Residential buildings in the United States are responsible for the consumption of 38% of electricity, and for much of the fluctuations in the power demands on the electric grid, particularly in hot climates. Residential buildings are also where occupants spend nearly 69% of their time. As “smart” technologies, including electric grid-connected devices and home energy management systems are increasingly available and installed in buildings, this research focuses on the use of these technologies combined with available energy use data in accomplishing three main objectives. The research aims to: (a) better understand how residential buildings currently use electricity, (b) evaluate the use of these smart technologies and data to reduce buildings’ electricity use and their contribution to peak loads, and (c) develop a methodology to assess the impacts of these operational changes on occupant thermal comfort. Specifically this study focuses on two of the most significant electricity consumers in residential buildings: large appliances, including refrigerators, clothes washers, clothes dryers and dishwashers, and heating, ventilation and air conditioning (HVAC) systems. First, to develop an improved understanding of current electricity use patterns of large appliances and residential HVAC systems, this research analyzes a large set of field-collected data. This dataset includes highly granular electricity consumption information for residential buildings located in a hot and humid climate. The results show that refrigerators have the most reliable and consistent use, while the three user-dependent appliances varied more greatly among houses and by time-of-day. In addition, the daily use patterns of appliances vary in shape depending on a number of factors, particularly whether or not the occupants work from home, which contrasts with common residential building energy modeling assumptions. For the all-air central HVAC systems studied, the average annual HVAC duty cycle was found to be approximately 20%, and varied significantly depending on the season, time of day, and type of residential building. Duty cycle was also correlated to monthly energy use. This information provides an improvement to previously assumed values in indoor air modeling studies. Overall, the work presented here enhances the knowledge of how the largest consumers of residential buildings, large appliances and HVAC, operate and use energy, and identifies influential factors that affect these use patterns. The methodologies developed can be applied to determine use patterns for other energy consuming devices and types of buildings, to further expand the body of knowledge in this area. Expanding on this knowledge of current energy use, smart large appliances and residential HVAC systems are investigated for use in reducing peak electric grid loads, and building energy use, respectively. This includes a combination of laboratory testing, field-collected data, and modeling. For appliance peak load reduction, refrigerators are found to have a good demand response potential, in part due to the nearly 100% of residential buildings that have one or more of these appliances, and the predictability of their energy consumption behavior. Dryers provide less consistent energy use across all homes, but have a higher individual peak power demand during afternoon and evening peak use times. These characteristics also make dryers also a good candidate for demand response. The study of continuous commissioning of HVAC systems using energy data found that both runtime and energy use are increased, and cooling capacity and efficiency are reduced due to the presence of faults or inefficiencies. The correction of these faults have an estimated 1.4% to 5.7% annual impact on a residential building’s electricity use in a cooling-dominated climate such as the one studied. Overall, appliance peak load reduction results are useful for utility companies and policy makers in identifying what smart appliance may provide the most peak energy reduction potential through demand response programs. The results of the HVAC study provides a methodology that can be used with energy use data, to determine if an HVAC system has the characteristics implying an inefficiency may be present, and to quantify the annual savings resulting from its correction. The final aspect of this research focuses on the development of a tool to enable an assessment the effect of operational changes of a building associated with energy and peak load reduction on occupant comfort. This is accomplished by developing a methodology that uses the response surface methodology (RSM), combined with building performance data as input, and uncertainly analysis. A second-order RSM model constructed using a full-factorial design was generally found to provide strong agreement to in and out-of-sample building simulation data when evaluating the Average Percent of People Dissatisfied (PPD[subscript avg]). This 5-step methodology was applied to assess occupant thermal comfort in a residential building due to a 1-hour demand response event and a time-of-use pricing rate schedule for a variety of residential building characteristics. This methodology provides a model that can quickly assess, over a continuous range of values for each of the studied design variables, the effect on occupant comfort. This may be useful for building designers and operators who wish to quickly assess the effect of a change in building operations on occupants. / text

