Browsing by Author "Claridge, David"
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Item 2018 Statewide Air Emission Calculations from Wind and Other Renewables VOL I(Energy Systems Laboratory, 2019-07) Baltazar, Juan-Carlos; Haberl, Jeff; Yazdani, Bahman; Claridge, David; Jung, Sungkyun; Kheiri, Farshad; Kim, ChulItem An Investigation of the Energy, Cost, and Comfort of Adaptive Model-Predictive Controls for Residential HVAC Systems(2023-08-03) Yang, Tao; O'Neill, Zheng; Claridge, David; Pate, Michael; Xie, LeThe building sector constitutes the largest portion of energy consumption worldwide, surpassing the industrial and transportation sectors. In the United States, buildings alone account for approximately 40% of total energy (with residences contributing 22% and commercial buildings consuming 18%) and are responsible for 40% of carbon emissions. As part of the 2030 U.S. action plan to combat climate change, a target of 50-52% reduction in greenhouse gas (GHG) emissions has been set, compared to the 2005 level. Therefore, quite clearly, reducing energy consumption in buildings, especially in the residential sector, holds significant potential to contribute towards achieving these ambitious energy and emission mitigation goals. Among the energy consumption in U.S. buildings, the Heating, Ventilation, and Air-Conditioning (HVAC) system, which provides a desirable environment for occupants living inside, is responsible for the majority of the total energy used. Compared to building automation systems that are extensively utilized in commercial buildings, HVAC control systems integrated for current residential buildings are limited. The central forced-air system is widely used in regular homes throughout North America, where manual, programmable, and connected ones (commonly known as smart thermostats) are the three main categories of thermostats. The first two categories are found in traditional thermostats, whereas connected thermostats offer additional capabilities such as remote setpoint operation via smartphones. However, occupants often struggle to determine the appropriate setpoint that will ensure their comfort while achieving energy savings, primarily because they are unable to consider the adaptation to several uncertain scenarios. One such scenario is the degradation of cooling/heating capacity caused by air conditioner (AC) unit faults. This degradation can hinder the HVAC system’s ability to maintain desired thermal requirement, especially when the cooling/heating load is high. Additionally, the emergence of the smart grid, coupled with increased on-site renewable generation, offers the opportunity to leverage new grid features, such as electricity price variations, to optimize energy consumption and reduce residents' energy bills. This ability to respond is highly appealing. Therefore, this research develops a cost-effective HVAC control framework for smart homes that has the capability of connecting fault detection and diagnosis and corresponding fault-adaptive control to provide an acceptable indoor thermal environment with lower energy consumption. Additionally, the framework is designed to be responsive to grid signals, aligning with grid requirements. To ensure its applicability in regular homes, a practical and user-friendly approach is generated, making it easy to implement and utilize. Fault modeling of residential HVAC systems has been established, which encompasses the creation of a fault library and the construction of modeling methods. This fault library comprises 24 common faults categorized into five types, commonly found in residential buildings. This workflow is demonstrated by injecting multiple faults into EnergyPlus models of prototype buildings. Fault modeling results are beneficial to understand the impact of faults in residential HVAC systems, serving as a foundation for generating fault detection and fault-adaptive control algorithms. Fault Detection and Diagnosis (FDD) algorithms are then generated for residential air-source Vapor Compression Cycle (VCC) systems, identified as the most impactful fault based on previous fault modeling investigations. Seven potential faults along the refrigerant line are considered. A quantitative comparison analysis is conducted for three rule-based FDD algorithms, utilizing open-source laboratory data and exclusive field data. Based on the accuracy rates observed for various faults, a hybrid FDD approach is recommended, with temperature measurements being the key determinant. When faults are detected that affect the HVAC capacity, strategies for pre-cooling or preheating homes are introduced. Model Predictive Control (MPC), recognized for its efficacy in slow and non-linear dynamic systems such as HVAC systems, stands out as a control methodology. This method capitalizes on the thermal mass of buildings, enabling precooling to offset the consequences of capacity degradation or to shift the building load. Simplified operational rules are then extracted from the offline implementation of a large-scale MPC system using a rule extraction method. Artificial Neural Network (ANN) is used to develop models for MPC, while optimization is achieved using Differential Evolution (DE). Rule extraction, facilitated by a Decision Tree (DT), emulates the MPC results, enabling the optimized control trajectory to be implemented to a certain extent in regular homes. These MPC-informed rules are computationally efficient and can be executed online in residential HVAC controllers. Using the same computer setup, the average runtime for MPC is 870 minutes over a ten-day period, while the MPC-informed Rule-Based Control (RBC) finishes in an average of 0.2 minute. This makes the MPC-informed RBC significantly faster than the original MPC. Finally, field tests are conducted to verify the effectiveness and efficiency of the developed FDD and adaptive control strategies. Two identical lab homes are utilized for this purpose. Lab Home A functions as the control home, while Lab Home B is the baseline home. For the FDD strategy demonstration, the heat pump system's FDD accuracy achieves 90.18%, counting all cases (including fault-free ones), with no false alarms. The detection accuracy stands at 96.4%. In terms of improving thermal comfort, unmet hours could be reduced from 2.05 ℉-hour (Lab Home A) to 0.22 ℉-hour (Lab Home B), thereby enhancing residents' thermal comfort under HVAC system malfunction or during heatwave conditions.Item An Analysis of A Low-Energy, Low-Water Use Community in Mexico City(2014-06-02) Bermudez Alcocer, Jose Luis; Haberl, Jeff; Baltazar-Cervantes, Juan-Carlos; Culp, Charles; Clayton, Mark; Claridge, DavidThis study investigated how to determine a potential scenario to reduce energy, water and transportation use in Mexico City by implementing low-energy, low-water use communities. The