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DOE OSTI2021

Dataset of low global warming potential refrigerant refrigeration system for fault detection and diagnostics

Abstract HVAC and refrigeration system fault detection and diagnostics (FDD) has attracted extensive studies for decades; however, FDD of supermarket refrigeration systems has not gained significant attention. Supermarkets consume around 50 kWh/ft 2 of electricity annually. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40%–60% of its total electricity usage and is equivalent to about 2%–3% of the total energy consumed by commercial buildings in the United States. Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Reducing refrigerant usage or using environmentally friendly alternatives can result in significant climate benefits. A challenge is the lack of publicly available data sets to benchmark the system performance and record the faulted performance. This paper identifies common faults of supermarket refrigeration systems and conducts an experimental study to collect the faulted performance data and analyze these faults. This work provides a foundation for future research on the development of FDD methods and field automated FDD implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗

DOE OSTI2020

Recovery of Alkaline-Earths into Liquid Bi in Ternary LiCl-KCl-SrCl 2 /BaCl 2 Electrolytes at 500 °C

Electrochemical reduction of Sr 2+ and Ba 2+ into liquid Bi was investigated in dilute concentrations of SrCl 2 /BaCl 2 (0-5 mol%) in LiCl-KCl electrolytes at 500 °C to ascertain the limit of liquid Bi electrodes for alkaline-earth recovery. Analysis of the electrodes after constant current electrolysis to the specific charge of 270 C g -1 showed Sr 2+ ions consuming 29% of charge at 5 mol% before dropping to 8%-10% of the total charge at 0.45-0.72 mol% SrCl 2 . Ba 2+ ions consumed 54% at 5 mol% BaCl 2 before decreasing to 22%-24% at 0.42-0.89 mol% BaCl 2 ; substantial co-deposition of Li was observed in all chemistries, consuming up to 53% of charge. Considering only 1% of the total charge was consumed for depositing Ba 2+ and Sr 2+ ions in ~0.1 mol% SrCl 2 /BaCl 2 electrolyte, the lower recovery limit of Bi for alkaline-earth elements is suggested to be at ~0.4 mol% SrCl 2 /BaCl 2 to achieve appreciable deposition of alkaline-earths (>1.5 mol% Ba/Sr in liquid Bi). The overpotentials of liquid Bi at 5 mol% of SrCl 2 /BaCl 2 were evaluated by electrochemical impedance spectroscopy. The co-deposition of Sr and Li exhibited the largest increase in charge transfer resistances implying sluggish charge transfer kinetics whereas the co-deposition of Ba and Li exhibited a large increase in mass transport resistances due to the slow diffusion of Ba 2+ ions in the electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Efficient and Safe Hydrogen Refueling of Fuel Cell Vehicles from an Emergency Chemical Hydride Storage Source

Zero-emissions hydrogen fuel cell electrical vehicles (FCEVs) have become more popular in recent years. However, the limited availability of hydrogen fueling stations is considered a critical barrier to sustainable adoption of hydrogen FCEV. To enable the widespread deployment and commercialization of hydrogen FCEV, the availability of hydrogen refueling stations needs to improve. One of the consequences of the lack of hydrogen refueling infrastructure is that consumers can suffer from “range anxiety”, meaning consumers would get anxious of running out of fuel during long-distance trip [4]. A practical solution is to provide a compact emergency hydrogen refueler that can be used if the consumer runs out of hydrogen before reaching the nearest hydrogen refueling station. A safe, compact, and user-friendly hydrogen refueler would give consumers the flexibility they need to feel comfortable using their hydrogen FCEV when planning a long-distance trip. Offering this product would alleviate range anxiety, and it would make Hydrogen FCEV a more attractive alternative to gasoline vehicles. The emergency hydrogen refueler consists of a lithium hydride bed that reacts with liquid water to produce hydrogen gas and lithium hydroxide.

