(5): 1934-1946. DOI: 10.13335/j.1000-3673.pst.2021.1217.
	WANG Y J, DU W J, WANG H F. Review on small signal stability analysis of large-scale wind power collection system[J]. Power System Technology, 2022, 46(5): 1934-1946. DOI: 10.13335/j.1000-3673.pst.2021.1217.
3	曹又敏. 基于多能互补的园区综合能源系统优化调度[D]. 西安: 西安理工大学, 2020. DOI: 10.27398/d.cnki.gxalu.2020.000816.
	CAO Y M. Optimal scheduling of comprehensive energy system in park based on multi-energy complementarity[D]. Xi'an: Xi'an University of Technology, 2020. DOI: 10.27398/d.cnki.gxalu.2020.000816.
4	PENG Z X, CHEN X D, YAO L M. Research status and future of hydro-related sustainable complementary multi-energy power generation[J]. Sustainable Futures, 2021, 3: 100042. DOI: 10. 1016/j.sftr.2021.100042.
5	杨勇平, 段立强, 杜小泽, 等. 多能源互补分布式能源的研究基础与展望[J]. 中国科学基金, 2020, 34(3): 281-288. DOI: 10.16262/j.cnki.1000-8217.2020.03.006.
	YANG Y P, DUAN L Q, DU X Z, et al. Research foundation and prospect on distributed energy system with the complementation of multiple energy sources[J]. Bulletin of National Natural Science Foundation of China, 2020, 34(3): 281-288. DOI: 10.16262/j.cnki. 1000-8217.2020.03.006.
6	GERAMI MOGHADDAM I, SAEIDIAN A. Self scheduling program for a VRB energy storage in a competitive electricity market[C]//2010 International Conference on Power System Technology. October 24-28, 2010, Zhejiang, China. IEEE, 2010: 1-6. DOI: 10. 1109/POWERCON.2010.5666037.
7	OMRAN W A, KAZERANI M, SALAMA M M A. Investigation of methods for reduction of power fluctuations generated from large grid-connected photovoltaic systems[J]. IEEE Transactions on Energy Conversion, 2011, 26(1): 318-327. DOI: 10.1109/TEC. 2010.2062515.
8	KAABECHE A, BELHAMEL M, IBTIOUEN R. Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system[J]. Energy, 2011, 36(2): 1214-1222. DOI: 10.1016/j.energy.2010.11.024.
9	SFIKAS E E, KATSIGIANNIS Y A, GEORGILAKIS P S. Simultaneous capacity optimization of distributed generation and storage in medium voltage microgrids[J]. International Journal of Electrical Power & Energy Systems, 2015, 67: 101-113. DOI: 10.1016/j.ijepes.2014.11.009.
10	MAHDAVI S, HEMMATI R, JIRDEHI M A. Two-level planning for coordination of energy storage systems and wind-solar-diesel units in active distribution networks[J]. Energy, 2018, 151: 954-965. DOI: 10.1016/j.energy.2018.03.123.
11	徐林, 阮新波, 张步涵, 等. 风光蓄互补发电系统容量的改进优化配置方法[J]. 中国电机工程学报, 2012, 32(25): 88-98, 14. DOI: 10.13334/j.0258-8013.pcsee.2012.25.017.
	XU L, RUAN X B, ZHANG B H, et al. An improved optimal sizing method for wind-solar-battery hybrid power system[J]. Proceedings of the CSEE, 2012, 32(25): 88-98, 14. DOI: 10.13334/j.0258-8013.pcsee.2012.25.017.
12	祝荣, 陈俊清, 宋伟, 等. 风光储一体化综合能源系统柔性调度策略[J]. 太阳能, 2022(5): 67-76. DOI: 10.19911/j.1003-0417.tyn 20220324.02.
	ZHU R, CHEN J Q, SONG W, et al. Flexible scheduling strategy for integrated energy systems with wind-pv-energy storage[J]. Solar Energy, 2022(5): 67-76. DOI: 10.19911/j.1003-0417.tyn 20220324.02.
13	郭进, 陆运章, 张佳亮, 等. 适用于青藏高原地区的风光柴互补能源系统的优化设计[J]. 太阳能, 2022(1): 55-61. DOI: 10.19911/j.1003-0417.tyn20201022.03.