proposed mixed-use community has multi-family apartments and a small grocery store. The research included the analysis of: case studies, energy simulation, and hand calculations for water, transportation and cost analysis. The previous case studies reviewed include: communities in Mexico City, Mexico, Austin, Texas, Phoenix, Arizona, New York City, New York and San Diego, California in terms of successful low-energy, low-water use projects. The analysis and comparison of these centers showed that the Multifamiliar Miguel Aleman is an excellent candidate to be examined for Mexico City. This technical potential study evaluated energy conserving measures such as low-energy appliances and efficient lighting that could be applied to the apartments in Mexico City to reduce energy-use. The use of the simulations and manual calculations showed that the application of the mixed-use concept was successful in reducing the energy and water use and the corresponding carbon footprint. Finally, this technical potential study showed taking people out of their cars as a result of the presence of the on-site grocery store, small recreation center and park on the ground floor also reduced their overall transportation energy-use. The improvement of the whole community (i.e., apartments plus grocery store) using energy-efficient measures provided a reduction of 70 percent of energy from the base-case. In addition a 69 percent reduction in water-use was achieved by using water-saving fixtures and greywater reuse technologies for the complex. The combination of high-efficiency automobiles and the presence of the on-site grocery store, small recreation center and park potentially reduced the transportation energy-use by 65 percent. The analysis showed an energy cost reduction of 82 percent reduction for apartments and a 22 percent reduction for the store. In addition, for water cost there was a 70 percent reduction for apartments and a 16 percent reduction for the store. Overall, a 64 total percent reduction in carbon dioxide (CO_(2)) was accomplished by saving energy-use in the apartments, the grocery store and transportation. Finally, a guide has been created for Mexico City to establish strategies and actions based on the results of this work in order to reduce overall energy and water-use in Mexico City. The guide is expected to be useful in the short term in Mexico City, and could be potentially adopted in the long term in other countries in the same manner as which Brazil and Colombia adopted the Mexican CONAVI’s 2010 Housing Building Code.Item Analysis of Building Peak Cooling Load Calculation Methods for Commercial Buildings in the United States(2016-04-28) Mao, Chunliu; Haberl, Jeff S; Baltazar-Cervantes, Juan-Carlos; Beltran, Liliana; Claridge, DavidThis study aims to provide valid comparisons of the peak cooling load methods that were published in the ASHRAE Handbook of Fundamentals, including the Heat Balance Method (HBM), the Radiant Time Series Method (RTSM), the Transfer Function Method (TFM), the Total Equivalent Temperature Difference/ Time Averaging Method (TETD/TA), and the Cooling Load Temperature Difference/Solar Cooling Load /Cooling Load Factor Method (CLTD/SCL/CLF), and propose a new procedure that could be adopted to update the SCL tables in the CLTD/SCL/CLF Method to make the results more accurate. To accomplish the peak cooling load method comparisons, three steps were taken. First, survey and phone interviews were performed on selected field professionals after an IRB approval was obtained. The results showed that the CLTD/SCL/CLF Method was the most popular method used by the HVAC design engineers in the field due to the reduced complexity of applying the method while still providing an acceptable cooling load prediction accuracy, compared to the other methods. Next, a base-case comparison analysis was performed using the published data provided with the ASHRAE RP-1117 report. The current study successfully reproduced the HBM results in the RP-1117 report. However, the RTSM cooling load calculation showed an over-prediction compared to the RTSM results in the report. In addition, analyses of the TFM, the TETD/TA Method and the CLTD/SCL/CLF Method were compared to the base-case cooling load. The comparisons showed the HBM provided the most accurate analysis compared to the measured data from the RP-1117 research project, and the RTSM performed the best among the simplified methods. The TFM estimated a value very close to the peak cooling load value compared to the RTSM. The CLTD/SCL/CLF Method behaved the worst among all methods. Finally, additional case studies were analyzed to further study the impact of fenestration area and glazing type on the peak cooling load. In these additional comparisons, the HBM was regarded as the baseline for comparison task. Beside the base case, fifteen additional cases were analyzed by assigning different window areas and glazing types. The results of the additional tests showed the RTSM performed well followed by the TFM. The TETD/TA Method behaved somewhere in between the TFM and CLTD/SCL/CLF Method. In a similar fashion as the base-case comparisons, the CLTD/SCL/CLF Method performed the worst among all methods. Based in part on the results of the survey and interview as well as the comparisons, updates to the SCL tables in the CLTD/SCL/CLF Method were developed that allowed the CLTD/SCL/CLF Method to be more accurate when compared to the HBM. The new updated SCL tables were calculated based on the SHGC fenestration heat gain model instead of the SC and DSA glass coefficients. Three examples were provided that showed the improved analysis with the updated SCL tables. All of the results showed an improved peak cooling load estimation.Item An Analysis of Energy Consumption in Grocery Stores in a Hot and Humid Climate(2013-04-09) Mukhopadhyay, Jaya; Haberl, Jeff; Claridge, David; Culp, Charles; Pate, MichaelThe intent of this study was to investigate the efficient use of energy by developing an energy efficient grocery store combined with cogeneration. This study demonstrated the potential to reduce the energy use in buildings, by implementing a decentralized source of energy generation that allowed for the use of a portion of the energy generated to be shared across building boundaries. This study considered a high energy use building such as a grocery store to be a part of a residential community, which could potentially participate in the sharing of energy across building boundaries. To better utilize energy resources the study proposed the implementation of a cogeneration facility to supply energy primarily to the store. Surplus energy generated by this cogeneration system was then shared with the requirements of the surrounding residential community. Finally, in order to better account for energy consumption