Accurate modeling of energy flows in buildings is necessary for optimization of mechanical systems, and architectural designs and components. One specific process which has been studied little is that of forced convection on the interior surfaces of window assemblies, which is present in the majority of newly constructed commercial buildings. To this end, energy flows associated with a specific Heating Ventilation and Air-Conditioning (HVAC) configuration- a floor register near a glass curtain wall with or without Venetian blinds- are analyzed experimentally and partially described with accepted theory. Natural convection at the same surface is analyzed as well, both to establish a baseline and to experimentally validate the experimental setup. A 60 cubic meter environmental chamber with precisely controlled interior conditions and electrical resistance heating panels is employed to study heat transfer at the interior surfaces of a building’s envelope. Convection heat transfer processes for various blind angles, HVAC regimes, surface temperatures, and window sizes are examined. Results show that convection at window and blind surfaces is highly dependent on blind angle, supply temperature and flow rate, moderately dependent on room-supply air temperature difference and HVAC regime, and weakly dependent on surface-supply air temperature difference. A simplified model of convection heat transfer in this particular situation is proposed for easy implementation in energy modeling software. / text

Sustainable Built Environments Senior Capstone / Climate change is gaining speed and affecting the life on earth in increasingly drastic ways. Humans are the main cause for climate change with the primary driver being amplified greenhouse gases in the atmosphere. Burning of fossil fuels and deforestation are the largest contributors of greenhouse gases, and both are done for human needs and comfort. A major source of greenhouse gases is the energy used to run buildings. Specifically, heating, cooling, and lighting are the largest users of electric; therefore, the largest contributors to climate change. This report takes an in depth look at building energy uses, how the energy used for these systems can be reduced, and how much carbon emissions can be cut by implementing appropriate design strategies and using proper materials for the climate. Computer programs COMcheck and eQUEST were used to analyze building energy performance and analyze the effect of alternate energy strategies. The results show that minimal modifications at the design stage of planning a building can decrease energy needs by up to 45% by passively using the environment as a power source. The results also display that using sensible materials can have a big impact on the long-term carbon emissions of a building. The analysis for this report was designed specifically for commercial buildings; therefore, future research would include the carbon emission analysis for residential buildings.

Currently, four areas of Texas have been designated by the United States Environmental Protection Agency (EPA) as non-attainment areas because they exceeded the national one-hour ground-level ozone standard of 0.12 parts-per-million (ppm). Ozone is formed in the atmosphere by the reaction of Volatile Organic Compounds (VOCs) and Nitrogen Oxides (NOx) in the presence of heat and sunlight. In May 2002, The Texas State Legislature passed Senate Bill 5, the Texas Emissions Reduction Plan (TERP), to reduce the emissions of NOx by several sources. As part of the 2001 building energy performance standards program which is one of the programs in the TERP, the Texas Legislature established the 2000 International Energy Conservation Code (IECC) as the state energy code. Since September 1, 2001, the 2000 IECC has been required for newly constructed single and multifamily houses in Texas. Therefore, this study develops and applies portions of a methodology to calculate the energy savings and NOx emissions reductions from the adoption of the 2000 IECC to new single family houses in non-attainment and affected counties in Texas. To accomplish the objectives of the research, six major tasks were developed: 1) baseline data collection, 2) development of the 2000 IECC standard building simulation, 3) projection of the number of building permits in 2002, 4) comparison of energy simulations, 5) validation and, 6) NOx emissions reduction calculations. To begin, the 1999 standard residential building characteristics which are the baseline construction data were collected, and the 2000 IECC standard building characteristics were reviewed. Next, the annual and peak-day energy savings were calculated using the DOE-2 building energy simulation program. The building characteristics and the energy savings were then crosschecked using the data from previous studies, a site visit survey, and utility billing analysis. In this thesis, several case study houses are used to demonstrate the validation procedure. Finally, the calculated electricity savings (MWh/yr) were then converted into the NOx emissions reductions (tons/yr) using the EPA's eGRID database. The results of the peak-day electricity savings and NOx emissions reductions using this procedure are approximately twice the average day electricity savings and NOx emissions reductions.

