Development and validation of online models with parameter estimation for a building zone with VAV system

The energy consumption by building heating, ventilating, and air conditioning (HVAC) systems has evoked increasing attention to promote energy efficient control and operation of HVAC systems. Application of advanced control and operation strategies requires robust online system models. In this study, online models with parameter estimation for a building zone with a variable air volume system, which is one of the most common HVAC systems, are developed and validated using experimental data. Building zone temperature and zone entering air flow are modeled based on physical rules and only the measurements that are commonly available in a commercial building are used. Various validation experiments were performed using a real-building test facility to examine the prediction accuracies for system outputs. Using the online system models with parameter estimation, the prediction errors for all validation experiments are less than 0.28 °C for temperature outputs, and less than 84.9 m³/h for air flow outputs. The online models can be further used for local and supervisory control, as well as fault detection applications.     

Real-time determination of optimal indoor-air condition for thermal comfort,air quality and efficient energy usage

For building, “surroundings” that effect on indoor-air condition change with respect to the time. Without proper determination of the desired indoor-air condition to heating, ventilating and air-conditioning (HVAC) system, it may not be feasible to provide simultaneously occupants with thermal comfort and acceptable air quality with efficient energy consumption all the time. This paper presents an alternative methodology of real-time determination of optimal indoor-air condition for HVAC system in order to achieve such total requirements. Predicted mean vote (PMV), CO₂ concentration and cooling/heating load are used as parameter indices for thermal comfort, indoor-air quality and energy consumption respectively. The performance index of the HVAC system is then defined by summation in terms of square errors between those actual parameter indices and their desired values. This performance index is to be systematically minimized by a gradient-based technique in order to yield optimal indoor-air condition for HVAC system. A case study was chosen in 24 h operating HVAC system of a single-storey building by determining indoor-air temperature, indoor-air humidity, indoor-air velocity, and air-ventilation rate. The experiment results show that the proposed methodology can be efficiently implemented in the real-time determination of indoor-air condition to HVAC system that maintains PMV and CO₂ concentration close to the desired levels with less energy consumption when compared to those from the conventional approach.     

空调系统控制的一种动态优化技术

为建筑空调系统控制提出一项动态的优化技术。在一个指定期间内，运用该算法，能得到使目标函数(例如运行成本或者峰值能耗)最小的房间温度曲线。该算法也能给出HVAC设备的最佳开、关时间。本文包括建筑热特性的模拟，优化技术和实例研究。     

An exergy application for analysis of buildings and HVAC systems

The paper presents an extended method for exergy analysis of buildings and Heating Ventilation Air Conditioning (HVAC) systems, according to an energy demand build-up model from the building side to the energy supply side. The HVAC systems comprise a thermal energy emission and control system, a thermal distribution system, an electricity distribution system and an energy conversion system. Energy and exergy that are required by a building and a HVAC system are posed into the external part and classified by different forms of energy carriers. The external part is out of the boundary of the study. The method is illustrated with an office building equipped with low-temperature heating and high-temperature cooling systems situated in the Netherlands. Thermal exergy and thermal energy demands of the building and thermal energy and thermal exergy losses occurring in the HVAC systems are discussed. The building and the HVAC systems to be considered meet standard Dutch energy performance regulations. Nevertheless their overall exergy efficiencies are low in both cases (17.15% and 6.81% subsequently). The exergy analysis also pinpoints that the thermal energy emission and control system and the energy conversion system are the main causes of the exergy inefficiencies in the heating and cooling cases, respectively.     

夏热冬冷地区办公建筑降低供暖空调能耗的技术路径

以上海地区某办公建筑为例,基于EnergyPlus能耗模拟,探讨了围护结构性能提升和暖通空调系统优化这2条节能技术路径对夏热冬冷地区办公建筑降低供暖空调全年能耗的有效性.结果 表明:围护结构性能提升的节能潜力较小,经济性较差;单纯提高围护结构保温隔热性能并不能保证降低建筑年耗冷量,应综合分析全年供热供冷能耗确定围护结构...     