of these buildings both site and source energy was considered. The study focused on hot and humid climates. This study was presented in two parts: Analyzing conventional grocery store systems to determine the maximum savings possible; and examining the option of co-generation systems to provide power to grocery stores and a portion of the community in order to reduce source energy use for the grocery store and a portion of the surrounding community. Source energy savings were in the range of 47% to 54% depending on the energy efficiency measures selected and the cogeneration configuration determined in the grocery store. Economic payback periods in the range of 4 to 7 years (time until zero net present value) were observed. The selection of appropriate options was narrowed down to two options that utilized more thermal energy within the boundaries of the store and generated more amount of surplus energy to be absorbed by the neighboring residential buildings.Item Analysis of Regenerative, High-Performance and Cultural-Based Single-Family Homes: Impacts of a New Generation of Affordable Housing in Saudi Arabia(2022-07-22) Mezaien, Ahmed Abdullah H; Baltazar, Juan Carlos; Yan, Wei; Caffey, Stephen; Claridge, DavidHousing represents a substantial financial challenge for many home-seekers in Saudi Arabia (KSA), especially among young adults. Most private, single-family homes available in the real estate market have significant square footage and also come with large land areas, and often they are completely devoid of the architectural identity of the region. Furthermore, such homes require large amounts of energy due to their large size, do not integrate passive thermal elements, and rarely integrate efficient active control systems. Several attempts have been made to explore the benefits of vernacular or local architectural elements from heritage architecture, some others have been concentrated on accessing affordable housing through leveraging cost-cutting construction techniques, building envelopes, and employing lower-cost building materials. Unfortunately, appropriate numerical experiment and comprehensive simulations are lacking in these investigations surrounding the integration of such elements into modern house designs. Additionally, it has been recognized by the American Council for an Energy-Efficient Economy ACEEE) that the residential sector can play a significant role in decarbonization, i.e., the minimization of carbon emissions through energy efficiency, electrification, distributed electricity generation, and the use/generation of electricity from carbon-free fuels. The principal objective of this research is to investigate a new generation of affordable housing that can support clean energy transformation by establishing new regenerative design that promote sustainability and cultural identity while offering a healthy living standard. This study is based on the City of Jeddah, KSA climate conditions, includes the integration of vernacular architectural elements; such as rowshans and windcatchers, renewable technologies, emergent efficient active control systems and life cycle analysis. The analysis of weather conditions revealed that Jeddah has the potential for natural ventilation 34% of the time annually, from November to March. Additionally, the findings surrounding the integration of local architectural elements into modern design through detailed CFD analysis showed that appropriate design configurations for rowshan and windcatcher provide ventilation to create an effective range of thermal comfort reducing the use of air conditioning in hot-dry climates. This study also included emergent cooling and renewable systems, such as variable refrigerant flow (VRF) systems and solar photovoltaics (PV) systems as technologies that could be integrated for regenerative design approaches. The VRF system can reduce up to 28% of the annual house electricity consumption than mini-split system, which reduced the EUI from 123 kWh/m2/yr (39 kBtu/ft2/yr) to 88 kWh/m2/yr (28 kBtu/ft2/yr) . Use of solar PV systems can reduce the EUI for households to zero or moving beyond the sustainable design concept and shifting to regenerative design, which produce positive results in healing the surrounding environment. The contribution of this research support the determination of create a new baseline for a regenerative single-family home design in Jeddah, KSA. Additionally, this research provides a step forward to developing passive and active hybrid design alternatives to realize a new generation of affordable housing necessary to deal with environmental problems in the coming decades under Saudi Vision 2030 requirements.Item Analysis of Residential Building Energy Code Compliance for New and Existing Buildings based on Building Energy Simulation(2020-11-11) Jung, Sungkyun; Haberl, Jeff; Baltazar, Juan-Carlos; Yan, Wei; Claridge, DavidCurrently, the International Energy Conservation Code (IECC) is the most widely-used residential building energy code in the United States. Either the IECC or IECC with amendments has been adopted by 33 states. The latest version of the IECC contains three compliance requirements, including: mandatory, prescriptive, and performance paths for compliance. The performance path includes specifications for the standard house design and the proposed design to be analyzed using whole-building energy simulations. In the performance path, the annual simulated energy cost of the proposed house must be less than the annual energy cost (or source energy usage) of the standard reference house. Unfortunately, most of the whole-building energy simulation programs are too complicated to be used by building energy code officials or homeowners without special training. To resolve this problem, simplified simulation tools have been developed that require fewer user input parameters. Such simplified software tools have had a significant impact on the increased use of the performance-based code compliance path for residential analysis. However, many of the simplified features may not represent the energy efficient features found in an existing residence. This may mis-represent the potential energy saving when/if a house owner decides to invest in a retrofit to reduce their annual energy costs. Currently, there are building energy simulation validation methods developed by ASHRAE, and RESNET including: ASHRAE Standard-140, IEA BESTEST, HVAC BESTEST, and BESTEST-EX. These tests have been developed to test the algorithms of building energy performance simulation, which require complex inputs and outputs to view the test results. Unfortunately, even though two different building simulation validation programs may produce the necessary inputs/outputs for certification, they are rarely tested side-by-side or on actual residences. Furthermore, results from