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Buildings energy consumption is rising continuously with massive urbanization progress, which then results in high greenhouse gas emission. A standing example is the urbanization process going on in the south-west part of China. Much has been discussed for improving building energy performance. However, to take another point of view, renewable energy source for buildings is a solution worth considering, for instance STES, which gains thermal energy from the sun, delivers it to buildings for space heating and hot tap water, also restores the solar energy in hot seasons in the storage system for the need of cold season.The aim of this paper is to couple the technology of STES with practical situation, explore the possibility of applying STES in south-west of China. This thesis work takes an estimation approach to weigh the possibility. The building project studied in this thesis is a campus project in the city of Guiyang, one of four major cities in the region of south-west China.Case study involves existing STES projects in Munich Germany and Anneberg Sweden, the performance evaluation of the Anneberg project is later to serve as an example in system gain & losses proportion, to guide the estimation work of the campus project.The estimation conclusion is drawn based on a cross-sectional analysis method, take the technology of STES, the practiced STES project and building projects in China as three loops visually, and observe how much they overlap each other. Behind the visual illustration, the overlapping is assessed with several factors, for instance possibility of storage system at location, possible STES performance and solar irradiation condition at site location etc. If most of these factors are checked to be “Ok” or “Good”, then the overlapping area is considered “large” enough, and therefore suggests a decent chance to implement STES system in the south-west China.A solar gain and sunlight simulation from a new police station energy consumption report assists in calculating the possible solar gain for the campus project, as the very close distance between these two sites (30 km) promises them the very similar solar irradiation condition. While the energy consumption of the studied campus project offers the energy demand for space heating and hot tap water in the need of 19,000 students, which is to be evaluated as the task of the STES system in the estimation work. Both building project reports are filed by GARDI (Architecture design research institution of Guizhou).Some key factors have been calculated and estimated, the heat demand of the studied campus project in Guiyang is 5,558 MWh/year, and the possible solar gain of this campus complexity is 4,900 MWh/year based on the gain & losses proportion of the Anneberg project evaluation. Due to the very different climate condition of Guiyang and Anneberg, as well as other uncertain factors such as effective roof area, solar collector efficiency, a sensitivity analysis evaluated the result with different parameters in changes of percentage. Final results in the changes of effective roof area at 80% and 85 %, borehole losses at 50% and 45%, available solar gain at 38%, STES system is shown to be capable of providing sufficient heat to buildings. If the heating demand and hot tap water, in the case of the campus project alone are all covered by STES system, there will be a reduction in CO2 emission of 5,368 tons/year.Cross-sectional analysis concludes four out of eight factors checked as “Good” and two as “Ok”, other two as “Unsure”. Other three cities (Chengdu, Kunming, and Chongqing) are brought to comparison later regarding climate condition. Besides Guiyang, two out of three are evaluated to have potential of STES implementation according to their sun hours, annual average temperature etc. STES system is estimated to be possible for implementation in south-west of China as the conclusion.

The British National Health Service (NHS) is one of the largest public services in the world and consequentially in 2004 it produced 25% of the total public sector carbon emissions for England. To meet national carbon targets the NHS must reduce its emissions; 26% by 2020, 64% by 2030, 80% by 2050 and is therefore interested in the development of strategies for reducing carbon dioxide emissions from buildings. The NHS building stock consists of a range of building archetypes constructed over the past 100 years. The energy used for heating and cooling hospital premises is the source of 22% of all NHS carbon emissions. The individual buildings are distributed across hospital sites that often have centralised energy plants, which make it difficult to monitor energy consumption on an individual building level. This thesis develops a method for monitoring the energy consumption of individual hospital buildings. The method was implemented on three case study buildings at Bradford Royal infirmary (BRI); a 1920s Nightingale, a nucleus and a modern modular building. Lessons were gathered from these studies to advance the knowledge on monitoring in UK hospitals. One of the key findings was that empirical models based on measured data are useful for estimating individual buildings annual heating energy consumption. The results show that the mechanically ventilated nucleus building had the highest energy consumption (808.7kWh/m2), followed by the naturally ventilated Nightingale building (420.7kWh/m2) and then the mixed-mode modular building (289.0kWh/m2). The internal environment was optimal in the nucleus building, but the Nightingale and modular buildings underperformed, with the modular overheating in summer and both buildings failing to meet air quality recommendations. Taking energy consumption and summer thermal resilience into consideration the Nightingale building had the best performance, demonstrating the longevity of the traditional design. The work identified a number of useful hospital design features; well-insulated heavyweight building fabric, well-controlled space heating, use of heat recovery ventilation and installation of localised monitoring equipment. Further useful research into this area could involve: using dynamic thermal simulation to test recommended building design features, investigating the monitoring method on a wider sample of sites and investigating air quality monitoring in hospitals.

