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At least 19 records

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid contradictions such as having to choose one sub-component to generate performance diagnostics to another, possibly not fully consistent, component.

Todling, Ricardo↗

Modelling and Optimizing CSP-PV Hybrid Systems Using the Hybrid Optimization and Performance Platform (HOPP)

The hybridization of concentrating solar power (CSP) with thermal energy storage (TES), photovoltaics (PV), and electrochemical battery energy storage systems (BESS) has the potential to provide continuous, high-capacity-factor energy production at a lower cost than a PV-BESS or CSP with TES alone. Because of the system complexity of CSP technology, it is challenging to evaluate the technological and financial performance of a CSP-PV hybrid system without detailed modeling of annual operations. To address this challenge, we have developed a modeling framework for evaluating the performance and financial viability of CSP systems hybridized with PV and BESS technologies. This modeling effort incorporates CSP tower and trough configurations into an existing modeling tool recently developed by NREL, the Hybrid Optimization and Performance Platform (HOPP). This paper provides a brief overview of our methodology, as well as an example case study. CSP with TES hybridized with PV provides the best benefit-to-cost ratio compared to the other simulated technology combinations. However, for the conditions considered, this configuration only increases the benefit-to-cost ratio by about 1% compared to the CSP with TES configuration. The PV-BESS system provides the lowest benefit-to-cost ratio compared to the other configurations explored because of the relatively low capacity credit received by the system.

Hamilton, William (ORCID:0000000244654239)↗

Analysis of GaAs and Si solar energy hybrid systems

Various silicon hybrid systems are modeled and compared with a gallium arsenide hybrid system. The hybrid systems modeled produce electric power and also thermal power which can be used for heating or air conditioning. Various performance indices are defined and used to compare the system performance: capital cost per electric power out; capital cost per total power out; capital cost per electric power plus mechanical power; annual cost per annual electric energy; and annual cost per annual electric energy plus annual mechanical work. These performance indices indicate that concentrator hybrid systems can be cost effective when compared with present day energy costs.

Heinbockel, J. H.↗

Investigating realistic anode off-gas combustion in SOFC/ICE hybrid systems: mini review and experimental evaluation

Solid oxide fuel cells (SOFCs) have been deployed in hybrid decentralized energy systems, in which they are directly coupled to internal combustion engines (ICEs). Prior research indicated that the anode tailgas exiting the SOFC stack should be additionally exploited due to its high energy value, with typical ICE operation favoring hybridization due to matching thermodynamic conditions during operation. Consequently, extensive research has been performed, in which engines are positioned downstream the SOFC subsystem, operating in several modes of combustion, with the most prevalent being homogeneous compression ignition (HCCI) and spark ignition (SI). Experiments were performed in a 3-cylinder ICE operating in the latter modus operandi, where the anode tailgas was assimilated by mixing syngas (H 2 : 33.9%, CO: 15.6%, CO 2 : 50.5%) with three different water vapor flowrates in the engine’s intake. While increased vapor content significantly undermined engine performance, brake thermal efficiency (BTE) surpassed 34% in the best case scenario, which outperformed the majority of engines operating under similar operating conditions, as determined from the conducted literature review. Nevertheless, the best performing application was identified operating under HCCI, in which diesel reformates assimilating SOFC anode tailgas, fueled a heavy duty ICE (17:1), and gross indicated thermal efficiency ([Formula: see text]) of 48.8% was achieved, with the same engine exhibiting identical performance when operating in reactivity-controlled compression ignition (RCCI). Overall, emissions in terms of NO x and CO were minimal, especially in SI engines, while unburned hydrocarbons (UHC) were non-existent due to the absence of hydrocarbons in the assessed reformates.

Engineering↗

Mobile radio alternative systems study satellite/terrestrial (hybrid) systems concepts

The use of satellites for mobile radio service in non-urban areas of the United States in the years from 1985 to 2000 was investigated. Several satellite concepts are considered: a system with single-beam coverage of the fifty United States and Puerto Rico, and multi-beam satellites with greater capacity. All of the needed functions and services identified in the market study are provided by the satellite systems, including nationwide radio access to vehicles without knowledge of vehicle location wideband data transmission from remote sites, two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The costs of providing the services are within acceptable limits, and the desired returns to the system investors are attractive. The criteria by which the Federal Communication judges the competing demands for public radio spectrum are reviewed with comments on how the criteria might apply to the consideration of land mobile satellites. Institutional arrangements for operating a mobile satellite system are based on the present institutional arrangements in which the services are offered to the end users through wireline and radio common carriers, with direct access by large private and government users.