a simplified analysis of a building is rarely compared against a detailed simulation of an existing building. Therefore, there is a need to compare the results of a simplified simulation versus a detailed simulation of an existing residence to better determine which parameters best represent the existing house so more accurate code-compliant simulations can be performed on existing structures. The purpose of this study is to develop an accurate, detailed simulation model of an existing single-family residence that is compared with a simplified building energy simulation of the same residence to help determine which on-site measurements can be made to help tune the simplified model so it better represents the existing residence. Such an improved building energy simulation can be used to better represent annual energy cost savings from retrofits to an existing building.Item Analysis of Support Vector Machine Regression for Building Energy Use Prediction(2020-07-15) Lee, Shinwoo; Baltazar, Juan Carlos; Haberl, Jeff; Claridge, DavidThere are many inverse modeling methods to model the whole building energy use. Multiple linear regression (MLR) and change-point liner regression (CPLR) have been some of the most common methods due to their intelligibility concerning building energy modeling and accuracy. Recently, as machine-learning techniques have become user-friendly, there have been an incremental number of attempts to apply these techniques to building energy modeling. However, few studies conducted an in-depth comparison with the conventional inverse model methods using large sample size. This study conducted an exhaustive comparative study based on Support Vector Machine (SVM), one of the most widely used machine-learning methods for flexibility and accuracy, with enough samples to draw a reasonable conclusion between models generated from conventional methods such as MLR and CPLR, and those from SVM. This work, besides the comparative analysis, included a thorough SVM performance analysis for building energy modeling. It described in detail its implementation, and showed its performance as a regression technique for building energy modeling under the influence of different variables. The comparative study focused on modeling whole building chilled water use (CHW) and heating hot water use (HHW), and analyzed the influence of such variables as the outdoor dry-bulb temperature (OAT), the outdoor dew-point temperature (DPT), the outdoor air enthalpy (OAE), and operational effective enthalpy (OEE). The numerical experiments were based on 41 whole year hourly building energy use dataset samples. These datasets were transformed into daily and monthly datasets. According to the comparative analysis between SVM and MLR, based on CHW datasets, SVM consistently showed higher performances by an average of 6.8% on daily and 2.0% on monthly models, respectively. For the SVM and CPLR performance analysis, four pairs of dependent and independent variables were considered: CHW-OAT, CHW-OAE, CHW-OEE, and HHW-OAT. On the daily model, SVM demonstrated consistently higher performances although most of the cases resulted in a marginal advantage by less than 1% for all variables utilized. Despite such marginal gains in mean performance, SVM showed advantages by up to 3% for some datasets. On the monthly model, however, SVM did not exhibit better results for any dependent-independent variable pair.Item Annual Report to the Texas Commission on Environmental Quality January 2015-December 2015(2017-05-04) Haberl, Jeff; Yazdani, Bahman; Baltazar, Juan-Carlos; Do, Sung Lok; Ellis, Shirley; Mukhopadhyay, Jaya; Parker, Patrick; Degelman, Larry; Zilbershtein, Gali; Claridge, DavidItem A Comparison of WinAM and EnergyPlus Predicted Consumption Due to the Effects of Thermal Mass and Temperature Setback(2018-08-17) Likins, Madison Marie; Claridge, David; Culp, Charles; Pate, MichaelThe purpose of this research was to compare the energy consumption of WinAM and EnergyPlus when thermal mass and a temperature setback are applied. Since WinAM does not account for thermal mass, a correction method was developed to correct the predicted savings produced by a temperature setback. This correction method accounts for thermal mass, wall resistance, building size, and wall area, and works best for climates with a wide range of temperatures. Hourly cooling coil and heating coil energy were plotted versus outside temperature for WinAM and EnergyPlus with varying wall constructions, climates, and temperature schedules, totaling 18 EnergyPlus simulations and 6 WinAM simulations. Consumption from these results were summed to calculate the monthly cooling and coil energy. For each simulation, the difference between energy consumption for a temperature setback and no setback were calculated for each month; this value is the predicted savings produced each monthly by implementing a temperature setback. The difference in predicted savings between WinAM and EnergyPlus was then plotted versus outdoor air temperature. This was used to create the correction method that adjusts WinAM predicted savings to better match EnergyPlus predicted savings. Results indicate WinAM under predicting hourly cooling and heating coil energy. Results also show WinAM over-estimating the predicted savings due to temperature setback by 200 1000 Btu/ft² depending on the temperature. By implementing the WinAM correction method, the WinAM over-estimation is reduced to 30-150 Btu/ft². The calculated percent reduction in the difference between EnergyPlus and WinAM predicted savings is up to 99%. The large reduction in the difference between WinAM and EnergyPlus predicted savings indicates the correction method works well for the simulations produced. Implementing the correction method leads to a WinAM model that more accurately predicts temperatures setback savings when thermal mass is applied.Item A Comprehensive Evaluation of the Impact of Continuous Commissioning®(2019-04-04) Ruffin, Alaina Jones; Claridge, David; Baltazar, Juan-Carlos; Culp, Charles; Pate, MichaelThe primary goal of this study was to quantify the impact of Continuous Commissioning®^1 (CC®) since the inception of the process in the early 1990s using a comprehensive evaluation of the impact of CC® projects implemented primarily by the Texas A&M Engineering Experiment Station’s Energy Systems Laboratory. Several quantitative analysis and comparison tasks were completed to accomplish the research objectives. The overall impact of Continuous Commissioning was analyzed including the energy cost savings as well as identification of non-energy impacts. The evaluation of the impact of CC by building type included education buildings, health care facilities, laboratory facilities, and office buildings. ASHRAE Standard 169-2006 was employed for the analysis of the impact of