Content uploaded by Arash Beizaee
Author content
All content in this area was uploaded by Arash Beizaee on May 23, 2017
Content may be subject to copyright.
A preview of the PDF is not available
Measuring and modelling the energy demand reduction potential of using zonal space heating control in a UK home
Abstract
Most existing houses in the UK have a single thermostat, a timer and conventional
thermostatic radiator valves to control the low pressure, hot water space heating
system. A number of companies are now offering a solution for room-by-room
temperature and time control in such older houses. These systems comprise of
motorised radiator valves with inbuilt thermostats and time control. There is currently
no evidence of any rigorous scientific study to support the energy saving claims of
these ‘zonal control’ systems.
This thesis quantifies the potential savings of zonal control for a typical UK home.
There were three components to the research. Firstly, full-scale experiments were
undertaken in a matched pair of instrumented, three bedroom, un-furbished, 1930s,
test houses that included equipment to replicate the impacts of an occupant family.
Secondly, a dynamic thermal model of the same houses, with the same occupancy
pattern, that was calibrated against the measured results. Thirdly, the experimental
and model results were assessed to explore how the energy savings might vary in
different UK climates or in houses with different levels of insulation.
The results of the experiments indicated that over an 8-week winter period, the
house with zonal control used 12% less gas for space heating compared with a
conventionally controlled system. This was despite the zonal control system resulting
in a 2 percentage point lower boiler efficiency. A calibrated dynamic thermal model
was able to predict the energy use, indoor air temperatures and energy savings to a
reasonable level of accuracy. Wider scale evaluation showed that the annual gas
savings for similar houses in different regions of the UK would be between 10 and 14%
but the energy savings in better insulated homes would be lower.
... Savings of 8-18% were found in a two-home study using a novel predictive controller [46] and rigorous experiments in a matched pair of test houses with synthetic occupancy [43] showed savings of around 12% [8]. Predictions using dynamic thermal simulation indicated that the absolute and percentage energy savings would be between 0.2 and 2.2 percentage points lower, in well-insulated dwellings, depending on location [7]. The costs of the zonal control systems when compared to the absolute energy cost savings produced long payback times, especially so in well-insulated homes [7,8]. ...
... Predictions using dynamic thermal simulation indicated that the absolute and percentage energy savings would be between 0.2 and 2.2 percentage points lower, in well-insulated dwellings, depending on location [7]. The costs of the zonal control systems when compared to the absolute energy cost savings produced long payback times, especially so in well-insulated homes [7,8]. In other UK modelling studies, energy savings of 10-15% [33] and 8-37% [12] have been reported. ...
... The gas data was mainly robust, though sometimes strings of zeroes were recorded. In these cases, the indoor air temperatures and the electricity demand profiles were examined, and, in a few cases, homes were eliminated from further analysis if the zeros could not be attributed to a household being away from home for example 7 . ...
Domestic zonal heating controls enable hydronic systems to heat rooms to different temperatures at different times. The first credible evidence known to the authors, of the in-use energy savings of such controls, is reported. The results and research methods are globally relevant.
The energy demands and room temperatures in 68, gas-heated, owner-occupied, semi-detached homes, in the English Midlands were monitored for a year before zonal controls were fitted in 37 of the homes prior to the second year of monitoring. The other homes retained the existing heating controls and so provided a matched (control) group. Surveys and questionnaires characterised the dwellings, heating systems and households.
In two thirds of the homes with zonal controls the annual gas demand decreased, in one third it increased. Overall, the mean gas demand decreased by 3.5% relative to the homes that retained their existing controls. Savings were achieved primarily by reducing bedroom temperatures, especially in the evenings.
Wireless, digital zonal controls are unlikely to provide an acceptable payback through reductions in energy bills at today’s prices, but they offer households the flexibility to react to time-of-use energy pricing.
A matched (control) group is essential for the reliable calculation of energy demand changes arising from interventions in occupied homes.
... For example, Cockroft et al. [11] simulated a UK semi-detached house and bungalow with different occupancy patterns, and found that multi-zone control could achieve 8-37% energy savings. Beizaee [7] studied a matched pair of British houses and found that over an 8-week winter period, the house with zonal control used 12% less gas for space heating compared to a conventionally controlled system. ...
