Rufei Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Rufei Li has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Jianli Wang
Huadian Zhengzhou Mechanical Design Institute Co., Ltd., Zhengzhou 450001, China
1 shared publication Jiayin Zhu
1 shared publication- Junxi Gao1 shared publication
Mingyi Jing
1 shared publicationRuixin Li
1 shared publicationWeilin Li
1 shared publication
Latest Publications
- 23 March 2023
- Published by Elsevier in Renewable Energy
- Vol. 209, 71-84
Study of the optimal placement of phase change materials in existing buildings for cooling load reduction - Take the Central Plain of China as an example
- 23 March 2023
- Published by Elsevier in Renewable Energy
- Vol. 209, 71-84
Study of the optimal placement of phase change materials in existing buildings for cooling load reduction - Take the Central Plain of China as an example
- Open Access
Peak Load Shifting Control for a Rural Home Hotel Cluster Based on Power Load Characteristic Analysis
The large-scale rural home hotel clusters have brought huge pressure to the rural power grid. However, the load of rural home hotels not only has the inherent characteristics of rural residential buildings but is also greatly impacted by the occupancy rate, which is very different from conventional buildings. Therefore, the existing peak shifting strategies are difficult to apply to rural home hotels. In view of the above problems, this study took a typical visitor village in Zhejiang Province as the research object, which had more than 470 rural home hotels. First, through a basic information survey and power load data collection, the characteristics of its power load for heating, cooling and transition months were studied, and a “No Visitors Day” model was proposed, which was split to obtain the seasonal load curve for air conditioning. Then, combined with the characteristics of the air conditioning power load and the natural conditions of the rural house, a cluster control peak-load-shifting system using phase change energy storage was proposed, and the system control logic was determined and established. Finally, the collected power load data was brought into the model for actual case analysis to verify its feasibility and the effect of peak-load shifting. The results showed that due to the influence of the number of tourists, the electricity loads on weekends and holidays were higher, especially the electricity load of air conditioning equipment in the heating and cooling seasons. An actual case was simulated to verify the peak-shifting effect of the proposed regulation strategy; it was found that the maximum peak load of the cluster was reduced by 61.6%, and the peak–valley difference was 28.6% of that before peak shifting.
Open AccessPeak Load Shifting Control for a Rural Home Hotel Cluster Based on Power Load Characteristic Analysis
The large-scale rural home hotel clusters have brought huge pressure to the rural power grid. However, the load of rural home hotels not only has the inherent characteristics of rural residential buildings but is also greatly impacted by the occupancy rate, which is very different from conventional buildings. Therefore, the existing peak shifting strategies are difficult to apply to rural home hotels. In view of the above problems, this study took a typical visitor village in Zhejiang Province as the research object, which had more than 470 rural home hotels. First, through a basic information survey and power load data collection, the characteristics of its power load for heating, cooling and transition months were studied, and a “No Visitors Day” model was proposed, which was split to obtain the seasonal load curve for air conditioning. Then, combined with the characteristics of the air conditioning power load and the natural conditions of the rural house, a cluster control peak-load-shifting system using phase change energy storage was proposed, and the system control logic was determined and established. Finally, the collected power load data was brought into the model for actual case analysis to verify its feasibility and the effect of peak-load shifting. The results showed that due to the influence of the number of tourists, the electricity loads on weekends and holidays were higher, especially the electricity load of air conditioning equipment in the heating and cooling seasons. An actual case was simulated to verify the peak-shifting effect of the proposed regulation strategy; it was found that the maximum peak load of the cluster was reduced by 61.6%, and the peak–valley difference was 28.6% of that before peak shifting.