CC by climate zone. The project objectives were compared to the project results using the predicted and actual energy cost savings. The CC energy cost savings were compared based on the level of project completeness as determined by the proposed and implemented CC measures. The impact of CC was presented for several case study projects. The 340 CC projects that were compiled and reviewed include 920 buildings (895 buildings with available information represent over 98 million ft^2 of building area). The impact of CC according to four building types considered 159 CC projects: 76 educational, 46 healthcare, 13 laboratory, and 24 offices with average annual savings of $0.48/ft^2 , $0.64/f^t2 , $1.51/ft^2 , and $0.49/ft^2 , respectively. The impact of 196 CC projects grouped by climate zone designations revealed that the majority of the total annual cost savings, about 90%, is from three zones. The average annual energy cost savings was $0.68/ft² for climate zone 2a hot and humid, $0.55/ft² for climate zone 3a warm and humid, and $0.58/ft^2 for climate zone 4a mixed and humid. Comfort issues, including thermal comfort, indoor air quality, and noise, were identified in 59 CC projects with resolutions for at least 34 projects. The annual energy cost savings, as of December 2016, exceeded $29.7 million (2017 $), for 198 CC projects (over 600 buildings with more than 60 million ft^2 of area). The cumulative cost savings up to December 2017 are $390 million (20 17). The terms Continuous Commissioning® and CC® are registered trademarks of the Energy SystemsItem Design and Development of a Vacuum Dehumidification Test Facility(2014-08-13) Schaff, Francesco Nima; Pate, Michael; Claridge, David; Bangerth, WolfgangA test facility was designed and constructed with the capability of isolating critical variables for controlling the novel membrane dehumidification-enabled cooling system’s operation parameters as well as for acquiring preliminary membrane and cooling system performance measurements. The completed test facility consisted of two systems: 1) the feed-air system, which simulated the inlet-air conditions and performed the feed-air dehumidification and sensible cooling and 2) the vacuum system, which enabled the feed-air dehumidification by evacuating the membrane permeate side. The feed-air system as constructed was able to supply membrane-inlet flow rates up to 10 scfm over a range of temperature and relative humidity conditions, including 90°F and 90%RH, which was specified by the project sponsor. In addition, the feed-air system components included a membrane module installation site for dehumidification as well as a sensible cooling system to cool the membrane-outlet air to the 55°F and 50%RH conditions again specified by the sponsor. Measurement stations were placed at the membrane-inlet, membrane-outlet, and the sensible cooler outlet to measure the temperature and relative humidity at these critical locations. The vacuum system as built used a Pfeiffer DUO 10 Vacuum Pump with a 7 cfm pumping capacity, which was preceded by a 60 plate heat exchanger with an effective area of 2.05m^(2) and an Oerlikon-Leybold WA 250 roots blower. The air leakage in the vacuum system was calculated to be less than 1% of the theoretical air permeation through the membrane module. Finally, the apparatus was constructed with the capability of measuring the power consumption of the equipment used for the dehumidification and sensible cooling process. The functionality of the test facility was demonstrated through preliminary testing of the membrane module and the operation of the complete cooling system. The results suggested that the membrane material exhibited an increase in water vapor permeance from temperatures of 70 to 100°F, with calculated permeance values ranging from to 3.93 ∙ 10^(-6) to 5.88 ∙ 10^(-6) kmol/kPa-m^(2)-s. In addition, the results indicated that the novel membrane dehumidification-enabled cooling system was capable of achieving the specified operating conditions at a feed-air flow rate of 0.16 scfm by using a membrane module area of 0.024m^(2).Item Determining Pressure Losses For Airflow In Residential Ductwork(2012-02-14) Weaver, Kevin Douglas; Culp, Charles; Claridge, David; Haberl, JeffAirflow pressure losses through rigid metallic and non-metallic flexible ducts were studied and recommendations to improve the rating of flexible ducts were made as part of this study. The testing was done in compliance with ASHRAE Standard 120-1999, Methods of Testing to Determine Flow Resistance of HVAC Air Ducts and Fittings (ASHRAE 1999). Duct sizes of 6", 8", and 10" were tested in a positive pressure, blow-through configuration. An As-Built Test Protocol expands the test configurations specified by Standard 120-1999. Results of the current tests extend the existing ASHRAE/ACCA data for flexible duct which does not include pressure loss data for flexible ducts that are compressed beyond approximately 4%. The data from this study exhibit higher pressure drops than prior ACCA or ASHRAE data. Some configurations exhibit over ten times the pressure loss found in rigid duct or fully stretched flexible duct of the same diameter.Item Development and Evaluation of High-Performance Rule-Based Sequences of Operation for Variable Air Volume Systems(2022-04-19) Lu, Xing; O'Neill, Zheng; Rasmussen, Bryan; Culp, Charles; Claridge, DavidCommercial buildings account for 35 percent of electricity consumption in the U.S., of which 30 percent is used by the heating, ventilation, and air conditioning (HVAC) system. Despite the significant role of the HVAC control systems in energy efficiency, its design, commissioning, and retrofit have long been an intricate and complicated issue, considering that only diffuse and fragmented information on system operation is available for decision making in most of the scenarios. Due to this limitation, designers and control contractors can only rely on ad-hoc control sequences for system operation in practice, which is one of the major reasons why buildings are operated sub-optimally. To provide standardized and high-performance rule-based HVAC control sequences, the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) has developed the Guideline 36 (GDL36) High Performance Sequences of Operation (SOO) for HVAC Systems to maximize energy efficiency. Although GDL36 was considered the most advanced rule-based HVAC control sequences in this era, most of the proposed controls are still under development and its actual performance remains largely unknown. Up till now, only a few field studies have been conducted to verify the overall effectiveness of GDL36 after its publication, and these studies only focused on the energy saving potential. There is a practical need to benchmark the SOO in GDL36 in different aspects. To address these gaps, this research