	GUO J, LU Y Z, ZHANG J L, et al. Optimal design of wind-pv-diesel hybrid energy system suitable for Qinghai-Tibet plateau[J]. Solar Energy, 2022(1): 55-61. DOI: 10.19911/j.1003-0417.tyn 20201022.03.
14	李彦哲, 郭小嘉, 董海鹰, 等. 风/光/储微电网混合储能系统容量优化配置[J]. 供电系统及其自动化学报, 2020, 32(6): 123-128. DOI: 10.19635/j.cnki.csu-epsa.000322.
	LI Y Z, GUO X J, DONG H Y, et al. Optimal capacity configuration of wind/PV/storage hybrid energy storage system in microgrid[J]. Proceedings of the CSU-EPSA, 2020, 32(6): 123-128. DOI: 10. 19635/j.cnki.csu-epsa.000322.
15	尹青, 杨洪耕, 马晓阳. 考虑多重不确定参数的配电网概率无功优化[J]. 供电系统保护与控制, 2017, 45(7): 141-147. DOI: 10.7667/PSPC160503.
	YIN Q, YANG H G, MA X Y. Probabilistic reactive power optimization for distribution network considering multiple uncertainties[J]. Power System Protection and Control, 2017, 45(7): 141-147. DOI: 10.7667/PSPC160503.
16	尹青, 杨洪耕, 马晓阳. 含大规模风电场的电网概率无功优化调度[J]. 电网技术, 2017, 41(2): 514-520. DOI: 10.13335/j.1000-3673.pst.2016.0720.
	YIN Q, YANG H G, MA X Y. Probabilistic optimal reactive power dispatch of power grid with large-scale wind farm integration[J]. Power System Technology, 2017, 41(2): 514-520. DOI: 10.13335/j.1000-3673.pst.2016.0720.
17	梅书凡, 檀勤良, 代美. 考虑风光出力季节性波动的储能容量配置[J]. 供电工程技术, 2022, 41(4): 51-57. DOI: 10.12158/j.2096-3203.2022.04.007.
	MEI S F, TAN Q L, DAI M. Energy storage capacity configuration considering seasonal fluctuation of wind and photovoltaic output[J]. Electric Power Engineering Technology, 2022, 41(4): 51-57. DOI: 10.12158/j.2096-3203.2022.04.007.
18	张歆蒴, 黄炜斌, 王峰, 等. 大型风光水混合能源互补发电系统的优化调度研究[J]. 中国农村水利水电, 2019(12): 181-185, 190. DOI: 10.3969/j.issn.1007-2284.2019.12.037.
	ZHANG X S, HUANG W B, WANG F, et al. Research on the optimal scheduling of large wind-PV-hydro hybrid energy compl ementary power generation system[J]. China Rural Water and Hydropower, 2019(12): 181-185, 190. DOI: 10.3969/j.issn.1007-2284.2019.12.037.
19	黄文龙, 葛文超, 任洪波, 等. 全可再生能源多能互补系统优化配置与运行探索[J]. 太阳能学报, 2024, 45(5): 351-359. DOI: 10.19912/j.0254-0096.tynxb.2023-0002.
	HUANG W L, GE W C, REN H B, et al. Exploration of optimal configuration and operation for all-renewable multi-energy complementary systems[J]. Acta Energiae Solaris Sinica, 2024, 45(5): 351-359. DOI: 10.19912/j.0254-0096.tynxb.2023-0002.
20	邵志芳, 张东强. 基于合约负荷曲线的多能互补供电系统容量优化配置[J]. 电网技术, 2021, 45(5): 1757-1767. DOI: 10.13335/j.1000-3673.pst.2020.0236.
	SHAO Z F, ZHANG D Q. Capacity configuration optimization of multi-energy complementary power system based on contract load curve[J]. Power System Technology, 2021, 45(5): 1757-1767. DOI: 10.13335/j.1000-3673.pst.2020.0236.
21	吴克河, 周欢, 刘吉臻. 大规模并网型风光储发电单元容量优化配置方法[J]. 太阳能学报, 2015, 36(12): 2946-2953. DOI: 10.3969/j.issn.0254-0096.2015.12.015.
	WU K H, ZHOU H, LIU J Z. Capacity allocation optimization method of large scale grid connected wind-pv-battery generation unit[J]. Acta Energiae Solaris Sinica, 2015, 36(12): 2946-2953. DOI: 10.3969/j.issn.0254-0096.2015.12.015.
22	谭岭玲. 多能互补型微电网规划配置和优化运行研究[D]. 哈尔滨: 哈尔滨工业大学, 2021. DOI: 10.27061/d.cnki.ghgdu.2021.002215.
	TAN L L. Study on planning and optimal operation of multi-energy complementary microgrid[D]. Harbin: Harbin Institute of Technology, 2021. DOI: 10.27061/d.cnki.ghgdu.2021.002215.
