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At least 181 records · Page 10

Fault Diagnosis in HVAC Chillers

Modern buildings are being equipped with increasingly sophisticated power and control systems with substantial capabilities for monitoring and controlling the amenities. Operational problems associated with heating, ventilation, and air-conditioning (HVAC) systems plague many commercial buildings, often the result of degraded equipment, failed sensors, improper installation, poor maintenance, and improperly implemented controls. Most existing HVAC fault-diagnostic schemes are based on analytical models and knowledge bases. These schemes are adequate for generic systems. However, real-world systems significantly differ from the generic ones and necessitate modifications of the models and/or customization of the standard knowledge bases, which can be labor intensive. Data-driven techniques for fault detection and isolation (FDI) have a close relationship with pattern recognition, wherein one seeks to categorize the input-output data into normal or faulty classes. Owing to the simplicity and adaptability, customization of a data-driven FDI approach does not require in-depth knowledge of the HVAC system. It enables the building system operators to improve energy efficiency and maintain the desired comfort level at a reduced cost. In this article, we consider a data-driven approach for FDI of chillers in HVAC systems. To diagnose the faults of interest in the chiller, we employ multiway dynamic principal component analysis (MPCA), multiway partial least squares (MPLS), and support vector machines (SVMs). The simulation of a chiller under various fault conditions is conducted using a standard chiller simulator from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE). We validated our FDI scheme using experimental data obtained from different types of chiller faults.

Choi, Kihoon↗

Research and Development of a Ventilation-Integrated Comfort System

From an indoor air quality perspective, the best residential ventilation strategies include filtering outdoor air and distributing that air to all occupied parts of a home. From an energy standpoint, it is desirable that energy be transferred from the exhaust air to the incoming outdoor air to limit heating and cooling impacts. Heat or energy recovery ventilators (HRVs or ERVs) can provide these functions, but researchers have seen many poor installations related to design, installation, and operation and maintenance. More robust ventilation systems may involve an ERV with a dedicated duct distribution system and controls. Such a duct system can be costly to install, and many builders reduce these costs by connecting an ERV to a central heating and cooling duct system. Although this can sometimes be done effectively, researchers have seen consistent challenges with low, inconsistent, or imbalanced flow rates; high electricity consumption; and—of greatest concern—outdoor air short-circuiting or not being delivered to occupied spaces at all. Most ERVs are designed to operate with their own duct system; they are not designed as an add-on to much larger heating, ventilating, and air-conditioning (HVAC) systems. The ventilation-integrated comfort system (VICS) is expressly designed to integrate with low-capacity, efficient, ducted heating and cooling systems. Overall, the latest VICS prototype consumed 40–75 watts (W), including the air handler power, to deliver 50–120 cfm of whole-dwelling ventilation. The large, cross-flow ERV core performed to match manufacturer values (73% winter sensible effectiveness, 64% summer total effectiveness), but further improvements are possible. The VICS system researched and tested during this project will provide efficient, controllable, balanced energy recovery ventilation that is integrated with heating and cooling systems. The integration reduces space and ductwork needed for separate ventilation systems, and there are no compromises to heating, cooling, or ventilation performance. The integrated nature of the device also reduces risks for improper installation and commissioning. Even when using the air handler blower to distribute outdoor air, the total power consumption is lower than that of most available ERV products in the same airflow range. This system has the potential to offer very high-performance ventilation with much smoother and simpler installation than conventional systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Space Suit Portable Life Support System Thermal Control Valve Ball Design

A Thermal Control Valve (TCV) has been in development for the Exploration Extravehicular Mobility Unit Portable Life Support System (xEMU PLSS). The xEMU PLSS TCV controls flow going to the liquid cooling and ventilation garment that the crew member wears during extra-vehicular activity to expel waste heat. A previous TCV version with a linear actuator and diverter valve has been tested to attempt to control the flow accurately. The previous valve has a non-linear flow response relative to valve position and has struggled to meet the setpoints desired for precise thermal control. While many diverter valve design variations have been attempted, all previous designs have had difficulty meeting set points. Additionally, high precision machining is required to create a metal-on-metal seal which has its own drawbacks and does not always meet requirements for internal leakage. This metal seal also requires stalling a linear actuator to load the seal in compression or tension which has caused sticking failures when stalled. A new approach and design for a TCV has been developed which uses a rotational ball to control flow and has demonstrated a much more precise and linear flow control. The design functions like a two-way ball valve with two Teflon seats that cradle and compress the ball for sealing. The ball outlet has a unique geometric design to create a set-able orifice like hole which is more predictable at controlling flow. Additionally, the Teflon seat performs much better for preventing internal leakage than the metal seal and prevents sticking by having a large range in which it is sealed without having to stall the actuator. This paper will review a new proposed xEMU PLSS TCV ball design and compare it with previous iterations of the design.

