热能储存
热质量
需求响应
暖通空调
灵活性(工程)
背景(考古学)
峰值需求
储能
负荷转移
热舒适性
工程类
环境科学
建筑工程
空调
工艺工程
电
热的
机械工程
电气工程
气象学
功率(物理)
古生物学
数学
量子力学
物理
统计
生物
生态学
作者
Yongbao Chen,Peng Xu,Zhe Chen,Hongxin Wang,Huajing Sha,Ying Ji,Shouxin Zhang,Qiang Dou,Sheng Wang
出处
期刊:Applied Energy
[Elsevier BV]
日期:2020-10-12
卷期号:280: 115956-115956
被引量:77
标识
DOI:10.1016/j.apenergy.2020.115956
摘要
Heating, ventilation, and air conditioning (HVAC) systems, combined with the internal thermal mass of buildings, have been deemed to be promising means of providing demand response (DR) resources, particularly for buildings with active energy storage systems. DR resources, such as peak-load reduction potential, can provide grid-responsive support resulting in a high degree of grid involvement and high flexible electricity demand. In the DR field, the potential of HVAC load flexibility has been considered in buildings. In the future smart buildings, it is important to take advantage of demand-side resources to achieve real-time energy supply–demand balance sustainably. In this context, DR potential and characteristics of buildings play a pivotal role in DR programs. However, few studies have investigated the internal thermal mass’s heat release and DR characteristics of buildings. Thus, a systematic experiment is conducted to study the DR potential and characteristics of internal thermal mass and active storage systems. The DR resources include the passive cooling storage from furniture, building envelope and an active water storage tank. Two DR control strategies, including pre-cooling and temperature resetting, are analyzed in this study. The experimental results show that the strategies are effective for short-term (0.5 h) and intermediate-term (2 h) DR programs. For a long-term DR program, active energy storage technology such as a water storage tank is required to satisfy the occupant's comfort requirements. Hence, we conclude that passive thermal mass and active storage systems should be simultaneously considered in practical DR programs for better DR implementation.
科研通智能强力驱动
Strongly Powered by AbleSci AI