aims at enhancing the existing standardized high-performance control sequences (GDL36) by conducting a comprehensive evaluation in terms of energy efficiency, fault robustness, ventilation performance, and grid ancillary service compatibility. The target HVAC systems in this research are multi-zone variable air volume (VAV) systems, which are one of the most popular HVAC system configurations in U.S. commercial buildings. First, a Modelica model of a five-zone VAV system that follows both airside and waterside SOO was developed and verified. This building model serves as the virtual testbed for the following intelligent controller evaluation and comprehensive fault impact analysis. Second, the energy saving potential of the high-performance rule-based controls was compared with that of the state-of-the-art intelligent controls (deep reinforcement learning (DRL)-based control (DRLC) and optimization-based control (OBC)) in two typical cooling weeks. Two supervisory control loops in the airside GDL36 SOO (e.g., supply air temperature and duct static pressure) were replaced by DRL and OBC controller. The results show that the GDL36 has a comparable energy performance (within a 3% deviation) with DRLC in scenarios under both high and mild cooling loads. GDL36 also has a comparable energy performance (within a 3% deviation) with OBC in scenarios with high cooling load, but it consumed 7% more energy in the shoulder week. In terms of thermal comfort, the GDL36 was found to have slightly more zone air temperature violation in all scenarios compared to the other two intelligent controllers (i.e., DRLC and OBC). Third, a comprehensive fault impact analysis of the GDL36 was conducted to assess its fault robustness. How these sequences handle and adapt to various types of common faults was evaluated through a large-scale fault simulation. The results show that a vast majority (~90%) of fault scenarios have a fault impact ratio (FIR) of less than 6% for energy consumption and energy cost. Besides, the results of FIR distributions also indicate that GDL36 SOO only has limited influence on key performance indexes (KPIs) such as the supply air temperature control quality, thermal comfort, ventilation performance, and peak power load. Fourth, considering that the HVAC system configuration of multiple zone VAV systems with multiple recirculation paths has long been neglected in literature, a CO2-based demand control ventilation (DCV) was developed and quantitatively investigated in this study in terms of energy and ventilation performance. The proposed DCV control sequences were tested in four typical ASHRAE climate zones and proved to achieve considerable energy savings while maintaining an acceptable indoor air quality compliant with ASHRAE Standard 62.1. Lastly, an experimentally validated frequency regulation (FR) control scheme was integrated with the GDL36 SOO for air handling unit (AHU) fans from the perspective of the building providing ancillary service in the future. The impacts on the energy efficiency and thermal comfort were assessed and potential control conflict was identified when the VAV system provides frequency regulation using the GDL36 SOO. In summary, this dissertation developed a Modelica-based virtual testbed and evaluated the GDL36 SOO for multi-zone VAV systems in a holistic view. For energy efficiency, the GDL36 SOO achieved a comparable performance in terms of energy efficiency and thermal comfort with two intelligent supervisory controls in both high and mild cooling load conditions. For the fault robustness, it demonstrated that there were only minor fault impacts over different KPIs for the system with GDL36 SOO through a large fault simulation. From the ventilation aspect, the proposed DCV SOO for multi-zone recirculating path systems showed its energy efficiency and ventilation compliance and could be readily merged into GDL36. Lastly, when the AHU fan provides the FR service, the FR control could be integrated with GDL36 SOO with limited impacts on the HVAC system. Following prerequisites need to be met. First, the time-varying FR capacity must be correctly estimated. Second, an anti-saturation control scheme needs to be developed to avoid the fan power surge and ensure a smooth transition to post-FR operation.Item Development of New Whole Building Fault Detection and Diagnosis Techniques for Commissioning Persistence(2012-12-07) Lin, Guanjing; Claridge, David; O'Neal, Dennis; Culp, Charles; Jacobs, TimothyCommercial building owners spent $167 billion for energy in 2006. Building commissioning services have proven to be successful in saving building energy consumption. However, the optimal energy performance obtained by commissioning may subsequently degrade. The persistence of savings is of significant interest. For commissioning persistence, two statistical approaches, Days Exceeding Threshold-Date (DET-Date) method and Days Exceeding Threshold-Outside Air Temperature (DET-Toa) method, are developed to detect abnormal whole building energy consumption, and two approaches called Cosine Similarity method and Euclidean Distance Similarity method are developed to isolate the possible fault reasons. The effectiveness of these approaches is demonstrated and compared through tests in simulation and real buildings. The impacts of the factors including calibrated simulation model accuracy, fault severity, the time of fault occurrence, reference control change magnitude setting, and fault period length are addressed in the sensitivity study. The study shows that the DET-Toa method and the Cosine Similarity method are superior and more useful for the whole building fault detection and diagnosis.Item Development, Quantification, and Demonstration of the Occupancy-Based Controls for Smart and Healthy Buildings(2022-09-05) Pang, Zhihong; O'Neill, Zheng; Aryal, Ashrant; Claridge, David; Rasmussen, BryanThe heating, ventilation, and air-conditioning (HVAC) system consumes a significant fraction of building energy to maintain satisfactory indoor air quality (IAQ) and thermal comfort conditions for its occupants. Occupancy-based control (OBC) is attracting significant research interest since it could address the contradiction between the goals of reducing building energy consumption and maintaining occupants’ needs (e.g., thermal comfort). This research aims to investigate and validate the role of occupancy-based HVAC controls in smart and healthy buildings regarding energy efficiency and infection risk mitigation. First, this study develops a nationwide building energy simulation suite to quantify energy savings of occupancy-based HVAC controls. Multiple levels of diversities are considered in this simulation suite, including building types, climate zones, etc. Second, a cost-effectiveness analysis framework is established to quantify monetary