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This paper compares HVAC simulations between EnergyPlus and DOE-2.2 for data centers. The HVAC systems studied in the paper are packaged direct expansion air-cooled single zone systems with and without air economizer. Four climate zones are chosen for the study - San Francisco, Miami, Chicago, and Phoenix. EnergyPlus version 2.1 and DOE-2.2 version 45 are used in the annual energy simulations. The annual cooling electric consumption calculated by Energy- Plus and DOE-2.2 are reasonably matched within a range of -0.4% to 8.6%. The paper also discusses sources of differences between EnergyPlus and DOE-2.2 runs including cooling coil algorithm, performance curves, and important energy model inputs. [ABSTRACT FROM AUTHOR]

Ideally, whole-building energy simulation programs model all aspects of a building that influence energy use and thermal and visual comfort for the occupants. An essential component of the development of such computer simulation models is a rigorous program of validation and testing. This paper describes a methodology to evaluate the accuracy of whole-building energy simulation programs. The methodology is also used to identify and diagnose differences in simulation predictions that may be caused by algorithmic differences, modeling limitations, coding errors, or input errors. The methodology has been adopted by ANSI/ASHRAE Standard 140, Method of Test for the Evaluation of Building Energy Analysis Computer Programs (ASHRAE 2001α, 2004). A summary of the method is included in the 2005 ASHRAE Handbook—Fundamentals (ASHRAE 2005). This paper describes the ASHRAE Standard 140 method of test and its methodological basis. Also discussed are possible future enhancements to ASHRAE Standard 140 and related research recommendations. [ABSTRACT FROM AUTHOR]

This paper describes the development and evaluation of a simple algorithm for limiting peak electrical demand in buildings using building thermal mass. The control algorithm is intended to reduce electrical demand in response to utility critical peak pricing (CPP) signals or similar incentives and involves adjustment of zone temperature setpoints within comfort bounds. The demand-limiting potential and impact on utility costs for CPP rates were evaluated through simulation for representative small commercial buildings throughout California. In general, it is possible to achieve between 1 and 2 W/ft² (10.76 and 21.53 W/m²) of demand reduction for a four-hour demand-limiting period while keeping zone temperatures between 70°F and 78°F (21.1°C and 25.6°C). This represents a 30%–100% reduction in peak electrical requirements for air conditioning depending on the climate. For typical CPP utility rates, the impact of the demand-limiting strategy on operating costs is relatively small, with less than about $50 in annual savings per 1000 ft² (92.9 m²). Greater incentives may be necessary to encourage customers to respond to critical capacity shortages. Furthermore, CPP super-peak energy rates do not encourage customers to minimize their demand during CPP periods but, rather, encourage them to reduce their integrated energy usage over this period. A better incentive would involve imposing a high peak demand charge for CPP periods. [ABSTRACT FROM AUTHOR]

Improved IT technology makes possible real-time evaluation of energy use on the scale of an electric distribution network using common utility bills or interval data as a data source. However, the available data are faulty and require validation and estimation. Because of the large number (typically millions) of meters to be monitored on a daily basis for years, visual inspection and other techniques that rely on human intervention are not suitable. This paper discusses simple, automatable methods and algorithms to validate and estimate monthly utility bills, which continue to be the most ubiquitous form of energy use measurement. A new method to identify suspect or missing bills is presented, as well as a choice of methods for replacing the suspect or missing bill with the most likely estimate. [ABSTRACT FROM AUTHOR]