Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort

نویسندگان

  • Kwang Ho Lee
  • Stefano Schiavon
چکیده

In building energy simulation, indoor thermal comfort condition, energy use and equipment size are typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during the heating season. The assumption is not reflected in practice and thus it may lead to errors. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing values above, indicating that the clothing insulation variation should be captured in building simulation software to obtain more reliable and accurate results. In this study, the impact of three newly developed dynamic clothing insulation models on the building simulation is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus version 6.0. The results showed that when the heating ventilation and air conditioning system (HVAC) is controlled based on indoor temperature the dynamic clothing models do not affect indoor operative temperatures, energy consumption and equipment sizing. When the HVAC is controlled based on the PMV model the use of a fixed clothing insulation during the cooling (0.5 clo) and heating (1.0 clo) season leads to the incorrect estimation of the indoor operative temperatures, energy consumption and equipment sizing. The dynamic clothing models significantly (p < 0.0001) improve the ability of energy simulation tools to assess thermal comfort. The authors recommend that the dynamic clothing models should be implemented in dynamic building energy simulation software such as EnergyPlus. OPEN ACCESS Energies 2014, 7 1918

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Heat Transfer, Environmental Benefits, and Social Cost Analysis of Different Insulation Methods by Considering Insulation Disadvantages

In this paper, the thermal performance of four common insulators in two internal and external insulation systems is investigated for the ASHRAE setpoint range by applying detailed numerical simulation and Anti-Insulation phenomenon. Anti-Insulation phenomenon and consequent extra load on the HVAC system can occur following the thermal insulation of a building if proper temperature setpoint is n...

متن کامل

Model Predictive Control for Mid-Size Commercial Building HVAC: Implementation, Results and Energy Savings

The paper presents field demonstration results from the implementation of a model predictive control formulation to optimize the operation of a variable volume, dual-duct, multi-zone HVAC unit serving an existing mid-size commercial building. This full-scale study is used to estimate the benefits of advanced building control technologies that can be integrated during a retrofit. The predictive ...

متن کامل

Study of thermal performance of building roofs in the city of Tehran

The design of a building can provide the highest thermal comfort in the interior without any mechanical equipment and save energy to a large extent. The roof of a building is an important part for thermal loss. This research studies the thermal performance of 14 conventional roof structures in Tehran city by using designbuilder 4.5. It is found that the polystyrene block performs best compared ...

متن کامل

Neural Network based HVAC Predictive Control

This paper addresses the problem of controlling Heating Ventilation and Air Conditioning (HVAC) systems with the purpose of maintaining a desired thermal comfort level, whilst minimizing the electrical energy required. Using a pilot installation, in the University of Algarve, Portugal, a Model Based Predictive Control (MBPC) strategy is used to control the HVAC equipment. The thermal comfort is...

متن کامل

Automatic HVAC Control with Real-time Occupancy Recognition and Simulation-guided Model Predictive Control in Low-cost Embedded System

Intelligent building automation systems can reduce the energy consumption of heating, ventilation and air-conditioning (HVAC) units by sensing the comfort requirements automatically and scheduling the HVAC operations dynamically. Traditional building automation systems rely on fairly inaccurate occupancy sensors and basic predictive control using oversimplified building thermal response models,...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014