暖通空调
能源消耗
空调
能源管理
冷负荷
阿什拉1.90
峰值需求
电
需求响应
控制(管理)
基线(sea)
汽车工程
能量(信号处理)
工程类
模拟
计算机科学
可靠性工程
机械工程
电气工程
统计
数学
人工智能
物理
海洋学
气象学
地质学
标识
DOI:10.1016/j.jobe.2020.101869
摘要
In recent years, various heating, ventilation, and air-conditioning (HVAC) control strategies have been proposed to reduce buildings’ energy consumption and environmental impacts. Due to different research designs, it is impossible to directly compare the reported performance of these strategies and determine the best approach for operating real-world buildings. To fill this gap, this research uses a well-validated building simulation model to holistically evaluate the performance of 12 existing HVAC cooling strategies in reducing the total cooling energy use, peak demand, and cooling energy cost. The findings include: i) The ON/OFF and night setup control strategies could lead to even higher energy cost than the 24/7 operation baseline; ii) demand-limiting control methods performed well across the three energy performance metrics and achieved the highest energy reduction ratios ranging from 9.8% to 10.5%; iii) precooling and extended precooling reduced the peak load most significantly by 15.4% and 21.4%, respectively; and iv) the resistive-capacitive (RC) network-based precooling optimization resulted in the highest electricity cost savings with reduction ratios of 16.6% and 12.9%, based on the two common price schedules. Besides providing valuable insights to the research community, this study offers a practical method to help building operators analyze and select the best HVAC control strategies for their energy management goals.
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