savings. Third, field testing is conducted in real commercial and residential buildings to validate and evaluate the energy saving of OBC. The impact on occupants’ thermal comfort is also investigated and discussed. Last, a smart carbon dioxide (CO2) based ventilation algorithm is developed to mitigate the infection risk of COVID-19 in buildings while maintaining relatively good energy performance. The results suggest that in general, occupancy sensors demonstrate great energy-saving potential, especially for the buildings with densely occupied spaces and dynamic occupancy schedules. Many factors influence the energy-saving potential of OBC in commercial and residential buildings, among which the climate zone play the dominant role. For commercial buildings, the 30% HVAC energy-saving goal is tangible on a nationwide scale; while for residential buildings, applying a temperature setback during the unoccupied period is not likely to achieve 30% HVAC energy savings nationally. Second, the cost-effectiveness analysis shows that although the HVAC energy savings of OBCs are substantial, the actual cost-effectiveness is not that satisfactory. Occupant-counting sensors' economic performance (measured by discounted payback period) in commercial buildings highly depends on the building type. It is recommended to implement occupant counting sensors only for the most densely occupied zones in commercial buildings to reduce the costs and achieve a DPB shorter than five years. For residential buildings, it’s hard to achieve a shorter-than-two-year DPB for many climate zones by simply applying temperature setback control. Third, the field testing results suggest that the HVAC energy-saving ratio in real building operation basically matches the computer simulation. The sensor accuracy and occupant behaviors also play a dominant role in the energy-saving ratio of OBC. Besides, results show that the implementation of OBC did not affect the occupant’s comfort too much in the daytime but could not achieve good temperature control in the nighttime due to high false negative issues. Last, the proposed smart ventilation control algorithm allows building operators to flexibly secure the building operation safety based on the preset maximum infection risk level, so the balance between energy efficiency and infection risk mitigation is maintained. The results show that the proposed control reduces the infection risk by more than a half compared with traditional outdoor airflow fraction based mitigation measures and achieves higher energy efficiency performance.Item Dynamic Building Envelope with Phase Change Material (PCM) and Multi-Layered Fenestration Using Model Predictive Controls(2023-08-03) Feng, Fan; O'Neill, Zheng; Claridge, David; Culp, Charles H.; Pate, MichaelAs buildings are designed and operated towards reducing energy demand while maintaining a both thermally and visually comfortable environment for occupants, building envelope systems, including windows, external walls, doors, roof, etc., have the potential to reduce building energy consumption, improving the energy flexibility and mitigate greenhouse gas emissions. In this thesis, we have conducted a simulation-based study of a dynamic building envelope with thermally activated phase change material (PCM) panel and adjustable fenestration system. We first explored an integrated simulation approach to coordinate the simulation of daylighting, thermal and energy performance evaluation of the dynamic building envelope. Specifically, we have developed a Radiance model for daylighting performance estimation, and then this model was validated by carrying out a series of experiments under different conditions. The validation results showed that the Radiance modeling approach can generate reliable indoor illuminance estimations with Coefficient of the Variation of the Root Mean Square Error (CV(RMSE)) values of less than 25% and Normalized Mean Bias Error (NMBE) values of less than 15% for all control points. Second, we investigated a PCM modeling approach to enhance the current PCM model in EnergyPlus to better account for the hysteresis effects of industrial-grade PCM products. Compared to experimental measurements, the enhanced PCM module can have a good agreement with Mean Bias Error (MBE) values of 0.5oC and 0.59 oC for PCM layer average temperature in both complete and incomplete phase change processes, respectively. Using this improved PCM model, we created an EnergyPlus simulation model for Then, an integration approach was developed to co-simulation of the Radiance model and EnergyPlus model in run-time for the studied dynamic building envelope. Moreover, this integrated simulation model can also enable the evaluation of advanced control strategies such as model predictive control (MPC). Third, the integrated physics-based simulation models were used as a virtual testbed to develop and test the MPC controller. We developed a set of control-oriented models to predict the indoor thermal and visual conditions and the electricity consumption of both electrical lighting system and HVAC systems. These control-oriented models consist of a zone dynamics sub-model, an indoor illuminance prediction sub-model, and an electricity consumption prediction sub-model. These control-oriented models were then used as surrogate models to the physics-based simulation models, and the evaluation results showed that these control-oriented models can generate accurate and efficient predictions for indoor conditions and electricity consumption with CV(RMSE) values of less than 25% and NMBE values of less than 15% for testing dataset. Finally, an MPC controller was formulated and implemented to adjust the states of the fenestration system and regulate both the electrical lighting system and air-conditioning system in order to minimize the total electricity cost when a time of use utility rate is applied and without violating both the thermal and visual comfort requirements. Compared to a baseline case, the proposed MPC controller can improve the indoor environment comfort and reduce the total electricity cost up to 25% for a clear day with a typical load profile and up to 45.7% on a cloudy day with a moderate load profileItem The Effect of Thermal Load Configurations on Passive Chilled Beam Performance(2012-11-15) Nelson, Ian 1982-; Claridge, David; Culp, Charles; Duggleby, Andrew; O'Neal, DennisThis dissertation presents the findings of a study to quantify the effect of heat source configurations on the performance of passive chilled beams. Experiments in a thermally controlled test room were conducted using thermal manikins as heat sources cooled with a 0.6 m by 2.4 m beam. The thermal manikins were arranged in a symmetric and an asymmetric configuration and tested over a range of input power to simulate a low-to-high load heat distribution