Impacts of simultaneous operating faults on cooling performance of a high efficiency residential heat pump
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Construction & Building Technology↗
SEARCH · Engineering Papers
Results for “Operational Efficiency”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Monitoring Based Commissioning: Step-by-Step Approach to Implementation in Chiller Plants
Chilled water systems consume a significant portion of the energy in manufacturing, and inefficient operation could significantly influence utility bills and the environmental footprint of a facility. One way to ensure long-term energy-efficient plant operation is to ensure that chilled water system equipment, such as chillers, cooling towers, and pumps, are running at their best. Periodic operational assessments help to meet efficiency objectives for cooling plants. However, occasional set point and operational changes resulting from short-term fluctuations cause the plant operation to deviate from optimal. These changes accumulate over time, and operational efficiency deteriorates. Significant energy efficiency improvement potential in chilled water systems can be achieved by operational changes alone. Recent developments in information technology and the industrial internet of things data processing ability have overcome traditional problems and given rise to a new paradigm: monitoring-based commissioning (MBCx). Commissioning platforms and fault detection and diagnostics capabilities have evolved over time and presented more sophisticated abilities to efficiently control process cooling plants. The typical architectures of the MBCx process and a detailed approach to implement the process for chilled water systems are presented. A case study highlighting the energy-and cost-savings potential of MBCx systems is also presented.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
S-QGPU: Shared quantum gate processing unit for distributed quantum computing
We propose a distributed quantum computing (DQC) architecture in which individual small-sized quantum computers are connected to a shared quantum gate processing unit (S-QGPU). The S-QGPU comprises a collection of hybrid two-qubit gate modules for remote gate operations. In contrast to conventional DQC systems, where each quantum computer is equipped with dedicated communication qubits, S-QGPU effectively pools the resources (e.g., the communication qubits) together for remote gate operations, and, thus, significantly reduces the cost of not only the local quantum computers but also the overall distributed system. Our preliminary analysis and simulation show that S-QGPU's shared resources for remote gate operations enable efficient resource utilization. When not all computing qubits (also called data qubits) in the system require simultaneous remote gate operations, S-QGPU-based DQC architecture demands fewer communication qubits, further decreasing the overall cost. Alternatively, with the same number of communication qubits, it can support a larger number of simultaneous remote gate operations more efficiently, especially when these operations occur in a burst mode.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
A Network-Aware Distributed Energy Resource Aggregation Framework for Flexible, Cost-Optimal, and Resilient Operation
To efficiently use the ubiquitous behind-the-meter distributed energy resources (DERs) in distribution systems for providing grid services, this paper presents a hierarchical control framework for DER optimal aggregation and control. We first develop a convex optimization model to evaluate the DER flexibility, and then use a convex model-predictive-control based approach to dispatch those DERs. The hierarchical control framework consists of a utility controller, community aggregators and multiple home energy management systems. The flexibility of the DERs is evaluated by each controller in the hierarchy such that the resultant flexibility is feasible given its operational domain. Based on the determined flexibility, the hierarchical controllers then compute optimal setpoints for the DERs to help the distribution system regulate node voltages and provide other distribution grid services. Numerical simulations performed on a model of a real distribution feeder in Colorado, using actual DER data in a residential community demonstrate that the proposed approach can effectively alleviate voltage issues and support resilient operation.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Operation of internal combustion engine with improved fuel efficiency
A process of operating a spark-ignited internal combustion engine (SI-ICE) with improved fuel efficiency and reduced emissions including under steady state and under lean-operating conditions at high overall air to fuel (AFR) ratios. A first supply of high octane hydrocarbon fuel, such as gasoline or natural gas, and a first supply of oxidant are fed to a fuel reformer to produce a gaseous reformate with a reforming efficiency of greater than 75 percent relative to equilibrium. The gaseous reformate is mixed with a second supply of oxidant, after which the resulting reformate blended oxidant is fed with a second supply of high octane hydrocarbon fuel to the SI-ICE for combustion. Steady state fuel efficiency is improved by more than 3 percent, when the reformate comprises from greater than about 1 to less than about 18 percent of the total volume of reformate blended oxidant fed to the engine.
33 ADVANCED PROPULSION SYSTEMS↗
Optimizing the Operational Parameters of an Electrochemical Purification Cell for Corrosion Mitigation in CSP Plants During Operation: Preprint
To make concentrating solar power (CSP) cost-competitive, the next generation of CSP plants will increase efficiency by operating at a higher temperature, which will require a new thermal energy storage material. One option for the thermal energy storage material is a ternary chloride salt that is stable at the temperatures required, but reacts easily with the atmosphere to form MgOHCl, a corrosive impurity. If left unchecked, this impurity will corrode the containment alloys, potentially leading to dangerous spills. We are working to design an electrochemical purification cell to remove MgOHCl from the molten chloride salt during CSP plant operation. In this paper, we use predictive modeling to assess the rate at which purification must occur. Additionally, we analyze possible process flow pathways for the molten chloride salts. Ultimately, we determine that implementation of a single reactor through which all chloride salts flow is the most efficient design to reduce impurity concentration below 0.1 mol % impurity.
concentrating solar power↗
LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)
The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.