Ryan Ogilvie↗

Space Suit Portable Life Support System Thermal Control Valve Ball Design

A Thermal Control Valve (TCV) has been in development for the Exploration Extravehicular Mobility Unit Portable Life Support System (xEMU PLSS). The xEMU PLSS TCV controls flow going to the liquid cooling and ventilation garment that the crew member wears during extra-vehicular activity to expel waste heat. A previous TCV version with a linear actuator and diverter valve has been tested to attempt to control the flow accurately. The previous valve has a non-linear flow response relative to valve position and has struggled to meet the setpoints desired for precise thermal control. While many diverter valve design variations have been attempted, all previous designs have had difficulty meeting set points. Additionally, high precision machining is required to create a metal-on-metal seal which has its own drawbacks and does not always meet requirements for internal leakage. This metal seal also requires stalling a linear actuator to load the seal in compression or tension which has caused sticking failures when stalled. A new approach and design for a TCV has been developed which uses a rotational ball to control flow and has demonstrated a much more precise and linear flow control. The design functions like a two-way ball valve with two Teflon seats that cradle and compress the ball for sealing. The ball outlet has a unique geometric design to create a set-able orifice like hole which is more predictable at controlling flow. Additionally, the Teflon seat performs much better for preventing internal leakage than the metal seal and prevents sticking by having a large range in which it is sealed without having to stall the actuator. This paper will review a new proposed xEMU PLSS TCV ball design and compare it with previous iterations of the design.

Ryan Ogilvie↗

Space Suit Portable Life Support System Thermal Control Valve Ball Design

A Thermal Control Valve (TCV) has been in development for the Exploration Extravehicular Mobility Unit Portable Life Support System (xEMU PLSS). The xEMU PLSS TCV controls flow going to the liquid cooling and ventilation garment that the crew member wears during extra-vehicular activity to expel waste heat. A pervious TCV version with a linear actuator and diverter valve has been tested extensively to attempt to control the flow accurately. The previous TCV diverter valve has a non-linear flow response relative to valve position and has struggled to accurately meet the setpoints desired for precision thermal control. While many diverter valve design variations have been attempted, previous designs have all had difficulty in meeting set points. Additionally, high precision machining is required for these diverter valves to create a metal-on-metal seal which has its own drawbacks and doesn’t always meet requirements for internal leakage. This metal compression seal also requires stalling the linear actuator to load the seal in compression or tension which has demonstrated valve sticking failures when stalled. The xEMU PLSS TCV implements a new approach and design for a TCV which uses a rotational ball to control flow and has demonstrated a much more precise and linear flow control. The design functions like a two-way ball valve with two Teflon seats that cradle and compress the ball for sealing. A new geometric design modification to the ball outlet can create a set-able orifice like hole which is more predictable at controlling flow than using an annulus with the previous diverter valve. Additionally, the Teflon seat performs much better for preventing internal leakage than the metal seal and prevents sticking by having a large range in which it is sealed without having to stall the actuator. This paper will review a new proposed xEMU PLSS TCV ball design and compare it with previous iterations of the design.

Ryan Ogilvie↗

Multi-Fidelity Modeling and Control for Building Temperature Control

The ability to control energy loads such as a building's heating, ventilation, and air conditioning (HVAC) system can help facilitate increased penetration of variable renewable energy sources into the electric grid. To be able to control these HVAC systems more effectively, detailed simulations of the corresponding building physics is becoming increasingly important. These detailed simulations can be complex, nonlinear, and can require immense computational power when used in an advanced control method such as model predictive control (MPC), prompting the need to explore less computationally intensive strategies. In this work, a multi-fidelity approach is proposed to combine samples from a complex, high-fidelity model with a simple, low-fidelity model within the MPC control loop. More specifically, the parameters of a reduced-order, linear building model are periodically updated with knowledge from its high-fidelity counterpart - an EnergyPlus model - in an online fashion using a Gaussian Process surrogate model. Hence, highly accurate predictions of current and future conditions in a building are maintained with a substantially reduced computational burden compared to using the high-fidelity models alone. In other words, this linear parameter varying model preserves the low computational requirements of a low-order linear model while accurately modeling a building's dynamics. This allows a building controller to take highly informed actions without requiring a large computational budget.

