| dc.description.abstract | This thesis emphasizes on VAV (Variable Air Volume) ventilation systems and, in particular, modelling and simulation of such systems. It touches a number of important HVAC related issues. Demand controlled ventilation (DCV) is a topic which naturally follows VAV, and has thus been outlined. New control strategies have been developed and tested by simulation, and some existing strategies have been reviewed.
The thesis has eight chapters. The introduction is followed by a literature survey on demand controlled ventilation. The purpose of the second chapter was to look into what had been done in the past, and to define the state of the art on DCV. Energy savings are also reported. The third chapter breifly treats common HVAC control issues.
The most important objective of chapter 4 was to develop new models and/or modify existing models suitible for VAV components and other components frequently used in VAV systems. To gain reusability, to increase accessibility and to provide an overview of the models presented and reviewed in this chapter, model libraries have been put together. They are categorized as follows:
• Flow/pressure model library
• Thermal model library
• Mass transfer (contaminant) model library
• Controls model library
The flow/pressure model category embraces steady state models expressing the flow/pressure relationship of the most common components of a variable flow system. These components are, among others, fans dampers, ducts, elbows and branches. The models are mainly based on known pressure-flow relations, assuming in most cases fully turbulent flows. The thermal model category contains dynamic models of the most commonly used components in a VAV system. These components are, among other fans, ducts/pipes,coils, heat recovery equipment and a building/room. Most models are nonlinear due to the relationship between temperature and flow rate. Some of them hvae been adopted from other authors and modified for VAV systems, and some are new. The mass transfer model category contains both steady state and dynamic models of varios common components of a VAV system. Among these are a rotary heat recovery unit-leakage and crossover flow, duct transport delay and zonal room models. The control equipment model category contains models of VAV controls such as temperature and CO2 sensors, PID controllers and sequenced controllers.
Chapter five takes model validity into consideration. Evaluation of the performance of the following models agianst measurements and other available data have been conducted:
• Thermal heating coil model
• Thermal pipe model
• Room contaminant model
• Fan pressure model
• Solar radiation (thermal model)
Chapter 6 breifly treats numerical methods and the importance of filtering and buffering of data. The component models presented in chapter 4 can be assembled to very versatile simulation systems for investigation of VAV control issues, energy related issues and general HVAC issues. The simulation systems which have been put together during this work are comprehensive and very detailed, and have shown to be capable of reproducing real system behavior in a very realistic manner. Different control strategies have been investigated through various case studies, presented in chapter 7. These strategies involve the following control methods and variables:
• Constant supply air temperature control.
• Set point reset ( compensation) of the supply air temperature controller according to the outdoor temperature
• Thermostatic room temperature control
• CO2 DCV
• Temperature DCV
• decipol DCV
• Combined CO2 and temperature DCV
• Direct flow (fan speed) control.
• Static pressure difference control.
• Variable set point of fan static pressure difference.
CO2 has shown as a very distinct measure of occupancy ratio. However, CO2 DCV connot be based purely on CO2 considerations. Minimum flow rates must be determined from an assessment of air qauality, in the same manner as many standards and regulations do. The set point of control also must be given attention. A commonly used level is 1000 ppm. In many applications (offices, schools, kindergartens, sevice buildings etc.) 1000ppm will be too high for acceptable air quality. Controlling air quality by converting CO2 levels to occupancy ratios have shown advantageous.
Most simulaton case studies include computation of energy usage. Numbers of energy savings are provided as a percentage ratio of energy used by a specific DCV VAV system to the energy used by an identical CAV (constant air volume) system. The relationship between occupancy ratio and energy savings is very distinct. A generalization of the energy savings which can be obtained by using a VAV DCV system have shown to be difficult. Numerous factors and parameters affect the final result. | nb_NO |