14 SOLAR ENERGY↗
Evaluation of the Energy, Hygrothermal, and Thermal Capacity Performance of Cross-Laminated Timber
Cross-laminated timber (CLT) construction is gaining momentum in the US because it offers multiple advantages over traditional construction methods. Benefits that have received the most attention focus on constructability, the environment, and protection (e.g., blast resistance), although CLT construction is likely to offer other benefits, as well. Still, these have not been studied at length because such evaluations are costly, requiring long-term assessments in an actual building and specialized technical knowledge. Among the possible benefits, CLT construction likely provides a higher-performing building envelope. Using CLT panels to enclose a building means fewer joints in the opaque envelope than what is required in traditional stick-framed construction. Fewer joints mean fewer locations where the air- and water-resistive barrier (WRB) could be compromised; thus, a CLT building enclosure may require less maintenance and have a longer lifespan than a traditionally built structure because of fewer air and water leaks. In addition, CLT’s thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours, reducing operational energy consumption throughout the lifetime of the CLT building (Salonvaara et al., 2022). Furthermore, more stable indoor temperatures can increase occupant comfort. The CLT’s thermal mass can also reduce energy costs by adjusting to utility time-of-use pricing without affecting occupant comfort. The ability of CLT buildings to bridge periods without HVAC operation prepares them for future grid interaction and provides a certain level of resilience against power outages. Researchers have attempted to quantify these benefits; however, their work is based on simplified simulations with numerous assumptions. To correctly understand the benefits, an actual building must be monitored. Therefore, information needs to be gathered on indoor and outdoor temperatures, HVAC energy consumption, thermostat setpoints, temperatures, and thermal transport in CLT components to comprehend how these parameters are affected by the CLT’s thermal mass. These data are needed to reduce the number of assumptions and calibrate simulation models to optimize HVAC controls to minimize overall energy consumption, reduce energy use and higher fees during peak demand, and maintain occupant comfort. Additionally, the calibrated simulation model allows the optimization exercise to be repeated in various US climates. Potential benefits can be tailored to buildings in various locations, and decisions can be made on where CLT construction could be most advantageous. Furthermore, monitoring and simulation results are needed to evaluate the durability of the CLT structures in different climates. This project’s researchers gathered information to help understand and quantify the benefits of CLT buildings concerning operational energy, moderated indoor temperatures, and comfort; the dynamic operation to provide grid services; and resilience in times of power outage. Through the corroboration of simulation models with real-world measurements, this study paves the way for extrapolating findings to other climatic zones and building typologies, thereby broadening the understanding of CLT’s multifaceted benefits and reinforcing its position as a material of choice in sustainable construction.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Perovskite Solar Module: Promise and Challenges in Efficiency, Meta‐Stability, and Operational Lifetime
Abstract Perovskite photovoltaics (PVs) are an emerging solar energy generation technology that is nearing commercialization. Despite the unprecedented progress in increasing power conversion efficiency (PCE) for perovskite solar cells (PSCs), up‐scaling lab‐made cells to solar modules remains a challenge. In this work, the recent progress of making perovskite mini‐modules is reviewed. In particular, a database summarizing the module size, performance, hysteresis, and operational lifetimes reported in the literature is built. After analyzing the performance losses from scaling PSCs to mini‐modules based on the data collected from the literature, the current key to high‐performance perovskite mini‐modules is found to be the coating method optimization. If the perovskite layer quality is well reserved, a >24% mini‐module efficiency is projected by only considering the losses from lateral resistivity and laser scribing area. Next, performance characteristics are explored including hysteresis and meta‐stable power outputs that must be overcome to correctly characterize perovskite modules. Finally, current challenges associated with the long‐term stability of perovskite modules are examined and the importance of such durability for commercialization is discussed. It is hoped that the findings in this review provide a bridge for the development of perovskite modules that will lead to commercialization in the near future.
