Title

Short-Term Curtailment Of Hvac Loads In Buildings

Abstract

Rapidly increasing requirements placed on utilities to reduce peak loads has led to utility customer incentives to shift peak demand to non-peak times or reduce peak loads when notified by the utility that the grid is close to capacity. This paper investigates methods used to reduce building demand during a fixed time window near a utilities on-peak period in response to short-term notification (a few hours advanced notice) through computer simulations using EnergyPlus. The work presented in this paper was performed under the ASHRAE research project, 1390-RP. Two building types (office and retail) were defined using two equally viable construction types (light and heavy mass). The four resulting building construction models, combining building types and constructions, were simulated in five selected cities which represent a diverse range of climate conditions. The control strategies investigated in the project include lighting power density reductions, global thermostat setpoint setback control, chilled water temperature reset, and supply air temperature adjustment. Results from computer modeling were analyzed. Demand reductions associated with changes in the thermal mass were insignificant compared to those achieved with control strategies. The lighting power density reduction is effective and easily implemented. Higher percent reductions in demand were achieved for the smaller buildings and medium retail building which used the packaged HVAC system type with global thermostat setpoint setback control. The peak demand reductions that are achievable when two or more control strategies are combined vary between 12% and 34% and are dependent on building and HVAC system types. ©2012 ASHRAE.

Publication Date

1-1-2012

Publication Title

ASHRAE Transactions

Volume

118

Issue

PART 2

Number of Pages

467-474

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84872023380 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84872023380

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