Integrated energy performance modeling for a retail store building

This paper presents an integrated energy performance modeling approach that considers heat and mass transfer through building envelope, HVAC (heating, ventilation, and air conditioning) and refrigeration systems of a retail store building with limited measured data. The internal heat gains/losses were estimated based on an Extended Kalman Filter. The simulation coupling strategy among room top units (RTUs), refrigeration display cases and zones is based on the ping-pong coupling strategy. The integrated model was validated against measured data from June to August, 2011. The results show that temperature prediction is within the ±1.5°C error band and the RTU electricity energy use prediction is within the ±10% error band. The difference between measured and simulated annual electricity consumption from the refrigeration system is 3%. Based on further analysis and diagnostics, deviations of model predictions from measured data were found to be partially due to the faults in the RTUs. Such deviation accounts for a 4% saving of the total building electrical energy consumption.     

基于ANN的绿色办公建筑HVAC系统运行能耗预测

办公建筑中暖通空调系统(HVAC系统)的运行能耗占总能耗比例较高。随着绿色建筑的大力推广,准确预测绿色办公建筑HVAC系统能耗是建筑运行优化的关键。研究以天津市某绿色办公建筑为研究对象,根据绿色办公建筑G中的HVAC系统——地源热泵系统和空调通风系统能耗的实际监测数据,建立了基于人工神经网络的能耗预测模型。研究结果表明,建立的分类多层感知器神经网络预测模型预测精度最好,仅基于气象参数及时间能够精确的预测建筑HVAC系统的小时能耗,为我国绿色办公建筑的设计和运行优化提供科学支持。     

用变速泵和变速风机代替调节用风阀水阀

通过５个工程实例，探讨在供热空调系统中利用变速风机和变速泵代替调节用风阀水阀实现风和水系统的调节的可能性，分析表明，这样做可以节省运行能耗，同时改善系统的调节品质，系统的初投资一般也不会增加。水泵和风机能耗约占供热空调系统总能耗的４０％，这些能耗中的１／３左右被各种调节阀门所消耗，但这样大的代价并没有换来好的调节效果，反而导致系统中许多问题发生。     

Economic evaluation of HVAC systems with ice storage designed using an optimization technique

Thermal energy storage (TES) is recognized as an important technique for energy management in heating, ventilation and air conditioning (HVAC) systems. This paper discusses the economic aspects of the optimal design for such systems. The model for optimal design so determines the sizes of the main components of the system - namely the chiller and the storage tank - that the system's life cycle cost is minimal. The model is based on linear programming and is implemented in a computer program for HVAC systems with ice storage. This paper demonstrates that the optimal sizes of chiller and storage tanks differ from those selected using traditional techniques. It emphasizes the cost-effectiveness of the optimally designed system and also includes a sensitivity analysis pertaining to the economic feasibility of such systems under different economic conditions.     

Regression analysis of high-rise fully air-conditioned office buildings

The building energy simulation computer program DOE-2 was used to carry out a parametric study of a generic high-rise air-conditioned office building in Hong Kong. A total of 28 design parameters related to the building load, the heating, ventilating and air-conditioning (HVAC) system and the HVAC refrigeration plant were found to correlate well with the predicted annual electricity consumption. Both linear and non-linear multiple regression techniques were used to develop regression models and energy equations for the prediction of annual electricity use. Twelve input design parameters (six from building load, four from HVAC system and two from HVAC refrigeration plant) were considered to be the most significant design variables and were used in the energy prediction equations. It is hoped that the resulting models and energy equations can be used as a simplified design tool for comparing the relative thermal and energy performance of different design schemes during the early design stage. This paper presents the methodology and the development work, and discusses the findings.     