36 MATERIALS SCIENCE↗
High-Fidelity Heavy-Duty Vehicle Modeling Using Sparse Telematics Data
Heavy-duty commercial vehicles consume a significant amount of energy due to their large size and mass, directly leading to vehicle operators prioritizing energy efficiency to reduce operational costs and comply with environmental regulations. One tool that can be used for the evaluation of energy efficiency in heavy-duty vehicles is the evaluation of energy efficiency using vehicle modeling and simulation. Simulation provides a path for energy efficiency improvement by allowing rapid experimentation of different vehicle characteristics on fuel consumption without the need for costly physical prototyping. The research presented in this paper focuses on using real-world, sparsely sampled telematics data from a large fleet of heavy-duty vehicles to create high-fidelity models for simulation. Samples in the telematics dataset are collected sporadically, resulting in sparse data with an infrequent and irregular sampling rate. Captured in the dataset was geospatial information, time series measurements, and vehicle-specific metadata from a subset of 96 vehicles from varied geographic regions across North America. A series of custom algorithms was developed to process vehicle data and derive both vehicle model input parameters and representative drive cycles. Derived models provide a basis on which to simulate real-world vehicles and iterate on vehicle aerodynamics, auxiliary power loads, transmission shift schedules, and other parameters to achieve reduced fuel consumption and increase energy efficiency. Notably, these models were developed without the use of expensive field data collection, using only data collected through fleet telematics. Processed representative drive cycles are used to validate the fuel economy of derived models. The models developed through this research allow for more representative vehicle simulations with increased flexibility regarding vehicle-to-vehicle variations.
ADVANCED PROPULSION SYSTEMS↗
Enabling Efficient Surveillance, Control, and Automation of Geothermal Operations with Advanced Predictive Analytics
Automation and control of geothermal energy production and operations require reliable and efficient predictive tools. While physics-based simulation offers a comprehensive tool for predicting energy production performance in geothermal systems, predicting the behavior of geothermal reservoirs involves complex multi-physics processes with coupling effects, highly uncertain input parameters and subsurface descriptions. Moreover, building, running, and integrating simulation models into standard model calibration and optimization workflows entail significant technical and computational efforts. An emerging alternative to physics-based simulation is data-driven predictive analytics models that have gained popularity in energy industry. In this report, we develop novel predictive models for integration into real-time fault diagnosis and model predictive control algorithms to improve the efficiency of energy production operations in geothermal reservoirs. The report includes two major research Thrust Areas, that is, the surface power plant and the subsurface reservoir.
15 GEOTHERMAL ENERGY↗
Development of Structure–Property Relationships for Ammonium Transport through Charged Organogels
Ammonia is a promising carbon-free fuel, but current methods to produce ammonia are energy intensive. New methods are thereby needed, with one promising method being electrochemical nitrogen reduction cells. Efficient cell operation requires robust catalysts but also efficient membrane separators that permit the selective transport of ions while minimizing the transport of the products across the cell. Commercial membranes have an unknown morphology which makes designing improved cells challenging. To address this problem, we synthesized a series of membranes with controlled crosslinking density and chemical composition to understand their impact on ammonium transport. Higher crosslinking density led to lower ammonium permeability. At the highest crosslinking density, similar ammonium permeability was observed independent of the water volume fraction and hydrophobicity of the monomers. These results suggest new directions to develop membranes with reduced ammonium crossover to improve the efficiency of these electrochemical cells.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent developments in catalyst-related PEM fuel cell durability
Cost and durability remain the two major barriers to the widespread commercialization of polymer electrolyte membrane fuel cell (PEMFC)-based power systems, especially for the most impactful but challenging fuel cell electric vehicle (FCEV) application. Commercial FCEVs are now on the road; however, their PEMFC systems do not meet the cost targets established by the U.S. Department of Energy, primarily due to the high platinum loading needed on the cathode to achieve the requisite performance and lifetime. Furthermore, while the activities of a number of commercial Pt-based alloy cathode catalysts exceed the beginning-of-life (BOL) targets, these activities, and the overall cathode performance, degrade via a variety of mechanisms described herein. Degradation is mitigated in current FCEVs by utilizing a cathode catalyst with a lower BOL activity (e.g., much lower transition metal alloy content and larger BOL nanoparticle size), necessitating higher catalyst loadings, and through the utilization of system controls that avoid conditions known to exacerbate degradation processes, such as limiting the fuel cell stack voltage range. The design and development of active and robust materials and eliminating the need for vehicle mitigation strategies would greatly simplify the operating system, allowing for greater transient operation, avoiding large hybridization, and curtailing of fuel cell power. Although system mitigation strategies have provided the near-term pathway for FCEV commercialization, material-specific solutions are required to further reduce costs and improve operability and efficiency. Future material developments should focus on stabilization of the electrode structure and minimization of the catalyst particle susceptibility to dissolution caused by oxide formation and reduction over PEMFC cathode-relevant operating potentials plus minimization of support corrosion. Ex situ accelerated stress tests have provided insight into the processes responsible for material and performance degradation and will continue to provide useful information on the relative stability of materials and benchmarks for robust and stable materials-based solutions not requiring system mitigation strategies to achieve adequate lifetime.