building modeling↗

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using spacecraft trace contaminant control systems to cure sick building syndrome

Many residential and commercial buildings with centralized, recirculating, heating ventilation and air conditioning systems suffer from 'Sick Building Syndrome.' Ventilation rates are reduced to save energy costs, synthetic building materials off-gas contaminants, and unsafe levels of volatile organic compounds (VOC's) accumulate. These unsafe levels of contaminants can cause irritation of eyes and throat, fatigue and dizziness to building occupants. Increased ventilation, the primary method of treating Sick Building Syndrome is expensive (due to increased energy costs) and recently, the effectiveness of increased ventilation has been questioned. On spacecraft venting is not allowed, so the primary methods of air quality control are; source control, active filtering, and destruction of VOC's. Four non-venting contaminant removal technologies; strict material selection to provide source control, ambient temperature catalytic oxidation, photocatalytic oxidation, and uptake by higher plants, may have potential application for indoor air quality control.

Graf, John C.↗

Analysis of Frost Prevention for Heat Recovery Ventilation in an Arctic Facility

Sub-Arctic environments present a unique challenge for the continuous operation of mechanical ventilation systems in occupied buildings where cold temperatures create complications for maintaining adequate air quality, efficiency, and system operability. Heat recovery ventilation is most difficult at the coldest temperatures, when there is the greatest availability to transfer heat between airstreams, due to the potential for frost accumulation in the exhaust airstream. Frost limits heat transfer and creates the potential for subsequent blockage of airflow. A successful frost prevention strategy is necessary to ensure that recovery ventilation systems function in locations with a large amount of annual heating degree days. Commonly, this is achieved by preheating outdoor air above freezing temperatures via airflow through a glycol-water mix hydronic coil before heat exchange occurs. Preheating the outdoor air proactively inhibits frost formation but is associated with a penalty to recovery efficiency. A commercial-scale heat recovery ventilator in a facility in Fairbanks, Alaska was analyzed for sensible recovery effectiveness and exhaust temperature at different winter conditions. The system utilized the common defrost strategy of preheating the air above-freezing with a static temperature control scheme. The heat transfer efficiency of the recovery ventilator was observed to be poor at various winter conditions with elevated exhaust temperatures indicating lost heat recovery effectiveness. Using prior findings on strategies for sub-freezing temperatures along with observed field conditions it was determined that a dynamic relationship between the coil and the exterior conditions would reduce the energy required to preheat the air and allow the heat exchanger to maximize effectiveness due to temperate difference. This reduction in preheated temperature of the air is achieved by modulating the temperature of the coil to keep the discharge air stream above a certain dewpoint temperature threshold, likely leading to energy savings for other sub-Arctic facilities using this frost control strategy.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

EMU Ventilation Loop Simulation and Assessment of Contamination of the EMU Sublimator Hydrophilic Coating

Controlling moisture is a critical function performed in the space suit during extra vehicular activity (EVA) missions. Currently, this function is carried out by a sublimator, which is coated with a hydrophilic material. Tests have shown that siloxane compounds can off gas from the helmet absorption pad extension (HAP-E) and helmet absorption band (HAB) when they are at elevated temperatures and initial testing indicated that siloxanes could damage the hydrophilic coating. Therefore, more representative testing was needed. Important test considerations were source and destination kinetics, system geometries, scrubbing efficacy by the activated charcoal from the Metox canister, and other benefits that derive from active condensation occurring on the hydrophilic coating during exposure. A ventilation loop that was originally constructed to test hardware for control of CO2 and trace contaminants under EVA conditions was modified to conduct the siloxane off gassing tests. A vacuum compatible acrylic chamber was installed to simulate the suit volume. A steel beaker located in the chamber contained the HAP-E and HAB materials and was heated with two band heaters. The flow exiting the chamber passed through a LiOH cannister, which contained carbon beds to simulate their function in the Metox. The flow then was directed into a smaller volume that contained a coupon, which was coated with the hydrophilic material and was maintained at 10°C (50°F). Moisture was injected upstream of the suit volume simulator to maintain the dew point between 12.7°C (55°F) and 18.3°C (65°F). The pressure was controlled to between 3.8 and 4.4 psia, and the flow was held at 6 acfm. The system was run for an equivalent of 25 ten-hour EVAs, where the HAP-E/HAB materials were changed out after each EVA. The effect of the potential off gassing on the coupon was measured after each EVA period.