... All data were collected during research work that is detailed in Beizaee et al. [2015] and Beizaee [2016]. ...
Building energy performance assessment based on in-situ measurements: Physical parameter identification. Annex 71. International Energy Agency. Energy in Building Communities Programme. August 2021 ISBN 9789075741094
https://bwk.kuleuven.be/bwf/projects/annex71/
In Subtask 3 ‘Physical Parameter Identification’ of the IEA EBC Annex 71 project we investigated methodologies to identify, in a way that is reproducible and repeatable, the performance of the fabric and systems of residential buildings that are in use, and for which we have limited monitoring data available. This is different from Subtask 2, as the identified performance indicators directly reflect actual physical parameters. To achieve the above, we apply statistical methods that are based on physical background knowledge.
The physical background is elaborated in Chapter 2. A complete heat balance is constructed as an umbrella that serves to encapsulate the different simplified models that are applied in this subtask. This reference allows us the clear pinpointing of the physical phenomena that are lumped into the estimated parameters, and to evaluate the impact of the model simplification on reliability.
The underlying pursuit that we set ourselves is to assess the building’s Heat Transfer Coefficient (HTC).
In Chapter 3 methods to determine HTC are established and further developed. Methods can be static, e.g. linear regression or energy signature, or dynamic, using e.g. ARX or stochastic state-space models. But they all consider simplified models of the investigated building. They also all use statistical modelling techniques to assess uncertainty and determine how accurate are the obtained performance indicators, and how confident we can be about them.
In Chapter 4 we review the different input parameters and corresponding statistical modelling approaches used to identify the simplified models from (limited) on site measured data. Although focus is on HTC, some methods identify additional physically relevant parameters, such as the solar aperture, efficiency of heating systems, airtightness, etc.
Four case studies have been selected and investigated in detail in this subtask. They consist of residential buildings that are in-use (by actual users or artificial users, i.e. automated heating and window opening). All of them are extensively monitored, and solid reference performance indicators are available. Moreover, in two of them intrusive well-controlled tests (e.g. co-heating tests) were performed. In Chapter 5 we will briefly introduce them, and refer the reader to more detailed instruction documents and data sources.
Chapter 6 explores the impact of the approaches that were outlined in Chapter 4 on the estimated physical parameters, and the related uncertainty. We zoom in on each significant term in the overarching heat balance laid out in Chapter 2, and apply different approaches that best represent these terms in a simplified way. The different approaches are tested on the four case studies. From this, we distil quality procedures and clear guidelines for building parameter identification.
Chapter 7 turns things around and focuses on obtaining optimal results for the case studies. For each case study, we apply the best possible approach to model those terms that prove most significant. For instance, for one particular case study, a combination of a beta-splines approach to model solar gains, and an explicit model of internal gains might prove optimal.
In Chapter 8 we make the step towards real life applications. Realistic measurement campaigns of five houses, with no additional energy usage monitoring other than smart meters, have been provided via the Technical Evaluation of SMETER Technologies (TEST) project, phase 2 of the UK. Only the raw data was provided and the target value (the reference value of the HTC) was unknown when performing the analysis. This offered the possibility to perform a blind test and validate the assumptions and guidelines develop in the previous chapters.
Finally, we summarise the overall general conclusions of the IEA EBC Annex 71 work on physical parameter identification in Chapter 9.
https://dynastee.info/wp-content/uploads/2021/09/EBC_Annex71-ST3_Physical-parameter-identification.pdf
... These checks should be done for representative rooms for all zone types, Roberti, et al. (2015). In most studies, acceptable absolute error recorded was in the range of ±1-2°C for most of the temperature data points (Booten & Tabares-Velasco, 2012;Royapoor & Roskilly, 2015;Ruiz, et al., 2016;Beizaee, 2016). Therefore, MAE of 1°C and RMSE of 1.5°C can be used as reasonable targets for air temperature calibration checks. ...