AN ABSTRACT OF THE THESIS OF Rohit Kadam, for the Master of Science degree in MECHANICAL ENGINEERING, presented on DECEMBER 2, 2011, at Southern Illinois University Carbondale. (Do not use abbreviations.) TITLE: NET ZERO BUILIND ENERGY CONSERVATION MAJOR PROFESSOR: Dr. Emmanuel Nsofor This research deals with energy studies performed as part of a net-zero energy study for buildings. Measured data of actual energy utilization by a building for a continuous period of 33 months was collected and studied. The peak design day on which the building consumes maximum energy was found. The averages of the energy consumption for the peak month were determined. The DOE EnergyPlus software was used to simulate the energy requirements for the building and also obtain peak energy requirements for the peak month. Alternative energy sources such as ground source heat pump, solar photovoltaic (PV) panels and day-lighting modifications were applied to redesign the energy consumption for the building towards meeting net-zero energy requirements. The present energy use by the building, DOE Energy software simulations for the building as well as the net-zero model for the building were studied. The extents of the contributions of the individual energy harvesting measures were studied. For meeting Net Zero Energy requirement, it was found that the total energy load for the building can be distributed between alternative energy methods as 5.4% to daylighting modifications, 58% to geothermal and 36.6% to solar photovoltaic panels for electricity supply and thermal energy. Thus the directions to proceed towards achieving complete net-zero energy status were identified.

Many scientists have accepted that human activities are the major cause of climate change and global warming. Knowledge on the effect this will have on office buildings and energy consumption in the future is essential. Thus the assessment of future building energy consumption is becoming more important especially in countries such as Malaysia where the majority of the office buildings depend on air-conditioning to maintain the occupants level of comfort. This research explores the effect of future climate change weather on the energy consumption of office buildings in Malaysia, by using simulation software. Simulated weather data sets HadCM3 were supplied by the Hadley Centre in the United Kingdom for the recent past and for the future up to 2099. Test Reference Years (TRYs) were selected from this data using the Finkelstein-Schafer Statistic (FS) method for four time slices, namely TRYs 1990-2007, 2010-2039, 2040-2069 and 2070-2099. The HadCM3 data was validated by comparing the 1990-2007 TRY with a TRY selected by the same method and period from the measured weather. The Hadley data was supplied as daily values, but the building simulation software required hourly values. Algorithms were therefore used to generate hourly values from the daily data for the relevant variables (dry bulb temperature, relative humidity, wind speed and global solar radiation) and to decompose global solar radiation into direct and diffuse radiation. Two different office building were modelled in the simulation software, one imaginary simplified typical building and one real building. The sensible and latent annual cooling loads were found for each building for each different TRY. A sensitivity analysis was also performed to investigate the effect on cooling load of changes in building design as possible ways of mitigating the effects of climate change. It was found that climate change will increases the building energy consumption by 13.6 percent in future and better understanding on building design will reduce this effect.

The world’s energy use in buildings (residential and commercial) accounts for around 40% of the worldwide energy consumption, and space heating is the responsible for half of the energy need in the building sector. In Europe, only a small share (less than 10%) of existing buildings was built after 1990. Most of the building stock does not satisfy the recent energy technical standards; in addition there is a very low trend to construct new buildings in the last years. Renovation of the existing buildings is a feasible option to reduce the energy need in Europe, but finding the optimum solutions for a renovation is not a simple task. Each design parameter differently influences the final energy need of buildings and, furthermore, the different variables are differently correlated each other. Building refurbishment will benefit from a tool for the selection of the best measures in term of energy need. This work, through a global sensitivity analysis, aims at determining the contribution of the design parameters to the building energy demand and the correlation between the different variables. The considered parameters are related to the improvement of the thermal transmittance of both the opaque envelope and the windows, the solar transmittance of the glazing surfaces, the window size, the thermal inertia of the internal walls and the external sunshades for windows. Several dynamic simulations have been performed varying the design parameters from different starting conditions. Finally, due to the large number of cases elaborated, an inferential statistical analysis has been performed in order to identify the predominant factors and the correlation between the design parameters in a global context.