08 HYDROGEN↗

DOE OSTI2021

Simple Acceptance Decisions and Acceptance Risk

Acceptance risk may be estimated using cumulative probability distribution functions applied to populations of measurands and test measurement values. “Simple acceptance” is a decision rule that sets the acceptance range of a test result equal to the tolerance range specification. While acceptance risk is comprised of both consumer risk and producer risk, this paper compares the effects of simple acceptance decision rules and guardbanding decision rules on consumer risk. Consumer risk is also known as the probability of false acceptance. The terms describe the risk of accepting test results as passing when the actual values exceed specification limits. False acceptance is only possible when the true value of a measurand is out of tolerance and the test result indicates that the measurand is within tolerance. Metrologists generally have some information about the test uncertainty regarding a specific acceptance test result. Along with a general lack of knowledge regarding the measurand population parameters, the complicated interplay between risk, dispersion, and central values generally prevents calibration laboratories from fully characterizing acceptance probabilities. Organizations that model the measurand populations can reduce consumer risk by avoiding certification of items whose measurand populations are not well centered. The models in this paper present a recurring trend: guardbanding reduces nonnegligible risks of false acceptance when compared to simple acceptance. However, guardbanding is not the most effective means of acceptance risk mitigation. Systematic characterization of measurand populations can provide the information a calibration laboratory needs to reliably control acceptance risk.

42 ENGINEERING↗

DOE OSTI2021

Connected Loads – Grid Connected Appliances: Commercial Refrigeration System Fault Detection and Diagnostics

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Understanding the Behavioral Aspects of Rate Design

Consumer demand for electricity has often been thought of as homogenous and inelastic. However, consumers may have preferences for their electricity consumption that they have been unable to realize due to the structures of electricity rates, and historic methods of regulation. As ratemaking becomes more dynamic, consumers will have a newfound ability to realize these preferences. This paper conducts a review of this issue through the lenses of utility regulation, neoclassical economics, and behavioral economics. It surveys what aspects of consumer preferences and behavior have been well established for the electricity sector and identifies gaps that could be filled by future research. This analysis has implications for stakeholders looking to understand how households will function in transactive and real time pricing environments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Connected Loads – Grid Connected Appliances: Deployment IoT Solution for Fault Detection and Diagnostics

As one of the most energy-intensive end-uses in the commercial buildings sector, supermarkets consume around 50 kWh/ft 2 ( or 537.6 kWh/m 2 ) of electricity annually, or more than 2 million kWh of electricity per year for a typical store. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40–60% of its total electricity usage and is equivalent to about 2–3% of the total energy consumed by commercial buildings in United States, or around 0.5 quadrillion Btu (or 0.53 quadrillion KJ). Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Current supermarket refrigeration systems rely on high global warming potential hydrofluorocarbon refrigerants. Reducing refrigerant usage or using environment friendly alternatives can result in significant climate benefits. Transcritical CO2 refrigeration systems have attracted more attention in recent years because of their zero-carbon emission advantages compared with traditional refrigerants. These systems are widely used in commercial buildings such as supermarkets. The refrigeration system can also be adapted to handle flexible building loads and be integrated into grid response transactive control to balance the supply and demand of the electric grid. Even minor improvements in the efficiency and operational reliability of supermarket refrigeration systems can create significant value in terms of saving energy, improving food quality, protecting the environment, reducing carbon footprint, and enhancing electric grid resilience. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50– 52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostics (AFDDs) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. This study reviews existing IoT solutions developed for building energy– related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Low-cost buffer storage for solar industrial steam applications

Motivation and importance: Many industrial process heat consumers operate throughout the day, and deep decarbonization with solar energy requires thermal energy storage. Thermal energy storage provides an additional operational benefit of firm delivery of steam – essential to reducing the risk of costly production interruptions. The group of process heat consumers that use steam for biofuels production for the California transportation fuels market is incentivized through the Low Carbon Fuel Standard (LCFS) to reduce their carbon intensity through the use of solar steam. Examples include ethanol and dimethyl ether production. The production of these and other fuels involves distillation driven by steam reboilers with steam pressures in the range 100-280 psig. These pressures can be delivered from the type of thermal energy storage that has been the focus of this project – a steam accumulator Sunvapor, Inc. (SVI) calls a “Bullet Steam Accumulator” or “BSA TM ”. Our project adds to the understanding of the design and integration of steam accumulators charged by solar thermal energy in a biofuels production facility, and similar facilities that consume process steam. The fuel application requires a demanding level of Process Safety Management not found in other steam applications. The type of steam accumulator SVI engineered and built integrates steam generation and storage in one vessel to reduce cost. Achieving a first of a kind permit to operate such a first device has also added to the understanding of the industrial application of such systems. Goals: The overall goal of the project has been to demonstrate the advantages that a “Bullet Steam Accumulator” (BSA™) can provide to solar steam integration with a manufacturing process. The industrial host has already been convinced of the potential of the available solar steam to lower than carbon intensity score. They have been interviewed for a number of publications such as that tout the advantages SVI’s system brings to their operations. Accomplishments: At the end of 2023 Sunvapor placed in service the country’s first industrial solar boiler with thermal energy storage. At the same time, this placement in service represents the first pilot commercial system to decarbonize biofuels production through the use of solar thermal energy. While the full technical effectiveness will be shown as soon as the customer’s plant is able to consume the available steam, the economic feasibility was indicated early in the project when the combination of costs and steam pricing required to meet investor expectations was determined. The project represents a reference pilot from which a full-scale commercial system may be expanded. This pilot is a necessary first step in providing the full potential benefits to the public, including decarbonization of transportation fuels. The decarbonization of the separation steps in fuels production may be the most cost-effective and nearest term solar fuel. Co-benefits include a reduction of air pollutants such as NOx and particulate matter, and job creation for the construction, operation and maintenance of industrial solar facilities.