Buildings have a significant impact on the environment. Construction of buildings and their operation accounts for 36% of global final energy use and 40% of energy‐related carbon dioxide (CO2) emissions. Also, as per the 2019 International Energy Agency (IEA) and United Nations Environment Programme (UNEP) report, the building sector has a strong potential to provide long-term energy and greenhouse gas emission savings without high financial costs. Building performance simulation tools, ranging from steady-state calculations to dynamic simulation methods, can calculate the anticipated energy consumption of a building with adequate levels of accuracy. However, there is considerable evidence to suggest that buildings underperform post-completion when compared against the expected performance prediction during the design-stage. The difference between the actual operation and the design intent is termed the ‘performance gap’. While the energy performance gap in buildings is a well-known phenomenon, its in-use interpretation is quite vague. It is important to understand the basis of assumptions and protocols used in design-stage performance calculations to assess the causes of the performance gap. In the context of the performance gap, energy performance is generally the most emphasised. The gap, however, is not limited to energy – it also applies to indoor environmental quality (IEQ) parameters, such as temperature and air quality. Moreover, the pursuit of energy efficiency may have the unintended consequence of compromising IEQ, thereby requiring a comprehensive approach to performance assessment. It is therefore important to consider energy and IEQ performance issues together. This thesis contributes to an improved understanding, quantification and resolution of performance gap related issues by using a novel simulation-based approach that enables systematic identification and classification of the root causes of the performance gap. A new measurement and verification (M&V) framework that is underpinned by building performance simulation and calibration is proposed. A key aspect of this new methodological framework is the identification and separation of the three types of performance gaps because of: 1. Use of inappropriate design-stage calculation methods (such as those used for regulatory compliance), 2. Technical issues with the building, its systems and their operations, and 3. Operational changes that the building has gone through to meet its functional requirements. For the first type of performance gap, CIBSE TM54 (CIBSE, 2013a) already provides guidance to reduce the perceived gap and enable improved estimates of building performance during the design-stage. This thesis focuses on the understanding of operational-stage issues and their detailed causes, related to the second and third types of the performance gap. This thesis is the first study that systematically defines, identifies and separates, • the technical issues that cause the performance gap between design intent and actual operation, and • the deviations of operating conditions from the design that are driven by the building’s function and occupancy. This is achieved by integrating the conventional post-occupancy performance assessment approach with building performance modelling and evidence-based model calibration. Another addition to the conventional approach, explored in this study, is the incorporation of IEQ. The issue of IEQ is addressed in two ways: first, by using zonal temperatures for calibration cross-validation, and second, by assessing the energy-related unintended consequences of IEQ underperformance which may happen during building operations. The calibrated simulation models are operationally accurate virtual representation of the actual building and can help to isolate the performance issues and validate the findings. The new framework proposed in this thesis is better suited than conventional M&V protocols such as ASHRAE (American Society of Heating Refrigerating and Air Conditioning Engineers) Guideline 14 and IPMVP (International Performance Measurement and Verification Protocol). These conventional M&V protocols also propose a calibration-based approach, but they generally focus on broad statistical requirements and are not tied to a framework for a procedural verification of all the most important issues that can cause the performance gap. It is likely that using these conventional protocols will identify some key issues during investigations while leaving other potential issues hidden. The guidance on calibration and validation provided in conventional M&V protocols is commonly used for all model calibration exercises. However, the conventional protocols were developed for calculating energy savings in retrofit applications, and the calibration criteria defined in them are mainly for checking the accuracy of building-level energy use totals. The calibration criteria do not check for the uncertainty or the accuracy of dependent parameters, such as zone temperatures and other environmental outputs, which could cross-validate the model. Mathematically, meeting just the statistical criteria for building-level energy use totals in a highly parameterized model and an under-determined search space can lead to unrealistic solutions also being validated. To better support the calibration accuracy with the new proposed M&V framework, advanced model validation criteria have also been developed. New multi-level calibration criteria are proposed, which factors in data quantity, quality and granularity. In this new advanced validation criteria, the