1990Unpublished venueRequires access

Reducing energy costs and peak electrical demand through optimal control of building thermal storage

James E. Braun

Open publisher page 360 citations

Abstract

This paper describes an investigation into the use of building thermal capacitance as a means of reducing the operating costs associated with maintaining adequate comfort conditions in buildings (termed dynamic building control). The state of the building thermal storage can be controlled through variations of the zone temperatures over time within the thermal comfort region. The primary opportunities in varying zone setpoints in an optimal fashion are associated with shifting cooling loads from daytime to nighttime to (1) reduce peak electrical demands, (2) take advantage of low nighttime electrical rates, (3) offset mechanical cooling with free cooling at night, and (4) enhance equipment operation at more favorable part-load conditions. The approach utilized in this study was to apply dynamic optimization techniques to computer simulations of buildings and their associated cooling systems for a range of conditions in order to determine the maximum possible savings. Results indicate that both energy costs and peak electrical use can be significantly reduced through optimal structures. However, the cost savings depend upon several factors, including (1) utility rate structure, (2) part-load characteristics of the cooling plant and air-handling system, (3) weather, (4) the occupancy schedule, and (5) building thermal capacitance.

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What this paper is about

This paper describes an investigation into the use of building thermal capacitance as a means of reducing the operating costs associated with maintaining adequate comfort conditions in buildings (termed dynamic building control). The state of the building thermal storage can be controlled through variations of the zone temperatures over time within the thermal comfort region. The primary opportunities in varying zone setpoints in an optimal fashion are associated with shifting cooling loads from daytime to nighttime to (1) reduce peak electrical demands, (2) take advantage of low nighttime electrical rates, (3) offset mechanical cooling with free cooling at night, and (4) enhance equipment operation at more favorable part-load conditions. The approach utilized in this study was to apply dynamic optimization techniques to computer simulations of buildings and their associated cooling systems for a range of conditions in order to determine the maximum possible savings. Results indicate that both energy costs and peak electrical use can be significantly reduced through optimal structures. However, the cost savings depend upon several factors, including (1) utility rate structure, (2) part-load characteristics of the cooling plant and air-handling system, (3) weather, (4) the occupancy schedule, and (5) building thermal capacitance.

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Available abstract

This paper describes an investigation into the use of building thermal capacitance as a means of reducing the operating costs associated with maintaining adequate comfort conditions in buildings (termed dynamic building control). The state of the building thermal storage can be controlled through variations of the zone temperatures over time within the thermal comfort region. The primary opportunities in varying zone setpoints in an optimal fashion are associated with shifting cooling loads from daytime to nighttime to (1) reduce peak electrical demands, (2) take advantage of low nighttime electrical rates, (3) offset mechanical cooling with free cooling at night, and (4) enhance equipment operation at more favorable part-load conditions. The approach utilized in this study was to apply dynamic optimization techniques to computer simulations of buildings and their associated cooling systems for a range of conditions in order to determine the maximum possible savings. Results indicate that both energy costs and peak electrical use can be significantly reduced through optimal structures. However, the cost savings depend upon several factors, including (1) utility rate structure, (2) part-load characteristics of the cooling plant and air-handling system, (3) weather, (4) the occupancy schedule, and (5) building thermal capacitance.

Key concepts: Offset (computer science), Peak demand, Automotive engineering, Occupancy, Load shifting, Cooling load, Thermal energy storage, Environmental science

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