Kiesling, J. D.↗

Discovery of a Hybrid System for Photocatalytic CO 2 Reduction via Attachment of a Molecular Cobalt-Quaterpyridine Complex to a Crystalline Carbon Nitride

While recent reports have demonstrated the attachment of molecular catalysts to amorphous, graphitic carbon nitrides (g-CN) for light-driven CO 2 reduction, approaches to the utilization of crystalline carbon nitrides have remained undiscovered. Herein, a functional hybrid photocatalyst system has been found using a crystalline carbon nitride semiconductor, poly(triazine imide) lithium chloride (PTI-LiCl), with a surface-attached CoCl 2 (qpy-Ph-COOH) catalyst for CO 2 reduction. The molecular catalyst attaches to PTI-LiCl at concentrations from 0.10 to 4.30 wt % and exhibits ∼96% selectivity for CO production in a CO 2 -saturated, aqueous 0.5 M KHCO 3 solution. Optimal loadings were found to be within 0.42–1.04 wt % with rates between 1,400 and 1,550 μmol CO/g·h at an irradiance of 172 mW/cm 2 (λ = 390 nm) and apparent quantum yields of ∼2%. This optimized loading is postulated to represent a balance between maximal turnover frequency (TOF; 300+ h –1 ) and excess catalyst that can limit excited-electron lifetimes, as probed via transient absorption spectroscopy. An increase in the incident irradiance yields a concomitant increase in the TOFs and CO rates only for the higher catalyst loadings, reaching up to 2,149 μmol CO/g·h with a more efficient use of the catalyst surface capacity. The lower catalyst loadings, by comparison, already function at maximal TOFs. Higher surface loadings are also found to help mitigate deactivation of the molecular catalysts during extended catalytic testing (>24 h) owing to the greater net surface capacity for CO 2 reduction, thus representing an effective strategy to extend lifetime. The hybrid particles can be deposited onto an FTO substrate to yield ∼60% Faradaic efficiency for photoelectrochemical CO production at −1.2 V vs Ag/AgCl bias. In conclusion, these results demonstrate the synergistic combination of a crystalline carbon nitride with a molecular catalyst that achieves among the highest known rates in carbon-nitride systems for the light-driven CO 2 reduction to CO in aqueous solution with >95% selectivity.

CO2 reduction↗

Model-Based Prognostics of Hybrid Systems

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

prognosis↗

Energy Equity Opportunities in Distributed Wind Hybrid Systems for Rural Loads

Distributed wind (DW) hybrid systems, or combinations of distributed energy resources with wind technologies, have the potential to provide energy equity benefits for rural loads. However, project developers and end-users do not understand these benefits well. This report outlines energy equity opportunities that result directly from DW-hybrid projects and proposes a framework that demonstrates how to consider equity in the DW-hybrid system, which can enhance existing resilience and valuation tools by incorporating a way to include equity considerations. Energy equity opportunities achievable with DW-hybrid systems for rural loads are defined by the core principles of energy justice for use in a proposed equity framework. As well, a catalog of equity resources, metrics, technology-agnostic frameworks, and best practices are linked in an attached Excel file. Electric cooperatives, technical assistance providers (including national laboratory and DOE staff), DW project developers, and technology providers can use this work to understand, evaluate, and define equitable outcomes for potential DW-hybrid projects.

17 WIND ENERGY↗

A Dual-Mode Hybrid System Combining Solar Thermal With Pumped Thermal Energy Storage

A hybrid system that delivers renewable electricity generation and electricity storage capabilities is introduced. This dual-mode hybrid system is based on Pumped Thermal Energy Storage (PTES) which uses a heat pump to convert electricity into thermal energy that is trans-ferred to silica particles which are stored in concrete silos. The stored heat is later converted back to electricity in a heat engine. The heat pump and heat engine use a closed Joule-Brayton cycle and fluidized bed heat exchangers. If the PTES system is co-located with an array of concentrating solar mirrors and a particle receiver, then the silica particles may also be heated up by the concentrating solar power (CSP) system. The PTES heat engine may also be used to convert the stored solar heat into electricity, thereby sharing this system between the PTES and CSP systems and reducing costs. However, this requires careful management of the heat engine off-design parameters. A thermodynamic model is used to evaluate the performance of the dual mode PTES-CSP hybrid system. The model accounts for turbomachinery effi-ciency, and approach temperature and pressure loss in heat exchangers, as well as other sources of inefficiency, such as motor-generator losses, and air fan power. The hybrid system also requires the evaluation of the turbomachinery efficiency and pressure ratio at off-design conditions since the CSP system operates over different temperature ratios than the Carnot Battery. Several design variables and design modifications are investigated, such as pressure ratios and maximum temperatures.

