Energy Efficiency of Distributed Environmental Control Systems [electronic resource]
In this report, we present an analytical evaluation of the potential of occupant-regulated distributed environmental control systems (DECS) to enhance individual occupant thermal comfort in an office building with no increase, and possibly even a decrease in annual energy consumption. To this end we...
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Online Access |
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| Format: | Government Document Electronic eBook |
| Language: | English |
| Published: |
Washington, D.C. : Oak Ridge, Tenn. :
United States. Department of Energy. Office of Energy Research ; distributed by the Office of Scientific and Technical Information, U.S. Department of Energy,
2011.
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| Subjects: |
MARC
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| 245 | 0 | 0 | |a Energy Efficiency of Distributed Environmental Control Systems |h [electronic resource] |
| 260 | |a Washington, D.C. : |b United States. Department of Energy. Office of Energy Research ; |a Oak Ridge, Tenn. : |b distributed by the Office of Scientific and Technical Information, U.S. Department of Energy, |c 2011. | ||
| 300 | |a 3055KB : |b digital, PDF file. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
| 338 | |a online resource |b cr |2 rdacarrier. | ||
| 500 | |a Published through SciTech Connect. | ||
| 500 | |a 02/23/2011. | ||
| 500 | |a Khalifa, H. Ezzat; Isik, Can; Dannenhoffer, John F. III. | ||
| 513 | |a Final; |b 09/15/2003 - 09/14/2005. | ||
| 520 | 3 | |a In this report, we present an analytical evaluation of the potential of occupant-regulated distributed environmental control systems (DECS) to enhance individual occupant thermal comfort in an office building with no increase, and possibly even a decrease in annual energy consumption. To this end we developed and applied several analytical models that allowed us to optimize comfort and energy consumption in partitioned office buildings equipped with either conventional central HVAC systems or occupant-regulated DECS. Our approach involved the following interrelated components: 1. Development of a simplified lumped-parameter thermal circuit model to compute the annual energy consumption. This was necessitated by the need to perform tens of thousands of optimization calculations involving different US climatic regions, and different occupant thermal preferences of a population of ̃50 office occupants. Yearly transient simulations using TRNSYS, a time-dependent building energy modeling program, were run to determine the robustness of the simplified approach against time-dependent simulations. The simplified model predicts yearly energy consumption within approximately 0.6% of an equivalent transient simulation. Simulations of building energy usage were run for a wide variety of climatic regions and control scenarios, including traditional “one-size-fits-all” (OSFA) control; providing a uniform temperature to the entire building, and occupant-selected “have-it-your-way” (HIYW) control with a thermostat at each workstation. The thermal model shows that, un-optimized, DECS would lead to an increase in building energy consumption between 3-16% compared to the conventional approach depending on the climate regional and personal preferences of building occupants. Variations in building shape had little impact in the relative energy usage. 2. Development of a gradient-based optimization method to minimize energy consumption of DECS while keeping each occupant’s thermal dissatisfaction below a given threshold. The DECS energy usage was calculated using the simplified thermal model. OSFA control; providing a uniform temperature to the entire building, and occupant-selected HIYW control with a thermostat at each workstation were implemented for 3 cities representing 3 different climatic regions and control scenarios. It is shown that optimization allows DECS to deliver a higher level of individual and population thermal comfort while achieving annual energy savings between 14 and 26% compared to OSFA. The optimization model also allowed us to study the influence of the partitions’ thermal resistance and the variability of internal loads at each office. These influences didn’t make significant changes in the optimized energy consumption relative to OSFA. The results show that it is possible to provide thermal comfort for each occupant while saving energy compared to OSFA Furthermore, to simplify the implementation of this approach, a fuzzy logic system has been developed to generalize the overall optimization strategy. Its performance was almost as good as the gradient system. The fuzzy system provided thermal comfort to each occupant and saved energy compared to OSFA. The energy savings of the fuzzy system were not as high as for the gradient-optimized system, but the fuzzy system avoided complete connectivity, and the optimization did not have to be repeated for each population. 3. We employed a detailed CFD model of adjacent occupied cubicles to extend the thermal-circuit model in three significant ways: (a) relax the “office wall” requirement by allowing energy to flow between zones via advection as well as conduction, (b) improve the comfort model to account both for radiation as well as convection heat transfer, and (c) support ventilation systems in which the temperature is stratified, such as in underfloor air distribution systems. Initially, three-dimensional CFD simulations of several cubicle configurations, with an adjoining c.. | |
| 520 | 0 | |a Building Environmental Control; Distributed Control. | |
| 536 | |b FG02-03ER63694. | ||
| 650 | 7 | |a Accounting. |2 local. | |
| 650 | 7 | |a Advection. |2 local. | |
| 650 | 7 | |a Control Systems. |2 local. | |
| 650 | 7 | |a Convection. |2 local. | |
| 650 | 7 | |a Diffusers. |2 local. | |
| 650 | 7 | |a Energy Consumption. |2 local. | |
| 650 | 7 | |a Energy Efficiency. |2 local. | |
| 650 | 7 | |a Fuzzy Logic. |2 local. | |
| 650 | 7 | |a Heat Transfer. |2 local. | |
| 650 | 7 | |a Hvac Systems. |2 local. | |
| 650 | 7 | |a Occupants. |2 local. | |
| 650 | 7 | |a Office Buildings. |2 local. | |
| 650 | 7 | |a Radiations. |2 local. | |
| 650 | 7 | |a Stratification. |2 local. | |
| 650 | 7 | |a Thermal Comfort. |2 local. | |
| 650 | 7 | |a Thermostats. |2 local. | |
| 650 | 7 | |a Transients. |2 local. | |
| 650 | 7 | |a Optimization. |2 local. | |
| 650 | 7 | |a Urban Areas. |2 local. | |
| 650 | 7 | |a Ventilation Systems. |2 local. | |
| 650 | 7 | |a Energy Conservation, Consumption, And Utilization. |2 edbsc. | |
| 710 | 2 | |a Syracuse University. |4 res. | |
| 710 | 1 | |a United States. |b Department of Energy. |b Office of Energy Research. |4 spn. | |
| 710 | 1 | |a United States. |b Department of Energy. |b Office of Scientific and Technical Information. |4 dst. | |
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