Multi-energy sharing optimization for a building cluster towards net-zero energy system

被引:16
作者
Gao, Hongjun [1 ]
Cai, Wenhui [1 ]
He, Shuaijia [1 ]
Jiang, Jun [2 ]
Liu, Junyong [1 ]
机构
[1] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
[2] State Grid Luzhou Power Supply Co, Luzhou 646000, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Building cluster; Multi-energy sharing; Net-zero energy index; Analysis target cascading; Benefit distribution; Shapley value; MANAGEMENT;
D O I
10.1016/j.apenergy.2023.121778
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the promotion of net-zero energy buildings, building users gradually face the realistic demand of net-zero energy. Multi-energy sharing is a crucial measure to further improve the scheduling efficiency of building cluster to realize net-zero energy. In this context, a multi-energy sharing optimization model for a building cluster towards a net-zero energy system is proposed. A decentralized energy system framework considering multi-energy sharing is established, which includes a building cluster operator and multiple buildings. The building resources (e.g., energy production, conversion and storage equipment) are also modelled. In addition, a flexible net-zero energy comprehensive index is proposed based on three evaluation indexes (e.g., cost, energy, and emission), which depends on users' demand and application scenarios. Then, the scheduling optimization model of the building cluster is decomposed into the optimization models of building users and the building cluster operator considering the net-zero energy goal. Moreover, the analysis target cascading method is adopted to realize the distributed coordination solution of the optimization models, and an improved Shapley value method is adopted to realize the benefit adjustment of the whole building cluster. Finally, the numerical result shows that the building cluster is closer to a net-zero energy system by multi-energy sharing. The overall economic benefit and the realization degree of net-zero energy are both improved. The influence of multi-energy sharing and net-zero energy indexes on scheduling optimization and benefit distribution are both discussed carefully.
引用
收藏
页数:20
相关论文
共 27 条
[1]  
Abdelghani H, 2021, WSEAS Trans Power Syst, V16
[2]   Distributed Augmented Lagrangian Method for Link-Based Resource Sharing Problems of Multiagent Systems [J].
Ananduta, Wicak ;
Nedic, Angelia ;
Ocampo-Martinez, Carlos .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2022, 67 (06) :3067-3074
[3]   An efficient and economical storage and energy sharing model for multiple multi-energy microgrids [J].
Cao, Wenzhi ;
Xiao, Jiang-Wen ;
Cui, Shi-Chang ;
Liu, Xiao-Kang .
ENERGY, 2022, 244
[4]   Optimal Meeting Scheduling in Smart Commercial Building for Energy Cost Reduction [J].
Chai, Bo ;
Costa, Alberto ;
Ahipasaoglu, Selin Damla ;
Yuen, Chau ;
Yang, Zaiyue .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (04) :3060-3069
[5]   Distributed control strategy for transactive energy prosumers in real-time markets [J].
Yin, Chen ;
Ding, Ran ;
Xu, Haixiang ;
Li, Gengyin ;
Chen, Xiupeng ;
Zhou, Ming .
Energy Conversion and Economics, 2022, 3 (01) :1-10
[6]   Game-based peer-to-peer energy sharing management for a community of energy buildings [J].
Cui, Shichang ;
Xiao, Jiang-Wen .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 123
[7]   A Scenario-Based Branch-and-Bound Approach for MES Scheduling in Urban Buildings [J].
Dan, Mainak ;
Srinivasan, Seshadhri ;
Sundaram, Suresh ;
Easwaran, Arvind ;
Glielmo, Luigi .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (12) :7510-7520
[8]   Green signalling effects in the market for energy-efficient residential buildings [J].
Fuerst, Franz ;
Oikarinen, Elias ;
Harjunen, Oskari .
APPLIED ENERGY, 2016, 180 :560-571
[9]   Optimal design of renewable energy solution sets for net zero energy buildings [J].
Harkouss, Fatima ;
Fardoun, Farouk ;
Biwole, Pascal Henry .
ENERGY, 2019, 179 :1155-1175
[10]   A coordinated control to improve performance for a building cluster with energy storage, electric vehicles, and energy sharing considered [J].
Huang, Pei ;
Lovati, Marco ;
Zhang, Xingxing ;
Bales, Chris .
APPLIED ENERGY, 2020, 268