current industry standard of monthly energy use checks is the lowest level of calibration, with higher levels requiring detailed checks, using granular and disaggregated energy use. However, all levels of calibration require minimum dependent parameter checks, such as IEQ checks for typical zone temperatures. Dependent parameter checks are desirable in model calibration; however, current statistical criteria used for calibration are not suitable for these checks. Revised and new metrics and thresholds are proposed and explored in this thesis for use in advanced calibrated model validation checks. Beyond the use of IEQ parameters (e.g. zone temperatures) in model calibration, another area of focus of this thesis is the unintended IEQ underperformance captured during the monitoring. The scope of this assessment is limited to underperformance in IEQ parameters linked to achieving high energy efficiency objectives, thermal comfort and indoor air quality (IAQ). Amongst the various IEQ parameters, thermal comfort and IAQ have complex and dynamic interactions with buildings energy end-uses. Comprising of multiple factors, which are both subjective and empirical, thermal comfort and IAQ performances have a high interrelation with the energy performance objectives. Therefore, along with conventionally tracked parameters of temperature and CO2, additional IAQ parameters (not used during the calibration process), such as NO2, PM2.5 and PM10, are analysed to enhance the understanding of unintended energy-related IEQ underperformance. The new methodology proposed in this study is applied to five case study buildings across four building sectors – offices, schools, hospitals and apartment blocks. These buildings represent a large cross-section of the UK building stock and, therefore, can provide useful insights into the issues in the construction sector that drive the performance gap. While detailed performance assessment and advanced validation is done for all five case study buildings using the proposed framework, in one case study building the multi-level calibration checking criteria is also fully explored. Using this methodology on the various case study buildings, cross-sectoral lessons, related to root causes of the energy performance gap and applicable in the wider industry context, are uncovered. Linking to the three types of performance gaps mentioned earlier, analysis of the results shows that, in most of the case studies, some of the energy performance gap is the perceived gap (related to point 1: use of inappropriate design-stage calculation methods) or is because of operational changes (related to point 3: changes that the building has gone through to meet its functional requirements). However, the most critical cause of the gap is due to technical issues (related to point 2: issues with the building, its systems and their operations) identified across the case studies. These issues were either design errors, improper construction and installation, poor commissioning or shortcomings in building systems and the use of new low-carbon technologies. It was observed that long-term involvement (with responsibility for the operational performance) of the design and construction teams are effective in lowering performance gaps. Issues related to IEQ were also observed across the case studies, such as overheating risks and poor IAQ. These added to the existing knowledge of energy-related IEQ issues and highlighted the need to address IEQ simultaneously with energy through better design, advanced operational controls and by incorporating regular IEQ measurements as part of operations and maintenance protocols. The novel approach presented here builds a case to move building performance calculations towards an operational context, where design projections are done using advanced simulation and with a view of tracking the projections through to operation using measurable performance outcomes. Overall, the study shows the importance of the early involvement of all stakeholders and their accountability to minimise performance issues. Integrating the findings from the case studies, a case could be built for having IEQ performance objectives in energy performance contracts. This can mitigate the trade-offs of IEQ against energy performance that leads to unintended health consequences for occupants. Further, this work promotes a way of integrating dynamic thermal simulation in regular post-occupancy checking and management of buildings.
... Calibration of dynamic thermal models is commonly performed in the building energy research community (Beizaee, 2016;Bou-saada and Haberl, 1995;Coakley, 2014;Georgiou et al., 2013;Marini et al., 2014;Mustafaraj et al., 2014;P. Xu et al., 2013;Yoon et al., 2003). ...
Urban areas in the Hot Summer and Cold Winter (HSCW) zone in China are home to 8% of the world’s population. Existing residential buildings in the HSCW zone in China are cold in winter and overheat in summer, due to a lack of adequate building fabric and central space heating in response to current legislation. As living standards increase, the number of residential buildings with installed air conditioning (AC) systems is also growing, which leads to a sharp increase in energy consumption. Building retrofit plays a vital role in reducing energy consumption and carbon dioxide emissions while increasing occupants’ thermal comfort. This study aims to develop retrofit measures for urban residential buildings and quantify the potential annual space-conditioning energy savings with regards to kWh at a city scale in the HSCW zone in China.
