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Abstract: Design engineers commonly oversize HVAC systems with the justification of needing a reasonable safety factor to manage periods more extreme than the specific design conditions. Unfortunately, the safety factor easily becomes excessive. The design engineers minimize their professional risk, and by doing so they are actually asking the building owner to pay an immediate penalty due to increased first cost of equipment and an ongoing penalty due to maintenance and energy use implications. The penalties associated with excessive safety factors are often not communicated to the client. This paper presents the results of a study of “rightsizing” rooftop HVAC systems. The study included intensive interviews with HVAC designers investigating the design process and extensive field measurement of rooftop units (RTUs) during peak cooling conditions. This paper focuses on defining the signature of oversizing, i.e. how to use the physical measurements to quantify the degree of oversizing of an RTU and how to estimate the penalty of oversizing in terms of energy consumption and peak electricity demand. Utility companies incentive programs have not yet identified mechanisms for incentivizing rightsizing of HVAC system. The methodology described in this paper can be used as the basis for such programs. [ABSTRACT FROM AUTHOR]

In practice, monthly temperature records play a major role calculating the heating and cooling degree-days of the air conditioner management in buildings. Classically, heating and cooling degree calculations are based on the comparison of outdoor temperature measurements with a standard level called the base temperature. Truncating the temperature series at a constant base temperature causes heating (deficits) and cooling (surpluses) degrees. Since outdoor temperature records are of random character, future predictions with probabilistic and statistical methods are convenient means for calculations. All previous methodologies in the literature are based on crisp logic with simple mathematical calculations. This paper proposes a new methodological approach by converting the actual temperature record probability distribution function (PDF) into a probabilistic standardized degree indicator (SDI) in normal (Gaussian) PDF form with zero mean and unit standard deviation. Furthermore, as a new evaluation methodology fuzzy logic inference calculations are provided. SDI is divided into seven classes, three for cooling, heating, and a single class for uncooled-unheated states. Heating and cooling degree changes according to SDI values are presented with crisp and fuzzy sets. The application of the methodology is made for Kadıköy urban area on the Asian side of Istanbul, Turkey. In the case of fuzzy set SDI air conditioned operation, it has been determined that there is cooling energy saving of approximately 25% compared to the crisp set. The same is true for the heating degree-day side. [ABSTRACT FROM AUTHOR]

Abstract: The large thermal time constant of thermally activated building systems (TABS) hampers communication between the system''s production and emission. Therefore, conventional building control strategies, typically using room temperature feedback, are unadapted to control thermal comfort efficiently. In this paper, measurement data and simulation results reveal that unadapted TABS control has a dramatic impact on overall energy performance. Measurements in a TABS building with room temperature feedback show the HVAC system switching between heating and cooling in a very short time frame. A simplified, generic room model is used to simulate, understand and evaluate this behaviour. For room temperature feedback control, only 45% of the cold and 15% of the heat produced actually controls room temperature. The remainder is stored in the TABS and exchanged between the heating and cooling system. Enlarging the heating-to-cooling set point band improves this ratio, while maintaining thermal comfort. On the other hand, night time operation control of the circulation pump, adapted to the TABS thermal time constant, eliminates this ‘unused’ energy completely. In this case, however, even with perfect heat gain forecasts, it is difficult to avoid room temperatures dropping below thermal comfort limits during initial office hours. Hence, a supplementary air-conditioning system seems inevitable. [Copyright &y& Elsevier]

Abstract: In the last decade a lot of research effort has been spent on identifying the effect of the urban climate on the energy performance of buildings and HVAC (heating ventilation and air conditioning) systems. In this paper a methodology is proposed to assess that effect by the exclusive use of modeled data. Particularly, by using a downscaling modeling procedure a process for the generation of weather files for energy calculations is achieved. From a non-hydrostatic weather model the urban climate of the city of Lisbon is simulated and via a weather generator climatic data files for the buildings’ simulation software are derived. The results on the energy behavior of a reference test cell for different sites inside the city of Lisbon are presented. [Copyright &y& Elsevier]