23	MALEKI A, ASKARZADEH A. Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system[J]. International Journal of Hydrogen Energy, 2014, 39(19): 9973-9984. DOI: 10.1016/j.ijhydene.2014.04.147.
24	李淼. 分布式能源系统3E效益综合评价研究[D]. 大连: 大连理工大学, 2015.LI M. Study on comprehensive evaluation of 3E benefit of distributed energy system[D]. Dalian: Dalian University of Technology, 2015.
25	LI M, MU H L, LI H N. Analysis and assessments of combined cooling, heating and power systems in various operation modes for a building in China, Dalian[J]. Energies, 2013, 6(5): 2446-2467. DOI: 10.3390/en6052446.
26	韩鑫. 分布式能源系统构造及建模研究[D]. 太原: 太原理工大学, 2015.HAN X. Research on construction and modeling of distributed energy system[D]. Taiyuan: Taiyuan University of Technology, 2015.
27	孙雯雯, 徐玉杰, 丁捷, 等. 高原高寒地区可再生能源与储能集成供能系统研究[J]. 储能科学与技术, 2019, 8(4): 678-688. DOI: 10.12028/j.issn.2095-4239.2019.0040.
	SUN W W, XU Y J, DING J, et al. An energy system for the integration of renewable energy with energy storage in a frigid plateau region[J]. Energy Storage Science and Technology, 2019, 8(4): 678-688. DOI: 10.12028/j.issn.2095-4239.2019.0040.
28	王乐莹. 多孔炭在铅炭电池负极中的作用机制研究[D]. 北京: 北京科技大学, 2017.WANG L Y. Study on the mechanism of porous carbon in the negative electrode of lead-carbon battery[D]. Beijing: University of Science and Technology Beijing, 2017.
29	包金鹏. 启停用铅炭储能体系的研究[D]. 长春: 吉林大学, 2020. DOI: 10.27162/d.cnki.gjlin.2020.007201.
	BAO J P. Study on activation and deactivation of lead-carbon energy storage system[D]. Changchun: Jilin University, 2020. DOI: 10.27162/d.cnki.gjlin.2020.007201.
30	梅简, 张杰, 刘双宇, 等. 电池储能技术发展现状[J]. 浙江供电, 2020, 39(3): 75-81. DOI: 10.19585/j.zjdl.202003012.
	MEI J, ZHANG J, LIU S Y, et al. Development status of battery energy storage technology[J]. Zhejiang Electric Power, 2020, 39(3): 75-81. DOI: 10.19585/j.zjdl.202003012.
31	李杰才. 石墨烯基新型多孔材料作为铅炭电池负极添加剂的研究[D]. 南宁: 广西大学, 2021. DOI: 10.27034/d.cnki.ggxiu. 2021. 000237.
	LI J C. Study on graphene-based novel porous materials as anode additives for lead-carbon batteries[D]. Nanning: Guangxi University, 2021. DOI: 10.27034/d.cnki.ggxiu.2021.000237.
32	LI M, MU H L, LI N, et al. Optimal option of natural-gas district distributed energy systems for various buildings[J]. Energy and Buildings, 2014, 75: 70-83. DOI: 10.1016/j.enbuild.2014.01.051.
33	SHEN H T, ZHANG H L, XU Y J, et al. Multi-objective capacity configuration optimization of an integrated energy system considering economy and environment with harvest heat[J]. Energy Conversion and Management, 2022, 269: 116116. DOI: 10.1016/j.enconman.2022.116116.
34	中国气象局气象信息中心气象资料室, 清华大学建筑技术科学系. 中国建筑热环境分析专用气象数据集[M]. 北京: 中国建筑工业出版社, 2005.
35	MEI F, ZHANG J T, LU J X, et al. Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations[J]. Energy, 2021, 219: 119629. DOI: 10.1016/j.energy.2020.119629.
36	王晓海. 基于综合能源协同优化的智慧园区容量配置研究[D]. 北京: 华北电力大学, 2020. DOI: 10.27140/d.cnki.ghbbu.2020.000516.
	WANG X H. Research on capacity allocation of smart park based on comprehensive energy collaborative optimization[D]. Beijing: North China Electric Power University, 2020. DOI: 10.27140/d.cnki.ghbbu.2020.000516.