A typical urban multi-storey residential building in Chongqing, a city in the HSCW zone of China, was used to develop a dynamic thermal model (DTM), following a systematic review to characterise building parameters. Then, a single flat was calibrated using indoor air temperature measured over one week. Afterwards, energy and thermal comfort performance was evaluated before and after energy saving retrofits using the calibrated DTM of the single flat, and twelve different flats location with regards to the building. To represent typical residential users, three types of households with different AC operating schedules were developed: high, medium, and low. After that, an optimum combination of retrofit measures able to reduce energy consumption and thermal discomfort of the typical building was selected for each of the seven retrofit measures accordingly: external wall insulation, roof insulation, double-glazed windows, air infiltration control, additional window overhang, enclosed communal staircase, and energy-efficient AC. Finally, a DTM of the typical building was created at nine levels of computational detail. The most computationally efficient DTM was then identified to devise twelve residential building archetypes, to quantify the energy reduction due to energy saving retrofits at a city scale for 321 residential buildings in Chongqing.
The results showed that a substantial amount of annual space-conditioning energy is required to maintain comfortable conditions for existing residential buildings in the HSCW zone. Despite a high energy consumption for comfort was theoretically required, results predicted that energy used was only 9.2 to 18.8 kWh/m2, depended on the use that was made of the AC system. As the predicted mean indoor air temperature in winter was 14°C and in summer was 29°C due to the occupants’ adaption to the environment. Not surprisingly, retrofitting these buildings was not cost-efficient, with a payback period of 56 years, when adaptive behaviour was considered. Yet, thermal comfort was improved significantly in winter and at the same time summertime overheating was prevented under the proposed retrofit measures. To evaluate large-scale residential energy saving retrofits, DTM with different level of computational detail were created, the most suitable DTM was used to wider applicability of outputs of the typical building; results showed that it reduced simulation time by 70% and achieved a 5% prediction difference of energy demand when compared to the case study building (DTM with the greatest level of computational detail).
The devised residential building archetypes predicted an annual 73% to 76% reduction for heating, 39% to 45% reduction for cooling, and 50% to 57% reduction for total energy consumption. At a city-scale for 321 residential buildings with built area of 4.07 million m2, 17 TWh of annual space-conditioning energy can be reduced if the proposed retrofit measures are employed. More importantly, the potential long-term energy savings do outweigh the cost, given the Chinese government pursuit of net-zero emissions by 2050.
Energy security, climate change and economic growth are matters of critical international importance in an effort to achieve a sustainable future. Energy consumption in buildings contributes to higher greenhouse gas emissions than the industrial or transportation sectors combined. In India, the energy in the residential sector accounts for almost 50% of the total energy consumption. The need for comfortable internal environments, healthy indoor air quality and the consequences of global warming are all contributing factors to the high reliance on mechanical cooling and ventilation systems. In recent years, financial growth and increase in disposable income in India, have accelerated purchases of such mechanical systems. In metropolitan cities of India with extreme climates (hot and dry, warm and humid), the use of these systems increases by 30% every year. This upward trend is likely to continue in response to occupants’ higher comfort expectations and the continuous increase of the outside temperature during the summer months due to climate change. This could further impact the climate and the electricity grid. Innovative solutions should establish reliable strategies for cooling purposes by utilizing the use of natural ventilation.
Mixed-mode buildings rely on both mechanical and natural systems to maintain comfortable conditions. Although the performance of mixed-mode buildings has already been studied and there is evidence for its positive impact on the reduction of energy demand, there is still a lack of knowledge on the best methods for controlling mixed-mode buildings. Today, the majority of the available algorithms for the control of mixed-mode systems are very simplistic and at a primitive stage of development. Typically, the control algorithms “make the decision” based on a predefined static set-point temperature, disregarding other important parameters, such as relative humidity, the position of windows and activity of occupants. Control algorithms that would account for a variety of parameters are of paramount importance to achieve energy savings whilst maintaining thermal comfort conditions.
The aim of this research was to investigate the impact on thermal comfort and energy savings of novel and sophisticated control algorithms in mixed-mode residential buildings in India.
Initially, it was important to identify all the control parameters that were important to be included in the control algorithms. Then the control algorithms were designed and presented in flow charts. To analyse the performance of the proposed control algorithms, computer simulations were performed, whilst a validation analysis was conducted to provide evidence of the validity of the control algorithms. Computer modelling comprised of co-simulations, using Dynamic Thermal Modelling (DTM) (EnergyPlus) and equation-based tools (Dymola using the Modelica language). The coupling of these was achieved using the Functional Mock-up Interface (FMI) for model exchange. The co-simulations enabled to examine the energy saving potential that can be achieved by the proposed control algorithms. In order to evaluate the ventilation performance of the proposed control algorithms, the ventilation rates and ventilation effectiveness of the systems were analysed using Computational Fluid Dynamics (CFD). This allowed the final analysis which included the evaluation of the ventilation performance of the control algorithms by calculating the ventilation effectiveness. To provide evidence of the proposed control algorithms and simulation approach, a validation study was done using data from an experimental chamber in India.