Application of multicriteria analysis in designing HVAC systems

The present paper discusses a study which aims to develop a method for choosing and managing in the best possible way heating, ventilating and air conditioning (HVAC) systems in new and existing buildings. The method utilises a combination of two analysis’ tools, the multicriteria decision-making and the building simulation towards the direction of a holistic assessment of HVAC systems. In order to evaluate the method, a series of HVAC systems are considered for installing in an office building and the multicriteria method Electre III is applied for their selection. The results show that the proposed model allows the classification of alternative technical solutions concerning the HVAC's design, taking into consideration economic, energy and environmental criteria as well as criteria of users’ satisfaction. Finally, the study also indicates that when applying the sustainability concept in the building sector, and especially in the HVAC systems, this should concern the overall socioeconomic costs.     

试论温和地区暖通空调节能设计

总结了温和地区民用建筑暖通空调工程设计实践经验,结合当地实际情况和建筑节能技术的发展,提出了有关温和地区特殊气候条件下暖通空调节能设计的一些初步构想,强调负荷计算和方案比选先行,强化全空气系统的应用,积极采用适宜当地气候与资源条件的节能技术。     

Multi-floor building heating models in MATLAB and Modelica environments

Buildings are one of the largest energy consumers in the world.In northern countries,buildings consume most of the energy for space heating owing to the predominating cold climate conditions.Today there is a trend to use Building Energy Management Systems(BEMS)in buildings to make the indoor environment more comfortable and to utilise energy in a more efficient way.Currently,BEMS lack a building heating model,and the control is often based on temperature zones.Integration of a good building heating model with BEMS may assist in monitoring the heating of buildings in an optimal way while saving energy.Hence,the goal is to develop a model that can be applied in on-line control with acceptable performance and accuracy.This article covers multi-floor physics-based building heating modelsdeveloped in MATLAB and Modelica environments.The Modelica model uses the model components from Modelica Buildings Library and is more complex than the MATLAB model.The applicability of the two models in on-line control in BEMS principally depends on the accuracy of the predictions and prediction time.The prediction accuracy of both models is satisfactory while the Modelica model is robust.With the used computational power,the MATLAB model provides faster results compared to the Modelica model.More real-time experiments are needed for both models,and they can be applied in on-line control,depending on the model simplicity,available computational power and real-time segments in the system.In addition,the methodology used in the MATLAB model development is application independent and can be implemented in different natures of building configurations.     

Life-cycle carbon and cost analysis of energy efficiency measures in new commercial buildings

Energy efficiency in new building construction has become a key target to lower nation-wide energy use. The goals of this paper are to estimate life-cycle energy savings, carbon emission reduction, and cost-effectiveness of energy efficiency measures in new commercial buildings using an integrated design approach, and estimate the implications from a cost on energy-based carbon emissions. A total of 576 energy simulations are run for 12 prototypical buildings in 16 cities, with 3 building designs for each building-location combination. Simulated energy consumption and building cost databases are used to determine the life-cycle cost-effectiveness and carbon emissions of each design. The results show conventional energy efficiency technologies can be used to decrease energy use in new commercial buildings by 20-30% on average and up to over 40% for some building types and locations. These reductions can often be done at negative life-cycle costs because the improved efficiencies allow the installation of smaller, cheaper HVAC equipment. These improvements not only save money and energy, but reduce a building’s carbon footprint by 16% on average. A cost on carbon emissions from energy use increases the return on energy efficiency investments because energy is more expensive, making some cost-ineffective projects economically feasible.     

绿色建筑理念在中国(泰州)科学发展观展示馆暖通空调设计中的体现

以中国(泰州)科学发展观展示馆项目为例,从暖通空调设计师的视角,介绍了《绿色建筑评价标准》在节能与能源利用和室内环境质量方面的各项细则要求。以绿色建筑三星级为目标,结合当地的气候特点,运用了地埋管地源热泵、变频调速、新风热回收、置换通风、多元通风等多项实用的节能技术,探讨了绿色建筑技术在暖通空调系统设计中的应用。     