14 SOLAR ENERGY↗

DOE OSTI2020

Frequency Analysis of Solar PV Power to Enable Optimal Building Load Control

In this paper, we present a flexibility estimation mechanism for buildings’ thermostatically controlled loads (TCLs) to enable the distribution level consumption of the majority of solar photovoltaic (PV) generation by local building TCLs. The local consumption of PV generation provides several advantages to the grid operation as well as the consumers, such as reducing the stress on the distribution network, minimizing voltage fluctuations and two-way power flows in the distribution network, and reducing the required battery storage capacity for PV integration. This would result in increasing the solar PV generation penetration levels. The aims of this study are twofold. First, spectral (frequency) analyses of solar PV power generation together with the power consumption of multiple building TCLs (such as heating, ventilation, and air conditioning (HVAC) systems, water heaters, and refrigerators) are performed. These analyses define the bandwidth over which these TCLs can operate and also describe the PV generation frequency bandwidth. Such spectral analyses, in frequency domain, can help identify the flexible components of PV generation that can be consumed by the various TCLs through optimal building load utilization. Second, a quadratic optimization problem based on model predictive control is formulated to allow consuming most of the low and medium frequency content of the PV power locally by building TCLs, while maintaining occupants’ comfort and TCLs’ physical constraints. The solution to the proposed optimization problem is achieved using optimal control strategies. Numerical results show that most of the low and medium frequency content of the PV generation can be consumed locally by building TCLs. The remaining high-frequency content of the PV generation can then be stored/offset using energy storage systems.

14 SOLAR ENERGY↗

DOE OSTI2020

Spinning the Facts against Genetically Engineered Foods?

A signaling game is developed in order to derive the equilibrium conditions under which special interest groups (SIGs) involved in the controversial debate over genetically engineered (GE) foods have the incentive to truthfully reveal their information or spin facts regarding the health impact of GE foods. Consumers can choose to inspect information provided by SIGs at a cost. The risk of spinning facts is much higher for pro-GE groups, because if it turns out that a certain GE food is unsafe, the penalty will be severe. However, anti-GE groups can still spin facts at low risk even if consumers choose to inspect. This helps explain why some pro-GE groups, particularly the biotech industry, tend to remain silent. Revealing information regarding the safety of GE foods could be counterproductive given pre-existing public skepticism. Consumers may not make “better” decisions with more information provided because more information increases their inspection costs. When it is costlier for consumers to inspect, it is more likely that anti-GE groups will continue to spin facts about the negative health impact of GE foods.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

DOE OSTI2021

Self-powered Heating: Efficiency Analysis

Conventional fuel-fired heating devices such as furnaces, boilers, and water heaters have fuel efficiency less than 100% on the basis of higher heating value. They also require electricity from the electric grid to power parasitic loads such as blowers, pumps, fans, and ignitors. The primary energy efficiency of the device accounts for both fuel used on-site and primary energy used off-site to produce electric power used by the device. This work compares conventional fuel-fired heating devices to two types of self-powered devices. A self-powered device (SPD) integrates a power cycle onboard to eliminate consumption of grid electricity. We assume that all heat rejected by the onboard power cycle is added to the process fluid, so that, compared with a conventional device, the same amount of heat is provided to the process fluid and the same amount of fuel is consumed, but grid electricity consumption is eliminated. The first SPD type is the basic one: exactly the electricity required is generated. The second type considered is the SPD with heat pump (SPD-HP), in which the power cycle generates more electricity than needed for parasitic loads, and the excess electricity is used to power a heat pump. The heat pump extracts additional heat from the ambient to boost efficiency. Both SPD and SPD-HP self-consume all the generated electricity, in contrast to combined heat and power (CHP) systems that export electricity. In this work, equations are derived to express the efficiency of three classes of heating devices: conventional (consuming grid electricity), self-powered (consuming no grid electricity), and self-powered with heat pump. The efficiency of each is derived as a function of up to six factors: (1) the fraction of combustion heat captured, (2) the rate of parasitic power consumption, (3) the fraction of electric energy dissipated as useful heat, (4) the power cycle conversion efficiency, (5) the grid efficiency, when applicable, and (6) the heat pump COP, when applicable. Scenarios are identified in which it is possible to achieve efficiency greater than 100% on a higher heating value basis. Plausible configurations using existing technology options are outlined.