项目	平段	高峰	低谷
购电/(CNY/kWh)	0.6	0.9	0.3
售电/(CNY/kWh)	0.36	0.36	0.36
天然气/(CNY/m³)	2.45	2.45	2.45

项目	参数	数值
燃气轮机	余热回收率	0.5
	发电效率	0.3
	余热制热效率	0.45

燃气锅炉	制热效率	0.9

电锅炉	制热效率	0.95

储能单元	充电效率	0.9
	放电效率	0.9
	SOC_max	0.8
	SOC_min	0.2

天然气	碳排放因子	0.22 kg/kWh

电网	碳排放因子	0.968 kg/kWh

设备	参数	数值
光伏发电机组	初始投资成本	2400 CNY/kW
	运行成本	0.03 CNY/kWh
	使用寿命	20年

风力发电机组	初始投资成本	2800 CNY/kW
	运行成本	0.05 CNY/kWh
	使用寿命	20年

燃气轮机	初始投资成本	3000 CNY/kW
	运行成本	0.05 CNY/kWh
	使用寿命	20年

燃气锅炉	初始投资成本	1150 CNY/kW
	运行成本	0.04 CNY/kWh
	使用寿命	20年

电加热器	初始投资成本	1050 CNY/kW
	运行成本	0.08 CNY/kWh
	使用寿命	20年

储电单元	初始投资成本	2000 CNY/kWh
	运行成本	0.018 CNY/kWh
	使用寿命	10年

蓄热单元	初始投资成本	140 CNY/kWh
	运行成本	0.016 CNY/kWh
	使用寿命	10年

参数	数值
初始种群规模	100
最大迭代次数	100
交叉概率	0.9
变异概率	0.1
优秀种群比例	0.3
光伏机组容量配置边界	[0,300]
风力机组容量配置边界	[0,300]
储电单元容量配置边界	[0,800]
槽式太阳能集热器容量配置边界	[0,300]
燃气轮机容量配置边界	[0,500]
燃气锅炉容量配置边界	[0,500]
蓄热单元容量配置边界	[0,400]

配置方案	系统年成本	系统年碳排放量
经济性最佳方案	1	0
碳排放最佳方案	0	1
综合性最佳容量配置方案	0.5	0.5