The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions

被引:20
作者
Gao, Datong [1 ]
Zhao, Bin [1 ]
Kwan, Trevor Hocksun [1 ]
Hao, Yong [2 ]
Pei, Gang [1 ]
机构
[1] Univ Sci & Technol China, Dept Thermal Sci & Energy Engn, Hefei 230027, Peoples R China
[2] Chinese Acad Sci, Inst Engn Thermophys, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Solar energy; Space heating; District energy; Energy management; DISTRICT ENERGY SYSTEM; THERMAL-ENERGY; RESIDENTIAL BUILDINGS; SEASONAL STORAGE; PERFORMANCE ANALYSIS; DYNAMIC SIMULATION; COOLING SYSTEMS; NEURAL-NETWORK; OPTIMIZATION; DEMAND;
D O I
10.1016/j.apenergy.2022.119326
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
Building space heating has led to tremendous energy consumption globally. The mismatch between fluctuating solar energy resources and stochastic space heating load shall be solved to realize the transition from fossil energy to solar energy for space heating. In the spatial aspect, the discrepancy of solar energy resources in different regions is considerable and the heating load is also varying with the climate type, population density, and so on. In the temporal aspect, the seasonal and diurnal solar energy resource usually has an opposite trend to the actual space heating demand. The spatial and temporal mismatch between solar energy and heating load cause inefficient solar energy utilization and prejudice the decarbonization goal. This work is focused on the status and solutions to this phenomenon, and the state-of-art from the perspective of both the supplement and demand sides are reviewed, as well as the extensive policy outlook for mitigating the mismatch problem in solar space heating applications. Finally, the future investigation suggestions and research gaps on this scientific problem are concluded from this work.
引用
收藏
页数:16
相关论文
共 113 条
[21]   Space-Confined Seeded Growth of Black Silver Nanostructures for Solar Steam Generation [J].
Chen, Jinxing ;
Feng, Ji ;
Li, Zhiwei ;
Xu, Panpan ;
Wang, Xiaojing ;
Yin, Wenwen ;
Wang, Mozhen ;
Ge, Xuewu ;
Yin, Yadong .
NANO LETTERS, 2019, 19 (01) :400-407
[22]   Prediction of the total day-round thermal load for residential buildings at various scales based on weather forecast data [J].
Chi, Fang'ai ;
Xu, Liming ;
Pan, Jiajie ;
Wang, Ruonan ;
Tao, Yekang ;
Guo, Yuang ;
Peng, Changhai .
APPLIED ENERGY, 2020, 280
[23]   Demand side management of heat in smart homes: Living-lab experiments [J].
Christensen, Morten Herget ;
Li, Rongling ;
Pinson, Pierre .
ENERGY, 2020, 195
[24]  
Dhabi A., 2021, World energy transitions outlook: 1.5C pathway
[25]   Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning [J].
Du, Yan ;
Zandi, Helia ;
Kotevska, Olivera ;
Kurte, Kuldeep ;
Munk, Jeffery ;
Amasyali, Kadir ;
Mckee, Evan ;
Li, Fangxing .
APPLIED ENERGY, 2021, 281
[26]   Seasonal storage and demand side management in district heating systems with demand uncertainty [J].
Egging-Bratseth, Ruud ;
Kauko, Hanne ;
Knudsen, Brage Rugstad ;
Bakke, Sara Angell ;
Ettayebi, Amina ;
Haufe, Ina Renate .
APPLIED ENERGY, 2021, 285
[27]   Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand [J].
Ehsan, Ali ;
Yang, Qiang .
APPLIED ENERGY, 2019, 235 :1277-1288
[28]   A novel decentralized platform for peer-to-peer energy trading market with blockchain technology [J].
Esmat, Ayman ;
de Vos, Martijn ;
Ghiassi-Farrokhfal, Yashar ;
Palensky, Peter ;
Epema, Dick .
APPLIED ENERGY, 2021, 282
[29]   Development of data-driven models for prediction of daily global horizontal irradiance in Northwest China [J].
Feng, Yu ;
Cui, Ningbo ;
Chen, Yuxin ;
Gong, Daozhi ;
Hu, Xiaotao .
JOURNAL OF CLEANER PRODUCTION, 2019, 223 :136-146
[30]  
Finnish Meteorological Institute, About us