25 ENERGY STORAGE↗
Artificial Intelligence for Data Center Operations (AI Ops)
HPC data centers such as the one at NREL's ESIF will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence (AI) and machine learning (ML) approaches provide the means to improve HPC data center efficiency (energy, operational, and managerial efficiency) and resiliency by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. The goal of coupled improvement of data center resiliency and energy efficiency through automated data collection and AI has led to a multi-year, multi-staged collaboration between NREL and Hewlett-Packard Enterprise's Advanced Technology Group, referred to as Artificial Intelligence for Data Center Operations (AIOps). The extended efforts within the AIOps project include a common goal of building capabilities for an advanced smart facility and demonstration of data collection and AI modeling techniques in the ESIF data center.
97 MATHEMATICS AND COMPUTING↗
Automated Cyber Security Testing Platform for Industrial Control Systems
Nuclear Power Plants (NPPs) are a complex system of coupled physics controlled by a network of Programmable Logic Controllers (PLCs). These PLCs communicate process data across the network to coordinate control actions with each other and inform the operators of process variables and control decisions. Networking the PLCs allows more effective process control and provides the operator more information which results in more efficient plant operation. This interconnectivity creates new security issues, as operators have more access to the plant controls, so will bad actors. As plant networks become more digitized and encompass more sophisticated controllers, the network surface exposed to cyber interference grows. Understanding the dynamics of these coupled systems of physics, control logic, and network communications is critical to their protection. The research into the cybersecurity of the Operational Technologies of NPPs is developing and requires a platform that can allow high fidelity physics simulations to interact with digital networks of controllers. This will require three main components: a network simulation environment, a physics simulator, and virtual PLCs (vPLC) that represent typical industry hardware. A platform that incorporates these three components to provide the most accurate representation of actual NPP networks and controllers is developed in this paper.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Low-Cost, Durable and Retrofittable Methane Oxidation Catalysts (Abstract)
There is significant concern over the contributions of GHG emissions to global warming which has sparked intense focus on reducing GHG emissions in industrial processes. In response, this project aims to develop and demonstrate a methane oxidation catalyst that can be deployed on NG engines used in US O&G industry and will serve to significantly reduce the carbon footprint associated with those midstream operations. The catalyst will achieve 90% oxidation efficiency while operating at 450°C or less and at 50% less Pd versus existing catalyst technology. This technology would enable the realization of nearly 30% reduced GHG emissions from NG engines (versus diesel) that methane slip from these engines otherwise negates.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
State of the art in low-temperature and high-temperature electrolysis
Water electrolysis is gaining traction in large-scale applications, with production of multiple technologies scaling to hundreds and thousands of megawatts of new electrolyzer capacity annually. Low-temperature electrolysis has dominated the electrolyzer market for decades, but still only represents a small amount of the overall hydrogen market, due to the higher production costs versus hydrogen derived from fossil fuels. Advances are needed in capital cost and efficiency to close the cost gap, especially for energy applications. Similarly, while high-temperature electrolyzers can operate more efficiently, reducing the operating cost, they still need further scale-up and cost reduction to compete in these markets. Understanding the recent advances in each and the priority research directions is important to focus and accelerate innovation, and will be discussed in this article. The different advantages and disadvantages of each of these technologies will also be reviewed; there will likely be applications for each in the overall deployment of renewable hydrogen.
36 MATERIALS SCIENCE↗
Energy Model to Evaluate Thermal Energy Storage Integrated with Air Source Heat Pumps: Preprint
Full decarbonization in buildings requires the replacement of combustion appliances with electric ones, and air source heat pumps (ASHP) are a candidate alternative. However, technical limitations, such as the efficiency decrease when operating in cold weather, limit their adoption in the global heating market. Among several options to improve ASHP efficiency operating in colder climates, thermal energy storage (TES) has been considered, as it may provide heating when it is cold and shift ASHP operation to times when the weather is warmer. It may also take advantage of time of use electricity rates and support defrosting when necessary. The evaluation of ASHP-TES systems, however, is still limited because traditional metrics do not capture their full economic and environmental benefits. In this work, a python framework is presented to model the ASHP with and without the presence of TES. Metrics are proposed to analyze the system performance in terms of costs, equivalent CO2 emission, and efficiency metrics to evaluate and compare alternative systems. Model validation against experimental data obtained for a commercial heat pump is provided, as well as an application example using Denver, Colorado, to highlight the model capabilities.
cold climate↗