of an indoor space. A computational fluid dynamics (CFD) model was developed in Star CCM+ v6.06 and used for further analysis of the flow field and to predict additional spatial arrangements of the beam, interior dimensions, and heat source configurations. The CFD model implemented a calculation for the beam cooling capacity to predict the beam performance based on the room thermal conditions. The experimental data revealed an average reduction of 15% in the passive beam cooling capacity for the asymmetrically configured thermal manikins compared to the symmetric arrangement. The CFD model was validated with the experimental data and predicted the asymmetric heat source beam performance reduction to be 17%. The reduction in performance based on the heat source arrangement was found with analysis of the CFD simulations to be a result of the above-beam air velocity field. The unbalanced thermal manikin configuration generated an unbalanced flow condition at the inlet of the beam that resulted in the room air circumventing the inlet of the passive beam, as compared to the inlet velocity field of the symmetric configuration. Additional configurations were investigated with the CFD model to include the beam position, floor area, ceiling height, and thermal manikin arrangements. The simulation results were analyzed by comparing the efficiency of beam performance using the beam cooling capacity calculation for each scenario. The predictions of additional configurations found that the efficiency increased when the beam was perpendicular to a group of heat sources and the changes in beam performance with heat source configurations was not affected by the interior dimensions of the space. However, the resulting thermal conditions in the occupied zone for the beam positions of highest efficiency may negatively impact the thermal comfort of occupants.Item Electrical Demand Analysis Software Tool Suite and Automatic Report Generation for Energy Audits(2015-05-06) Morelli, Franco Javier; Rasmussen, Bryan; Culp, Charles; Claridge, DavidThe American Society of Heating, Refrigeration and Air Conditioning Engineers (ASHRAE) defines an energy audit through a multi-tiered stratagem characterized by the level of in-depth analysis. The Level 1, or walkthrough survey is highlighted by low to no cost energy efficiency evaluations and a list of improvement measures that warrant further inquiry. Through the Industrial Assessment Center (IAC) at Texas A&M University, the Department of Energy's, Advanced Manufacturing Office maintains collaboration with academic entities to further the goal of reducing industrial and manufacturing energy consumption. As a result, the IAC at Texas A&M University performs ASHRAE Level 1 Energy Audits for manufacturing plants across gulf coast states. The IAC at Texas A&M University seeks to develop a series of electrical demand analysis and report generation software tools to optimize and enhance the electrical investigation inherent with establishing efficient industrial resource (electricity, water, natural gas) usage. Typically, such analysis are done through utility bill information, quantifying usage and capital charge characteristics, as well as usage trends over the course of the billing period. By establishing electrical analysis through the use of 15-minute or 30-minute demand data sets, available to industrial and manufacturing clients augmented with Interval Data Recorder (IDR) meters, the Industrial Assessment Center at Texas A&M has developed a suite of electrical analysis tools designed to increase analysis fidelity, identify pre-visit Energy Conservation Measures (ECM), establish unknown variables helpful in diagnosing ECMs, size systems design to optimize electrical usage, create a simple, user friendly interface and increase ECM implementation. While the conclusions and results for the following work and tools will not be known for some time, preliminary efforts have shown that the tools are effective in interpreting and diagnosing aberrant electrical usage. In particular, one instance in usage of the demand visualization tool diagnosed an issue where a facility was being charged double the amount of their typical demand. Supporting data, along with key IAC visits will be required to determine if the following tools are effective in increasing IAC implementation rates.Item Energy Consumption and Financial Impact from Capital Projects at Utilities & Energy Services, Texas A&M University(2016-09-14) Sakurai, Yasuko; Pate, Michael; Claridge, David; Jacobs, Timothy; Welch, Ben David; Henry, RobertThis record of study presents the intern’s engineering and management experiences during her doctoral internship with Utilities & Energy Services (UES), Texas A&M University (TAMU) in partial fulfillment of the requirements for the Doctor of Engineering program. The intern was involved in the implementation of two capital projects, the chilled water system optimization project and the thermal energy storage tank project, during the internship period. Through this internship, the intern met her technical internship objectives of enhancing her understanding of the chilled water system, the “Demand Flow” optimization software, and the thermal energy storage tank operation. The efficiency of the west campus chilled water system and its avoided consumption and cost during the commissioning period were reported. The intern also acquired additional managerial skills development at UES through skill development courses by TAMU Employee & Organizational Development, and in practice as a UES manager. In addition to her involvement in project implementation, the intern was also interested in the energy consumption and financial impacts from implemented capital projects. These two projects were part of 2013 and 2014 UES capital projects, among a series of capital projects in the past ten years. Three system efficiency and financial indicators were introduced to benchmark the impacts from implemented capital projects starting in fiscal year (FY) 2004. Energy Utilization Index (EUI), EUI Ratio, and utility rates were the three indicators for benchmarking. The impacts of the two projects along with other capital projects were discussed through the projected results of the three indicators. The projected FY16 source and site EUIs were reduced mainly as a result of building consumption reduction efforts, while the projected EUI Ratio remained the same as previous year. The FY16 electricity and chilled water rates were decreasing because of lower purchased electricity rate and higher projected commodity consumptions. The chilled water rate reduction included the increase in debt and depreciation from chiller upgrades and other chilled water related capital projects. The FY16 heating hot water rate was increasing because of higher purchased natural gas rate.