This research has contributed to the existing body of knowledge by providing four main conclusions concerning the design and control of mixed-mode ventilation and cooling systems: i) to deliver comprehensive guidelines on the design and control of mixed-mode buildings, and the ways in which the co-simulations can be implemented to improve the existing control algorithms that can be found in the literature; ii) the use of the co-simulations showed that the developed control algorithms, when dampers/windows and ceiling fans are used, can improve the predicted hours of thermal comfort by up to 1900h compared to the scenarios when the ceiling fans were turned off, while achieving up to 55% energy reduction depending on the city; iii) the CFD simulations predicted that cross ventilation with the maximum opening areas for windows and dampers in combination with the operation of the ceiling fans can dillute the contaminants and/or heat in the building resulting in comfortable internal environments resulting in heat removal effectiveness of 1.65; and iv) the accurate and validated control algorithms that were developed in this research can be used for any study that requires control of mixed-mode buildings regardless of the geometry of the building. The use of co-simulations provides great flexibility since the same control algorithms can be used in any geometry or building location without the need for any modification of the code.
Transitioning to more efficient and less carbon-intensive heating is a monumental policy challenge in the United Kingdom. However, very few households in the UK—and perhaps even elsewhere—have actual experience with state-of-the-art smart heating systems that may utilize enhanced control or feedback. Drawing from a unique sample of actual adopters of smart heating, this study closely examines the heating preferences, practices, and profiles of homes when they are given smarter heating systems. The study utilizes qualitative household data from the Energy System Catapult’s Living Laboratory of 100 smart homes in Birmingham (West Midlands), Bridgend (Wales), Manchester (Greater Manchester), and Newcastle (Northumberland). We examine the heating preferences and profiles of participants, with findings inductively organized around the themes of temperature, including tradeoffs between comfort, cost, and value; time, including the utility of heat scheduling; and space, including zonal heating controls. We also discuss patterns of learning, the emergence of environmental values, and issues of discomfort. We conclude by commenting on important distinctions between radiant and ambient heat, as well as between scheduled and on-demand heat. The main findings are 1) tradeoffs between comfort, value and cost occur when it comes to smart heating; 2) people want different numbers of warm hours in their homes at very different times; 3) households chose to heat different numbers of rooms; and 4) there are other non-monetary and non-functional aspects of smart heating that households value.
This paper aims to investigate the potential of advanced radiator controls to reduce space heating energy demand in dwellings. The study uses Dynamic Thermal Modelling (DTM) to compare the space heating energy consumption of dwellings with programmable Thermostatic Radiator Valves (TRVs) and dwellings with conventional TRVs.
Conventional TRVs can often lead to overheating or heating rooms when not required. Programmable TRVs can overcome these limitations and this study employs DTM software package, DesignBuilder to estimate the resultant heating energy savings in a
semi-detached dwelling. It is found that use of programmable TRVs can lead to space heating energy savings of up to 30%, without reducing thermal comfort of occupants.
Sensitivity analysis (SA) is usually carried out along with energy simulations to understand buildings performance and reduce their consumptions. The quality of their results mainly depends on thermal models and input data. Having accurate data about properties and operation conditions of buildings is difficult. In consequence, simulation inputs are affected by uncertainties that may have significant effects on outputs and are important to be considered. Law-driven detailed models are widely used. They ensure reliability and versatility but require a large number of input parameters.
Fundamentals; Sustainability; Legislation; The building in winter; The building in summer; Building energy and environmental modelling; Heating methods; Electric Storage heating; Indirect heating systems; Heat emitting equipment; Pumps & Pipeline Equipment and Water Treatment; Piping design; Boilers & Burners; Renewable Energy Sources; Combined heat and power; Fuels, storage and handling; Combustion emissions and chimneys; Ventilation; Air conditioning; Air distribution; Ductwork design; Fans and air treatment; Calculations for air conditioning; Refrigeration, chillers and heat pumps; Hot water supply systems; Noise control; Motor drives, starting methods and control; Controls and building management systems; Commissioning & Handover Management; Safety in Design; The building in operation. © 2008, Faber Maunsell. Published by Elsevier Ltd. All rights reserved.