PLSS↗

Cluster analysis of occupancy schedules in residential buildings in the United States

The energy performance of residential buildings significantly depends on the building occupants’ behavior, which can be highly variable. When the heating, ventilation and air conditioning (HVAC) system is controlled based on the presence or absence of occupants in a building, occupant behavior is of even further importance to its energy performance. In current practice, building energy simulation tools generally use a single occupancy profile to represent the building’s occupancy schedule, the schedule of which is considered to be the same, regardless of the type of household being modeled. Thus, there is significant potential for improvement to allow for more flexibility and accuracy in calculation of occupancy. The objective of this study is to assess the variations in the typical types of occupancy schedules followed by the U.S. population using cluster analysis. American Time Use Survey data, which statically represents the overall U.S. population’s activities, across 12 years (2006–2017), is used. The ATUS data is segregated into smaller groups based on age and weekday/weekend, then divided into activities that are considered “at home” and “away from home”, which are mapped to the presence or non-presence of occupants in the home. Cluster analysis is then used to identify common types of occupancy schedule patterns for each age group. Three main types of patterns are obtained from cluster analysis for each age group, which together represent approximately 88% of people in the United States. The output of the cluster analysis is further analyzed to evaluate the variation in characteristics, including the number of times leaving home, time of day when leaving the home, and the timespan of absence from the home. The results of this study provide detailed insights on how typical occupants in the United States spend their time in residential spaces which can be used to create occupancy profiles for residential buildings. Finally, these occupancy profiles could be utilized inform an assessment of the energy use impact of occupancy-based controls of energy consuming systems and technologies.

42 ENGINEERING↗

Dialogue Between Lighting and HVAC Systems: Improving building system integration

Lighting systems have long been capable of sensing when someone enters or exits a room and using that knowledge to turn lights on or off. More recently, connected lighting systems with sensors integrated into every luminaire have become broadly available, facilitating highly granular occupancy detection. Similarly, HVAC systems have long been able to use an understanding of building occupancy to adjust temperature setpoints and reduce energy use without significant impacts to occupant comfort. Energy codes (e.g., ASHRAE/IES Standard 90.1, IECC, Title 24) now require “occupied standby HVAC control,” whereby systems adjust both temperature and ventilation setpoints in zones that are determined to be unoccupied during normal occupancy hours. Here, this article discusses current issues that stymie the integration of Lighting and HVAC systems, and DOE activities focused on addressing them.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CELSS for advanced manned mission

An overview of the major concepts of Controlled Ecological Life Support System (CELSS) includes an identification of environmental factors, such as gravity levels, light levels, and growth volume, that influence the type of CELSS system that can be developed. Various plant growth systems are described together with their possible space applications. Life support functions performed by plants include food production, atmosphere regeneration, and water purification. Selected relationships between biological and physical-chemical life support techniques are considered as a part of these functions. Consumers in a CELSS may be humans, animals, or microorganisms, but nutritional, water, and atmosphere requirements of humans are emphasized in this report, as they are the primary requirement drivers for a CELSS design. The human role in waste generation is discussed as it affects plant nutrient availability. The role of waste management systems in recovering nutrients for plant growth and requirements for CELSS are defined for air, water, and food. Both physical and a biological nutrient recovery/waste disposal systems are examined. The separate subsystems of a CELSS are identified and discussed. Nutrient recovery, plant irradiation, automation, and facilities equipment and applications are reviewed with special attention to direct solar irradiation using fiber optics. These subsystems, along with other environmental control systems, such as thermal, humidity, and ventilation, are essential to plant growth in the space environment.

NASA Discipline Life Support Systems↗

Hydrostatic Hyperbaric Chamber Ventilation System

The hydrostatic hyperbaric chamber (HHC) represents the merger of several technologies in development for NASA aerospace applications, harnessed to directly benefit global health. NASA has significant experience developing composite hyperbaric chambers for a variety of applications, including the treatment of medical conditions. NASA also has researched the application of water-filled vessels to increase tolerance of acceleration forces. The combination of these two applications has resulted in the hydrostatic chamber, which has been conceived as a safe, affordable means of making hyperbaric oxygen therapy available in the developing world for the treatment of a variety of medical conditions. Specifically, hyperbaric oxygen therapy is highly-desired as a possibly curative treatment for Buruli Ulcer, an infectious condition that afflicts children in sub-Saharan Africa. Hyperbaric oxygen therapy is simply too expensive and too dangerous to implement in the developing world using standard equipment. The hydrostatic hyperbaric chamber technology changes the paradigm. The HHC differs from standard hyperbaric chambers in that the majority of its volume is filled with water which is pressurized by oxygen being supplied in the portion of the chamber containing the patient s head. This greatly reduces the amount of oxygen required to sustain a hyperbaric atmosphere, thereby making the system more safe and economical to operate. An effort was taken to develop an HHC system to apply HBOT to children that is simple and robust enough to support transport, assembly, maintenance and operation in developing countries. This paper details the concept for an HHC ventilation and pressurization system that will provide controlled pressurization of the system, and provide adequate washout of carbon dioxide while the subject is enclosed in the confined space during the administration of the medical treatment. The concept took into consideration operational complexity, safety to the patient and operating personnel, and physiological considerations. The simple schematic, comprised of easily acquired commercial hardware, supports sustainability.