Gluesenkamp, Kyle↗

DOE OSTI2022

Quantifying policy gaps for achieving the net-zero GHG emissions target in the U.S. light-duty vehicle market through electrification

The U.S. light-duty vehicle (LDV) industry, a major greenhouse gas (GHG) emitting sector, is embracing decarbonization. Considering only electrification pathways, this study uses publicly-available tools – MA3T and VISION on vehicle market penetration, fleet accounting and life-cycle analysis to quantify the policy gaps for LDVs to achieve the net-zero GHG emissions target in nine vehicle penetration cases under two electricity mix scenarios, including the U.S. administration's decarbonization strategy – 100% clean electricity by 2035. The MA3T model is a multinomial discrete choice model for market share projection by vehicle technology, and the VISION is a vehicle stocks and GHG emissions projection model by using vehicle and travel characteristics. This study projects the impacts of technology and policy enforcement on shaping the dynamics and decarbonization of the LDV market. Additionally, achieving the expected improvement of battery technology and charging infrastructure is critical but can only reduce the 2050 GHG emissions to 48–54% of the 2020 level under the electricity renewable mix scenario. It is almost impossible to achieve a 100% battery electric vehicle stock by 2050 and the 2050 net-zero target in the LDV industry unless ban of internal combustion engine technology is implemented starting in 2035 and under the 2035 100% clean electricity scenario. These extreme conditions also sacrifice most from the consumer welfare perspective. A greater policy forcing intensity accelerates plug-in electric vehicle penetration, while with declining marginal effect and reduced consumer welfare. Among the investigated policy scenarios, the policy forcing intensity equivalent to a fuel tax of $1–2 per gasoline gallon reduces the most GHG emissions while keeping a positive consumer welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

HD ADOPT: Heavy-Duty Vehicle Choice Model Documentation

HD ADOPT is a logit consumer vehicle choice and stock model that analyzes the Class 8 tractor market. The model projects future technology shares, fuel consumption, and greenhouse gas (GHG) emissions under input assumptions of technology progress, energy prices, and policies. ADOPT is distinguished from other vehicle choice models through inclusion of non-linear and heterogenous consumer preferences and characterization of the full range of market options rather than use of composite vehicles. In addition, ADOPT has integrated vehicle simulation capabilities that enable performance assessment and optimization of endogenous technology evolution. Optionally, the model is able to adjust this evolution to enforce compliance with fuel economy and GHG emissions regulations. Primary results include projection of technology shares and future in-use fleet energy demand, petroleum consumption, and GHG emissions. This enables analysis and comparison of future scenarios of technology improvements, economic conditions, and national policies. Recent new features for the HD modeling also enable examination of different on-board hydrogen fuel storage technologies from the lens of consumer preferences for vehicle cost and range. This report documents current ADOPT capabilities and methodologies.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Grid‐responsive smart manufacturing: A perspective for an interconnected energy future in the industrial sector

Abstract With the growing amount of renewable energy sources, the grid has become responsible for accounting for intermittency and the flexibility needed to utilize dynamic sources. Expensive peaking plants and energy storage systems have been proposed as ways to mitigate those problems. There is a large group of energy consumers that can respond to grid conditions. Historically, these consumers have been residential and commercial users, but with modern innovations and practices, industrial consumers have the potential to become a major player in this space. Grid‐responsive smart manufacturing can be used to utilize modern tools in manufacturing innovation as enablers for grid response. These modern tools already exist but are not widely used for industrial grid‐side energy management. This article defines grid‐responsive smart manufacturing, identifies five major barriers to its widespread implementation, and portrays the path to getting industrial users to be key players in grid stability and flexibility.

Billings, Blake W.↗

DOE OSTI2025

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