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Journal of ZheJiang University (Engineering Science)  2024, Vol. 58 Issue (6): 1243-1254    DOI: 10.3785/j.issn.1008-973X.2024.06.014
    
Low-carbon optimal scheduling of integrated energy system considering multiple flexible resources
Haijun XING1(),Yujing YE1,Zheyuan LIU2,Weijian JIANG2,Wenbo ZHANG1,Shuxin TIAN1
1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
2. Jiaxing Power Supply Company, State Grid Zhejiang Electric Power Co. Ltd, Jiaxing 314000, China
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Abstract  

An integrated energy distributed low-carbon economic dispatch model that considered multiple flexible resources was proposed, aiming at the problem of insufficient system flexibility and low carbon of integrated energy systems (IES) with multiple parks. Firstly, the flexibility requirements of the system were analyzed, the IES flexibility margin constraints were proposed, and multiple flexibility resource models including carbon capture plants were constructed to make full use of the flexible operation mode of carbon capture plants. Second, ladder-type carbon trading was introduced to establish a two-tier scheduling model for the integrated energy system. The upper layer of the model aimed to minimize the cost of energy supply by energy suppliers, and the lower layer aimed to minimize the operating cost of energy operators consisting of energy hubs (EH). The model was solved by using the objective cascade analysis method to achieve the collaborative scheduling between the upper and lower layers of the energy supplier and energy service provider with respect to the characteristics of the multi-subject operation. Finally, the positive effect of the proposed model on enhancing the system flexibility and low carbon was verified through an arithmetic example consisting of IEEE30-node network, Belgium 20-node gas network and multiple energy hubs.



Key wordsintegrated energy      flexibility      carbon capture      carbon trading      analytical target cascading     
Received: 14 August 2023      Published: 25 May 2024
CLC:  TP 393  
Fund:  国家自然科学基金资助项目(52007112).
Cite this article:

Haijun XING,Yujing YE,Zheyuan LIU,Weijian JIANG,Wenbo ZHANG,Shuxin TIAN. Low-carbon optimal scheduling of integrated energy system considering multiple flexible resources. Journal of ZheJiang University (Engineering Science), 2024, 58(6): 1243-1254.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.06.014     OR     https://www.zjujournals.com/eng/Y2024/V58/I6/1243


含多种灵活性资源的综合能源系统低碳优化调度

针对含多园区的综合能源系统(IES)所面临的灵活性和低碳性不足的问题,提出考虑多种灵活性资源的综合能源分布式低碳经济调度模型. 分析系统的灵活性需求,提出IES灵活性裕度约束,并构建包含碳捕集电厂在内的多种灵活性资源模型,充分利用碳捕集电厂的灵活运行模式. 引入阶梯式碳交易,建立综合能源系统双层调度模型. 模型上层以能源供应商供能成本最小为目标,下层以由能量枢纽(EH)组成的能源运营商运行成本最小为目标. 针对多主体运营特性,利用目标级联分析法进行求解,实现能源供应商和能源服务商上下层协同调度. 通过由IEEE30节点电网、比利时20节点气网和多个能量枢纽组成的算例,验证所提模型对提升系统灵活性和低碳性的积极作用.


关键词: 综合能源,  灵活性,  碳捕集,  碳交易,  目标级联分析法 
Fig.1 Framework diagram of integrated energy system
Fig.2 Schematic diagram of flexibility analysis for integrated energy system
Fig.3 Schematic diagram of flexible operation of carbon capture power plants
Fig.4 Structure diagram of energy hubs
Fig.5 Flow chart of solution process using target cascade method
机组编号$ {P_{{\text{G}}i,\max }} $/
MW
$ {P_{{\text{G}}i,\min }} $/
MW
$ {{{a}}_i} $/
(元·MW?2)
$ {{{b}}_i} $/
(元·MW?1)
$ {{{c}}_i} $/元$ {e_{{\text{G}}i}} $/
(t·MW?1·h?1
13501000.014200750.8
2250500.02325012500.6
3150500.0692755000.5
Tab.2 Parameters of CCS power units
Fig.6 Structure diagram of integrated energy system
Fig.7 Load data of integrated energy system
物理量变量数值物理量变量数值
最大工作
状态系数
$ \alpha $1.05单位碳捕
集能耗
$ \lambda $/(MW·h·t?1)0.27
碳捕集效率$ \eta $0.9碳交易单价1$ {\lambda _{\text{1}}} $/(元·t?120
碳交易单价2$ {\lambda _2} $/元40碳交易单价3$ {\lambda _3} $/(元·t?160
热电联产电效率$ {\eta _{{\text{CHP,P}}}} $0.6热电联产热效率$ {\eta _{{\text{CHP,H}}}} $0.3
电转气效率$ {\eta _{{\text{P2G}}}} $0.6热泵系数$ {\eta _{{\text{HP}}}} $2.0
燃气锅炉效率$ {\eta _{{\text{GB}}}} $0.7燃气轮机效率$ {\eta _{G{\text{T}}}} $0.6
风电波动系数$ {\lambda _{{\text{wind}}}} $0.09光伏波动系数$ {\lambda _{{\text{pv}}}} $0.17
Tab.1 Equipment parameters of integrated energy system
气源${Q_{w i,\max }}$/MW${Q_{w i,\min }}$/MW$ {\rho _j} $/(元·MW?1)
GW11 200600195
GW21 000500175
Tab.3 Parameters of gas source
场景${F_1}$/万元$ {f_{{\text{c}}{{\text{o}}_2}}} $/万元$ {f_{{\text{ccs}}}} $/万元${E_{\text{G}}}$ /t
场景1327.06.036.85212.1
场景2325.55.835.75449.3
场景3353.835.3070635.0
场景4321.0036.95432.1
Tab.4 Scheduling result of different scenarios
Fig.8 Linking-up load in scenario 1
Fig.9 Flexibility of supply and demand considering flexibility constraint in scenario 1
Fig.10 Flexibility of supply and demand without considering flexibility constraint in scenario 2
Fig.11 Relationship between flexibility safety margin and total cost
Fig.12 Energy consumption of carbon capture equipment in scenario 1
Fig.13 Volume of liquid in storage of carbon capture device in scenario 1
Fig.14 Sensitivity analysis of carbon trading price
Fig.15 Convergence process of analytical target cascading
优化算法Fs/万元Fp/万元tc/s
集中式328.4415.5203
KKT条件转换328.2415.3335
目标级联分析327.0416.7308
Tab.5 Comparison of cost and time consuming results of different optimization algorithms
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