MITCHELL OTOMATIC MANUAL MANUAL

It uses building characteristics data from audit, energy use data and zone monitoring to get insight into the physical and operational characteristics of the building.

MITCHELL OTOMATIC MANUAL MANUAL

Manual calibration consists of iterative and pragmatic process that involves the fine tuning of the input variables in a trial and error procedure. At present the most used statistical indices for the evaluation of the calibration accuracy are relative MBE (Mean Bias Error), RMSE (Root Mean Square Error), CVRMSE (Coefficient of Variation of RMSE) and NRMSE (Normalized RMSE), defined as follows : However, calibration with large time granularity (annual basis) can produce very good results while on a monthly basis can be affected by much larger errors. Usually calibration at a small time scale (hourly of sub-hourly) results more difficult and time consuming than large scale such as annual and/or monthly rates. Typical variables that are involved in the calibration process are mainly energy consumption and indoor air temperature, for which simulated values are compared to measured ones on a specific time scale. Although this process can be considered essential for having reliable results, still few practitioners are capable to perform it. Calibration consists of an iterative process where model input is changed to reconcile the model output with the measured data.

Retrofit projects and operations management for buildings require accurate modelling that can be achieved through calibration. Considering the white box approach, many BEPS tools are available for example, TRNSYS, Energy Plus, DOE-2, ESPr, IDA ICE and for the most popular, accurate capabilities evaluations and comparisons have been made. Building energy performance simulation (BEPS) can be achieved using data driven (black box) or law driven (white box) models. Building modelling can then be used both as a diagnostic tool, to better understand the physics laws of the building, and as a prognostic tool to predict the building’s behaviour once the laws are known. The reduction of the energy consumption can be pursued if the energy distribution throughout the building is known and understood. Simulation can be used to estimate the energy consumption of a building and consists of the construction of a virtual model of the building that has to reproduce the behaviour of the real building as accurately as possible. This objective can be reached using two different and complementary approaches-measurements and simulations. Worldwide energy reduction will then benefit from the improvement of energy efficiency in buildings. Although both methods require high expertise from operators and showed good results in terms of accuracy, automatic calibration presents better performance and consistently helps with speeding up the procedure. Differences, advantages and disadvantages are evidenced applying both methods to a dynamic simulation model of a real office building in Rome, Italy. This paper aims to compare a manual calibration procedure with an automatic calibration method developed by the authors, coupling dynamic simulation, sensitivity analysis and automatic optimization using IDA ICE, Matlab and GenOpt respectively. Automatic calibration relies on mathematical and statistical methods that mostly use optimization algorithms to minimize the difference between measured and simulated data. Manual calibration consists of an iterative trial and error procedure that requires high skill and expertise of the modeler. Two approaches can be adopted-manual or automatic. High modelling accuracy can be achieved only through calibration. For this purpose, simulation models can be used both as diagnostic and prognostic tools, reproducing the behaviour of the real building as accurately as possible. Energy reduction can benefit from the improvement of energy efficiency in buildings.

Mitchell otomatic manual