A demand limiting strategy for maximizing monthly cost savings of commercial buildings

被引:40
作者
Sun, Yongjun [1 ]
Wang, Shengwei [1 ]
Huang, Gongsheng [1 ,2 ]
机构
[1] Hong Kong Polytech Univ, Dept Bldg Serv Engn, Kowloon, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Div Bldg Sci & Technol, Hong Kong, Hong Kong, Peoples R China
关键词
Peak demand reduction; Building energy; Demand prediction; Cost saving; Demand limiting algorithm; ENERGY; MODEL;
D O I
10.1016/j.enbuild.2010.07.018
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Monthly peak demand costs usually contribute greatly to the monthly electricity bills of commercial buildings. Peak demand limiting control, which gained substantial attention recently, is an efficient way to reduce it. Most of previous studies either focus on the daily peak demand reduction without taking account the related energy rise, or explore the relationship between energy rise and demand reduction only on a daily basis. Unlike the previous studies, a new demand limiting control strategy is proposed in this paper in order to maximize the monthly cost saving. The new strategy is realized as follows. At first step, a proper monthly demand threshold is identified. At second step, a specific approach, named as proportional-integral-derivative (PID) algorithm, is implemented to restrain the daily peak demand to the given threshold by adjusting the indoor room temperature set-point. The extended pre-cooling duration is also estimated at this step based on the difference between the predicted daily peak demand and the identified threshold. The results of case studies show that the proposed strategy can substantially reduce the monthly electricity cost. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:2219 / 2230
页数:12
相关论文
共 15 条
[1]   Real-time predictive supervisory operation of building thermal systems with thermal mass [J].
Chen, TY .
ENERGY AND BUILDINGS, 2001, 33 (02) :141-150
[2]  
Drees KH, 1996, HVAC&R RES, V2, P332
[3]   Energy and cost minimal control of active and passive building thermal storage inventory [J].
Henze, GP .
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2005, 127 (03) :343-351
[4]   Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements [J].
Lee, Kyoung-ho ;
Braun, James E. .
BUILDING AND ENVIRONMENT, 2008, 43 (10) :1755-1768
[5]   Evaluation of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements [J].
Lee, Kyoung-Ho ;
Braun, James E. .
BUILDING AND ENVIRONMENT, 2008, 43 (10) :1769-1783
[6]  
Massie D.D., 2004, ASHRAE T, V110, P361
[7]  
Seem JohnE., 1995, ASHRAE HVACR Research, V1, P21
[8]  
TRNSYS, 2004, TRNSYS 16 DOCUMENTAT
[9]   Simplified building model for transient thermal performance estimation using GA-based parameter identification [J].
Wang, SW ;
Xu, XH .
INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 2006, 45 (04) :419-432
[10]   An optimization-based approach for facility energy management with uncertainties [J].
Xu, J ;
Luh, PB ;
Blankson, WE ;
Jerdonek, R ;
Shaikh, K .
HVAC&R RESEARCH, 2005, 11 (02) :215-237