14 SOLAR ENERGY↗

The First Experiment with VLBI-GPS Hybrid System

In this paper, we introduce our GPS-VLBI hybrid system and show the results of the first experiment which is now under way. In this hybrid system, GPS signals are captured by a normal GPS antenna, down-converted to IF signals, and then sampled by the VLBI sampler VSSP32 developed by NICT. The sampled GPS data are recorded and correlated in the same way as VLBI observation data. The correlator outputs are the group delay and the delay rate. Since the whole system uses the same frequency standard, many sources of systematic errors are common between the VLBI system and the GPS system. In this hybrid system, the GPS antenna can be regarded as an additional VLBI antenna having multiple beams towards GPS satellites. Therefore, we expect that this approach will provide enough data to improve zenith delay estimates and geodetic results.

Kwak, Younghee↗

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

Structural Decomposition↗

Viewing hybrid systems as products of control systems and automata

The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.

Grossman, R. L.↗

Resilience for Advanced Distributed Wind Systems: Identifying the resilience benefits of advanced controls and hybrid systems for distributed wind

Under the Department of Energy (DOE) Wind Energy Technologies Office (WETO), Idaho National Laboratory (INL) has been tasked with defining the resilience benefits of distributed wind systems for the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project. This project is a collaboration between the National Renewable Energy Laboratory (NREL), Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL). In the final year of this project, INL is collaborating with the other labs to bring together key results from our previous work on resilience, cybersecurity and risk, distributed wind hybrid systems, and valuation of distributed wind.

17 WIND ENERGY↗

Molecular Level Understanding of Polyethylene Terephthalate (PET) Depolymerization in Base/Alcohol Hybrid Systems

Polyethylene terephthalate (PET) depolymerization in base/alcohol hybrid systems represents a promising low-energy approach for chemically recycling PET waste into valuable monomers. This study investigates the mechanistic pathways of PET depolymerization in NaOH/alcohol solutions, emphasizing the competing roles of hydroxide and alkoxide species. Utilizing a combination of experimental techniques, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations, we explore how factors such as base concentration, alcohol chain length, and pKa values of alcohols influence PET depolymerization efficiency and pathways. Our findings indicate that alkoxide ions (RO⁻) exhibit notably higher reactivity than hydroxide ions (HO⁻), favoring an alcoholysis pathway in the base/alcohol hybrid system. Experimental results across a series of C1 to C5 alcohols show that longer-chain alcohols, particularly 1-butanol, achieve higher PET conversion, although this does not align solely with simple nucleophilicity trends of alkoxides. While DFT calculations reveal comparable activation energies for various alkoxides in PET depolymerization, MD simulations underscore the significant role of alcohol chain length, with longer-chain alcohols forming more stable or frequent interactions with PET. Additionally, the alkoxide concentration, influenced by the alcohol’s pK a , directly impacts PET conversion. These suggest that PET depolymerization is governed by a balance between alkoxide concentration and alkoxide-PET interactions, rather than activation energies or nucleophilicity alone. From a practical perspective, incorporating long-chain alcohols as cosolvents may enhance process efficiency but increases raw material costs by approximately 30%. However, long-chain alcohols present a safer and more sustainable alternative to hazardous cosolvents such as dichloromethane. This work offers a molecular-level understanding of PET depolymerization in base/alcohol systems and provides insights into optimizing these systems for more efficient and sustainable PET recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Particle Filters and Consistency-Based Approaches for Monitoring and Diagnosis of Stochastic Hybrid Systems

Fault detection and isolation are critical tasks to ensure correct operation of systems. When we consider stochastic hybrid systems, diagnosis algorithms need to track both the discrete mode and the continuous state of the system in the presence of noise. Deterministic techniques like Livingstone cannot deal with the stochasticity in the system and models. Conversely Bayesian belief update techniques such as particle filters may require many computational resources to get a good approximation of the true belief state. In this paper we propose a fault detection and isolation architecture for stochastic hybrid systems that combines look-ahead Rao-Blackwellized Particle Filters (RBPF) with the Livingstone 3 (L3) diagnosis engine. In this approach RBPF is used to track the nominal behavior, a novel n-step prediction scheme is used for fault detection and L3 is used to generate a set of candidates that are consistent with the discrepant observations which then continue to be tracked by the RBPF scheme.

Narasimhan, Sriram↗