A set of 'standard' dwellings, comprising a Detached House, a Semi-Detached House, a Bungalow, a Post-1919 Terrace, a Period Terrace and a Timber-Framed House is defined. The set can be seen to serve three main functions: 1) As a series of 'benchmark' buildings for which the predictions of different thermal prediction models could be tested. 2) As a series of example houses which, while they do fully cover all house types currently existing in the UK, are based on 'averages' of several types. 3) As an example of the level of detail needed to describe a building such that it can be modelled without the need for the modeller to make many assumptions. The dimensions, construction and thermo-physical properties of each house are given, together with casual gain information corresponding to two occupancy schedules. These may be considered as 'guide' values such that subsequent thermal modelling of the dwellings is possible and, while efforts have been made to make the information as representative as possible, should not be taken to be fully realistic. The design heat loss and radiator sizing for each house are also determined. The descriptions should be sufficient for modelling by most currently-available thermal models, and therefore represent a 'reference' set of building types, against which different models can be tested, and on which the effects of changing a design parameter (for example window area) can be tested.
In order to avoid rotted, icky, and stinky crawlspaces, crawlspaces must have plenty cross ventilation and good drainage. A code-ventilation, continuous impermeable ground cover gives an excellent drainage, however it still a mess. Addressing these issues, there are solutions offered including old crawlspaces, old crawlspace temperatures, insulated crawlspace temperatures, moisture dynamics, warming the wood, and vapor barrier.
Calibrated simulation is the process of using an existing building simulation computer program and "tuning" or calibrating the various inputs to the program so that observed energy use matches closely with that predicted by the simulation program. The two primary reasons for adopting this approach is that it allows (1) more reliable identification of energy savings and demand-reduction measures (involving equipment, operation, and/or control changes) in an existing building and (2) increased confidence in the monitoring and verification process once these measures are implemented. Historically, the calibration process has been an art form that inevitably relies on user knowledge, past experience, statistical expertise, engineering judgment, and an abundance of trial and error. Despite widespread interest in the professional community, unfortunately no consensus guidelines have been published on how to perform a simulated calibration using detailed simulation programs. ASHRAE initiated a research project (RP-1051) intended to cull the best tools, techniques, approaches, and procedures from the existing body of research and develop a coherent and systematic calibration methodology that includes both "parameter estimation" and determination of the uncertainty in the calibrated simulation. This paper provides a pertinent and detailed literature review of calibrated simulation techniques, describing their strengths, weaknesses, and applicability, thus serving as a precursor to reporting the results of the research project in subsequent papers.
Natural ventilation is widely applied in sustainable building design because of its energy saving, indoor air qualify and indoor thermal environment improvement. It is important for architects and engineers to accurately predict the performance of natural ventilation, especially in the building design stage. Unfortunately, there is not any good public tool available to predict the natural ventilation design. The integration of the multi-zone model and the computational fluid dynamics (CFD) simulation provides a way to assess the performance of natural ventilation in whole buildings, as well as the detailed thermal environmental information in some particular space. This work has coupled the multi-zone airflow model with the thermal model. A new program, called MultiVent, has been developed with a web-server that can provide online calculation for the public. The MultiVent program can simultaneously simulate the indoor air temperature and airflow rate with known indoor heat sources for buoyancy dominated, buoyancy-wind combined and wind dominated cases. To properly apply the MultiVent program to the natural ventilation design, two configurations in naturally ventilated buildings should be carefully studied: the atrium and large openings between the zones. A criterion has been set up for dividing the large opening and the connected atrium space into at least two sub-openings and sub-zones. The results of the MultiVent calculation can provide boundary conditions to the CFD simulation for some particular zone. In order to correctly simulate the particular space with CFD, the location and conditions at the integrating surface (boundary surface) have been studied. This work suggested that the simulation zone should include part of the connected atrium space when