Design of a fuzzy set environment comfort system

Dounis, Anastasios I.; Santamouris, M.; Lefas, C.C.; Argiriou, Athanassios A.

doi:10.1016/0378-7788(94)00902-v

Cited by 69 publications

(29 citation statements)

References 7 publications

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“…Dounis et al introduced a fuzzy logic controller (FLC) using a set of fuzzy rules for PMV control [70]. They used calculated PMV and ambient temperature values as controller inputs in order to determine auxiliary heating, cooling and opening angle of the windows.…”

Section: Comfort Controlmentioning

confidence: 99%

Energy Efficiency of Distributed Environmental Control Systems

Khalifa¹,

Işık²,

Dannenhoffer³

2011

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Wilcoxen of the Syracuse University Maxwell School, and three engineering graduate students who performed the analytical and computational work under the supervision of Professors Khalifa, Isik, Dannenhoffer and Wilcoxen, namely: Mr. Ian Cosden who developed and implemented the thermal model of the building and its environmental control system; Mr. Seckin Ari who developed the comfort model and performed the optimization and control analyses; and Mr. Xuanhang (Simon) Zhang, who developed the CFD model of intra-and inter-cubicle air and energy transport and refined the thermal and comfort models accordingly.Report No. DOE\ER63694-1 iii A. ABSTRACTRecent research has indicated that allowing building occupants to customize their own local environment increases satisfaction and workplace performance. However, concern about the possible increase of energy consumption associated with the implementation of distributed localized environmental control has limited the widespread adoption of such systems. 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 occupantselected "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. The model also allowed us to study the effect of the thermal resistance of the partitions between adjacent workstations, which can have a significant influence on the energy cost (3% to 78% increas...

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Section: Comfort Controlmentioning

confidence: 99%

Energy Efficiency of Distributed Environmental Control Systems

Khalifa¹,

Işık²,

Dannenhoffer³

2011

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“…At this regard, although some interesting works related to the artificial intelligence topics have shown that fuzzy systems and neural networks can simultaneously control both requirements, in this way contributing to reduction of energy consumption and guarantying acceptable indoor comfort conditions [14,15,16,17,18], we need to better matching the purposes of the energy saving and of the indoor thermal conditions for people. In other words, we must dispose of effective and simple tools of analysis that contemporary take into account both requirements in the building and HVAC design process.…”

Section: Introductionmentioning

confidence: 99%

Comparing different control strategies for indoor thermal comfort aimed at the evaluation of the energy cost of quality of building

Calvino¹,

Gennusa²,

Morale³

et al. 2010

Applied Thermal Engineering

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The rapid improvement in the standard of living requires more detailed and sophisticated methods of evaluating comfort conditions. But, maintaining thermal comfort conditions in confined environments may require complex regulation procedures and the proper management of heating, ventilating and air conditioning (HVAC) systems. In turn, the requirements for indoor thermal comfort do not necessarily coincide with those of energy saving purposes, which in the last years are

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“…This is an important step towards an IoT approach for creating smart buildings. The majority of recent developments in BEMS have followed the advances made in computer technology, telecommunications and information technology [48], and hence capable of achieving energy optimisation by guaranteeing a satisfactory performance level with reduced energy consumption.…”

Section: Introductionmentioning

confidence: 99%