A novel approach for building occupancy simulation

Building occupancy is an important basic factor in building energy simulation but it is hard to represent due to its temporal and spatial stochastic nature. This paper presents a novel approach for building occupancy simulation based on the Markov chain. In this study, occupancy is handled as the straightforward result of occupant movement processes which occur among the spaces inside and outside a building. By using the Markov chain method to simulate this stochastic movement process, the model can generate the location for each occupant and the zone-level occupancy for the whole building. There is no explicit or implicit constraint to the number of occupants and the number of zones in the model while maintaining a simple and clear set of input parameters. From the case study of an office building, it can be seen that the model can produce realistic occupancy variations in the office building for a typical workday with key statistical properties of occupancy such as the time of morning arrival and night departure, lunch time, periods of intermediate walking-around, etc. Due to simplicity, accuracy and unrestraint, this model is sufficient and practical to simulate occupancy for building energy simulations and stochastic analysis of building heating, ventilation, and air conditioning (HVAC) systems.     

Applying a multi-objective optimization approach for Design of low-emission cost-effective dwellings

Modern buildings and their HVAC systems are required to be not only energy-efficient but also produce fewer economical and environmental impacts while adhering to an ever-increasing demand for better environment. Research shows that building regulations which depend mainly on building envelope requirements do not guarantee the best environmental and economical solutions. In the current study, a modified multi-objective optimization approach based on Genetic Algorithm is proposed and combined with IDA ICE (building performance simulation program). The combination is used to minimize the carbon dioxide equivalent (CO₂-eq) emissions and the investment cost for a two-storey house and its HVAC system. Heating/cooling energy source, heat recovery type, and six building envelope parameters are considered as design variables. The modified optimization approach performed efficiently with the three studied cases, which address different summer overheating levels, and a set of optimal combinations (Pareto front) was achieved for each case. It is concluded that: (1) compared with initial design, 32% less CO₂-eq emissions and 26% lower investment cost solution could be achieved, (2) the type of heating energy source has a marked influence on the optimal solutions, (3) the influence of the external wall, roof, and floor insulation thickness as well as the window U-value on the energy consumption and thermal comfort level can be reduced into an overall building U-value, (4) to avoid much of summer overheating, dwellings which have insufficient natural ventilation measures could require less insulation than the standard (inconsistent with energy saving requirements) and/or additional cost for shading option.     

Contrasting the capabilities of building energy performance simulation programs

For the past 50 years, a wide variety of building energy simulation programs have been developed, enhanced and are in use throughout the building energy community. This paper is an overview of a report, which provides up-to-date comparison of the features and capabilities of twenty major building energy simulation programs. The comparison is based on information provided by the program developers in the following categories: general modeling features; zone loads; building envelope and daylighting and solar; infiltration, ventilation and multizone airflow; renewable energy systems; electrical systems and equipment; HVAC systems; HVAC equipment; environmental emissions; economic evaluation; climate data availability, results reporting; validation; and user interface, links to other programs, and availability.     

Method for modelling space conditioning aggregated daily load curves: Application to a university building

Physically based load modelling methodologies have been widely developed and used because of their ability to predict the energy load dynamic response. Most building energy programs predict energy consumption and energy system performance through a whole building energy simulation as well as a global analysis of building thermal processes and heating, ventilation and air-conditioning (HVAC) system performance. A different approach is presented in this paper by introducing a new method for modelling the daily load profile of a group of air-conditioning systems. This method is based on the simulation of a single HVAC system, a set of end-use electrical measurements, and a detailed walk-through and energy audit. The basic methodology allows deducing the aggregated load of a group of space conditioning devices by the addition of the daily simulation of each individual physical system. As an application, the space conditioning daily demand curve of a university building is studied and results are presented.     

基于人工神经网络的变风量空调控制系统

研究了变风量空调系统神经网络预测优化控制方法,优化指标考虑了舒适性和耗能量,舒适性指标取PMV指标,耗能量包括风机和冷水泵能耗。系统的控制量为送风风速和冷水流量,被控参数为空调区域的温湿度,采用预测滚动优化控制算法训练多层前向神经网络,然后将其作为优化反馈控制器来求解变风量暖通空调系统的优化解,并在运行中实时预测空调区域的负荷。仿真结果表明,采用此方法,在模型环境、负荷参数变化的情况下,既可以达到节能的要求,又可以使空调区域的温湿度保持在舒适范围内。