Sargusingh, Miriam M.↗

An analysis of the hybrid internal mass modeling approach in EnergyPlus

Accurate simulation of building system dynamics is particularly important for understanding building energy flexibility. Among all dynamics in a building, a zone temperature’s variation is especially important, as it significantly affects a building’s electricity load profile when its heating, ventilating, and air conditioning (HVAC) system is controlled with on/off cycles or setpoint reset strategies. To accurately simulate a zone temperature’s dynamics, internal mass needs to be modeled carefully. In this paper, we compare the two internal mass modeling approaches provided by EnergyPlus, i.e., internal mass object and zone air capacitance multiplier, to better understand their impacts on zone temperature simulation. Real building zone temperature dynamic data from small- and medium-sized office buildings are analyzed and compared with simulated data. In particular, we illustrate the effectiveness of a hybrid method of the two EnergyPlus modeling approaches, which yields more realistic zone temperature dynamics, especially when the zone is conditioned with heat pump systems with on/off cycling.

Chen, Zhelun↗

A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems

Use of renewable energy resources can play a significant role in mitigation of climate change since they reduce the dependency on fossil fuels. However, high penetration of renewable energy resources into the power grid may cause some reliability problems. Ancillary services are key to realize the potential of renewable resources without disturbing the grid reliability. In recent years, many control approaches focused on exploiting the aggregate flexible heating, ventilation, and air-conditioning (HVAC) loads of buildings. However, there are still research gaps in assessing in advance the resulting indoor temperature responses for given total power and weather profiles before implementing the controls in the buildings. Such an assessment is critical to guarantee satisfying both the grid related objective (reliability) and the building related objective (occupants' comfort). Towards addressing this research gap, this paper presents a machine-learning approach for predicting the ratings of indoor temperature responses. In this approach, a prediction model was developed using a dataset generated by a set of model-free control simulations. The developed model achieved high prediction accuracy and showed the potential of the proposed approach.

Amasyali, Kadir↗

Building Load Control Using Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty and the Risk-Adjustable Variants

Aggregation of heating, ventilation, and air conditioning (HVAC) loads can provide reserves to absorb volatile renewable energy, especially solar photo-voltaic (PV) generation. In this paper, we decide HVAC control schedules under uncertain PV generation, using a distributionally robust chance-constrained (DRCC) building load control model under two typical ambiguity sets: the moment-based and Wasserstein ambiguity sets. We derive mixed integer linear programming (MILP) reformulations for DRCC problems under both sets. Especially, for the Wasserstein ambiguity set, we use the right-hand side (RHS) uncertainty to derive a more compact MILP reformulation than the commonly known MILP reformulations with big-M constants. All the results also apply to general individual chance constraints with RHS uncertainty. Furthermore, we propose an adjustable chance-constrained variant to achieve tradeoff between the operational risk and costs. We derive MILP reformulations under the Wasserstein ambiguity set and second-order conic programming (SOCP) reformulations under the moment-based set. Using real-world data, we conduct computational studies to demonstrate the efficiency of the solution approaches and the effectiveness of the solutions. Summary of Contribution: The problem studied in this paper is motivated by a building load control problem that uses the aggregation of heating, ventilation, and air conditioning (HVAC) loads as flexible reserves to absorb uncertain solar photovoltaic (PV) generation. The problem is formulated as distributionally robust chance-constrained (DRCC) programs with right-hand side (RHS) uncertainty. In addition, we propose a risk-adjustable variant of the DRCC programs, where the risk level, instead of being predetermined, is treated as a decision variable. The paper aims to provide tractable reformulations and solution algorithms for both the (general) DRCC and the (general) adjustable DRCC models with RHS uncertainty.

97 MATHEMATICS AND COMPUTING↗