Comparison of the prediction accuracy of daily and monthly regression models for energy consumption in commercial buildings /
(daily models) or by regressing the monthly energy
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1996.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | (daily models) or by regressing the monthly energy average temperature during the operation period. Based on buildings are generally determined as the difference between consumption should be regressed versus the average ambient consumption versus the monthly average temperature (monthly daily energy consumption versus the daily average temperature developed for a midsize commercial building with (i) dual- different from the weather used for model development, the duct CAV and VAV systems, (ii) office and university errors for both daily and monthly regression models were as errors were identified as the difference between the energy high as 15%. However, the prediction error of daily hours per day, annual energy prediction errors of daily model. models use weather from a year very different from the models when the AHUs are operated 24 hours per day. When models). Since the post-retrofit weather is generally occupancy schedules, and (iii) different operating practices of monthly regression models were found to be in the same period. Most baseline models are developed by regressing the prediction error of the baseline model may be different from range as the error of the daily models. 2. When the AHUs regression models can be decreased to a range of 2% to 3% if regression models were found to be less than 1.4%. The errors results are summarized below: 1. When the AHUs operate 24 shut-down is performed during unoccupied hours, daily energy simulated by a calibrated simulation program when both temperature during operating hours to develop the baseline the daily average energy consumption is regressed versus the the energy consumption predicted using a baseline model and the fitting error. Daily and monthly baseline models were the measured energy consumption during the post retrofit The measured energy savings from retrofits in commercial these findings, we suggest use of daily or monthly regression use predicted by the regression models and the values using the weather of a mild weather year. The prediction weather year used to develop the regression model. The major were shut down during unoccupied periods, annual prediction |
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| Item Description: | "Major subject: Mechanical Engineering". Vita. |
| Physical Description: | xxi, 164 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references. |