4.7 Article

Evaluation of a cost-responsive supply air temperature reset strategy in an office building

期刊

ENERGY AND BUILDINGS
卷 158, 期 -, 页码 356-370

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2017.10.017

关键词

Supply air temperature reset; Controls; Variable air volume; Demand based reset; Trim and respond; Model predictive control

资金

  1. California Energy Commission (CEC) at the University of California, Berkeley [PIR-12-026]
  2. Center for the Built Environment (CBE) at the University of California, Berkeley

向作者/读者索取更多资源

This paper describes a new supply air temperature control strategy for multi-zone variable air volume systems. We developed the strategy with the intent that it is simple enough to implement within existing building management systems. At 5-min intervals, the strategy estimates the cost of fan, heating and cooling energy at three different supply air temperatures (current, higher, lower), and chooses the one with the lowest cost as the setpoint. We then implemented this strategy in a seven floor, 13,000 m(2) office building and compared the energy costs to the industry best practice control strategy in a randomized (daily) controlled trial over a 6-month period. We showed that the new control strategy reduced total HVAC energy costs by approximately 29%, when normalized to the typical annual climate data for this location and operating only during typical office hours. These findings indicate that the current industry best practice control strategy does not find the optimal energy cost point under most conditions. This new control strategy is a valuable opportunity to reduce energy costs, at little initial expense, while avoiding more complex approaches, such as model predictive control, that the industry has been hesitant to adopt. We describe the new control strategy in language common to the industry (see sequence of operations included as supplemental material) so that readers may easily specify and implement this immediately, in new construction or controls retrofit projects. (C) 2017 Elsevier B.V. All rights reserved.

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