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# 42540_19 - CHAPTER 19 ENERGY ESTIMATING AND MODELING...

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19.1 CHAPTER 19 ENERGY ESTIMATING AND MODELING METHODS GENERAL CONSIDERATIONS .............................................. 19.1 Models and Approaches ........................................................... 19.1 Characteristics of Models ........................................................ 19.1 Choosing an Analysis Method ................................................. 19.3 COMPONENT MODELING AND LOADS ............................. 19.3 Calculating Space Sensible Loads ........................................... 19.3 Ground Heat Transfer .............................................................. 19.7 Secondary System Components ................................................ 19.9 Primary System Components ................................................. 19.12 SYSTEM MODELING ............................................................ 19.17 Overall Modeling Strategies .................................................. 19.17 Degree-Day and Bin Methods ................................................ 19.17 Correlation Methods .............................................................. 19.22 Simulating Secondary and Primary Systems ......................... 19.22 Modeling of System Controls ................................................. 19.23 Integration of System Models ................................................. 19.23 DATA-DRIVEN MODELING ................................................. 19.24 Categories of Data-Driven Methods ...................................... 19.24 Types of Data-Driven Models ................................................ 19.25 Examples Using Data-Driven Methods ................................. 19.30 Model Selection ...................................................................... 19.31 MODEL VALIDATION AND TESTING ................................. 19.31 Methodological Basis ............................................................. 19.32 Summary of Previous Testing and Validation Work ............... 19.33 NERGY requirements and fuel consumption of HVAC systems E directly affect a building’s operating cost and indirectly affect the environment. This chapter discusses methods for estimating energy use for two purposes: modeling for building and HVAC sys- tem design and associated design optimization ( forward model- ing ), and modeling energy use of existing buildings for establishing baselines and calculating retrofit savings ( data-driven modeling ). GENERAL CONSIDERATIONS MODELS AND APPROACHES A mathematical model is a description of the behavior of a sys- tem. It is made up of three components (Beck and Arnold 1977): 1. Input variables (statisticians call these regressor variables , whereas physicists call them forcing variables ), which act on the system. There are two types: controllable by the experimenter, and uncontrollable (e.g., climate). 2. System structure and parameters/properties , which provide the necessary physical description of the system (e.g., thermal mass or mechanical properties of the elements). 3. Output ( response , or dependent ) variables, which describe the reaction of the system to the input variables. Energy use is often a response variable. The science of mathematical modeling as applied to physical systems involves determining the third component of a system when the other two components are given or specified. There are two broad but distinct approaches to modeling; which to use is dictated by the objective or purpose of the investigation (Rabl 1988). Forward (Classical) Approach. The objective is to predict the output variables of a specified model with known structure and known parameters when subject to specified input variables. To ensure accuracy, models have tended to become increasingly com- plex, especially with the advent of cheap and powerful computing power. This approach presumes detailed knowledge not only of the various natural phenomena affecting system behavior but also of the magnitude of various interactions (e.g., effective thermal mass, heat and mass transfer coefficients, etc.). The main advantage of this approach is that the system need not be physically built to predict its behavior. Thus, this approach is ideal in the preliminary design and analysis stage and is most often used then.

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42540_19 - CHAPTER 19 ENERGY ESTIMATING AND MODELING...

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