Performance Of Configurations Research Articles

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. The performance of conventional control is highly driven by the physics-based, offline developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This paper describes a novel, fully data-driven probabilistic framework to derive a linear representation of post-contingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

Improving the Intensity Forecast of Tropical Cyclones in the Hurricane Analysis and Forecast System

Abstract A modification to the mixing length formulation in a planetary boundary layer (PBL) scheme is introduced to improve the intensity forecast of tropical cyclones (TCs) in a basin-scale Hurricane Analysis and Forecast System (HAFS) for the real-time experiment in 2021. The 2020 basin-scale HAFS with the physics suite of the NCEP operational Global Forecast System performs well in terms of the reduced root-mean-square (RMS) errors in track and intensity except for the mean intensity bias, compared with NCEP operational hurricane models. To address the large intensity bias issue, the vertical mixing length near the surface used in the PBL scheme is increased to follow the similarity theory, consistent with that used in the surface layer scheme. Test results show that the RMS error and bias in intensity are further reduced without the degradation of the track forecast. An idealized one-dimensional TC PBL model is used to understand the model response to the modification, indicating that the radial wind is strengthened to dynamically balance the enhanced downward momentum mixing. This is also exhibited in the case study of a three-dimensional HAFS simulation, with the improved vertical distribution of the simulated wind speed in the eyewall area. Given the improvement, the modification has been implemented in one of the configurations of the first version of the operational HAFS at NCEP. Finally, the adjustment of the parameterization of diffusion and mixing in TC simulations is discussed. Significance Statement A modification to the mixing length formulation in a PBL scheme is described, which improves the intensity forecast of tropical cyclones simulated in the Hurricane Analysis and Forecast System (HAFS). Retrospective tests indicate that the modification can reduce the root-mean-square error and bias of the simulated TC intensity by 5%–10% and 50%, respectively. This modification has been implemented in one of the operational configurations of HAFS, version 1, at NCEP, improving the hurricane model guidance.

Improved regional forecasting of an extreme Arctic cyclone in August 2016 with WRF MRI‐4DVAR

AbstractCycling data assimilation and forecast experiments in August 2016 together with a case study of an intense Arctic cyclone (AC16) are performed. Initial conditions from newly developed Multi‐Resolution Incremental Four‐Dimensional Variational (MRI‐4DVAR) and Three‐Dimensional Variational (3DVAR) data assimilation along with forecasts from the polar version of the Weather Research and Forecasting (Polar WRF) model, mimicking operational configurations, are applied. The tasks are to evaluate MRI‐4DVAR performance during a 20‐day cycling run, to investigate the impacts of initial conditions on the forecast skill of AC16, and to identify the factors impacting AC16's predictability. The results from the 20‐day cycling period demonstrate the robustness and reliability of MRI‐4DVAR for data assimilation and subsequent forecast skill. Multiple processes, including mergers of Arctic cyclones, mergers of vortices, vertical coupling between low‐level and upper‐level circulations, baroclinic processes and jet stream forcing, contributed to the generation and development of AC16. Compared to the initial conditions from 4DVAR, 3DVAR produced amplified polar vortices, stronger baroclinic instability, intensified upper‐level jet streams and a stronger low‐level frontal zone, causing the overdevelopment of AC16 in 3DVAR‐based forecasts. For MRI‐4DVAR, the accurate prediction of AC16 5–7 days ahead is likely due primarily to the more accurate representation of upper‐level atmospheric fields, that was facilitated by better satellite radiance assimilation with MRI‐4DVAR that also produced a balanced initial model state. It is concluded that the high‐resolution Polar WRF which is optimized for Arctic conditions combined with 4DVAR facilitated the improved prediction of AC16 compared to the Global Forecast System (GFS) operational deterministic global forecast.

Characterizing dynamic test fixtures through the modal projection error

Across many industries and engineering disciplines, systems of components are designed and deployed into their operational environments. It is the desire of the engineer to be able to predict if the component or system will survive its operational environment or if the component will fail due to mechanical stresses. One method to determine if the component will survive the operational environment is to expose the component to a simulation of the environment in a laboratory. One difficulty in executing such a test is that the component may not have the same boundary condition in both the laboratory and operational configurations. This paper presents a novel method of quantifying the error in the modal domain that occurs from the impedance difference between the laboratory test fixture and the operational configuration. The error is calculated from the projection from one mode shape space to the other, and the error is in terms of each mode of the operational configuration. The error provides insight into the effectiveness of the test fixture with respect to the ability to recreate the individual mode shapes of the operational configuration. A case study is presented to show the error in the modal projection between two configurations is a lower limit for the error that can be achieved by a laboratory test.

Enhancing economic viability: Optimal integration of an absorption power cycle for enhanced financial performance in flame-assisted fuel cells

In the realm of energy economics, where financial considerations are intertwined with policy imperatives, there is a pressing need for advanced power generation technologies, given the escalating CO2 emissions and global warming concerns. Flame-assisted Fuel Cells (FFCs) have surfaced as a promising innovation with several advantages; however, their low electrical efficiency remains a critical concern. A strategic approach is proposed to enhance FFC efficiency by effectively utilizing waste heat through the integration of an Absorption Power Cycle (APC). A comprehensive modeling encompassing exergy, environmental impact, financial factors, and policy alignment was executed, coupled with tri-criteria optimization to identify optimal operational conditions. Through a comparative analysis of the FFC/APC integrated system against the standalone FFC, considering varying operational parameters and optimal configurations, it is shown that despite incurring additional costs, the incorporation of the APC unit falls short of fully compensating for the supplementary power generation expenses. As a result, the combined cycle yields higher electricity costs compared to the standalone FFC. Nonetheless, the integrated system presents a significant increase in exergy efficiency, along with a reduction in CO2 emissions. This integration not only addresses energy efficiency and environmental concerns but also aligns with the broader objectives of transparency and sustainability in capital markets. These compelling advantages may position the integrated plant as a preferable choice among energy economists, policy makers, and environmental advocates, even considering the higher initial capital outlay, due to its alignment with broader economic, environmental, and policy objectives.

Genome-resolved correlation mapping links microbial community structure to metabolic interactions driving methane production from wastewater

Anaerobic digestion of municipal mixed sludge produces methane that can be converted into renewable natural gas. To improve economics of this microbial mediated process, metabolic interactions catalyzing biomass conversion to energy need to be identified. Here, we present a two-year time series associating microbial metabolism and physicochemistry in a full-scale wastewater treatment plant. By creating a co-occurrence network with thousands of time-resolved microbial populations from over 100 samples spanning four operating configurations, known and novel microbial consortia with potential to drive methane production were identified. Interactions between these populations were further resolved in relation to specific process configurations by mapping metagenome assembled genomes and cognate gene expression data onto the network. Prominent interactions included transcriptionally active Methanolinea methanogens and syntrophic benzoate oxidizing Syntrophorhabdus, as well as a Methanoregulaceae population and putative syntrophic acetate oxidizing bacteria affiliated with Bateroidetes (Tenuifilaceae) expressing the glycine cleavage bypass of the Wood–Ljungdahl pathway.

Evaluation of an Improved AROME Configuration for Fog Forecasts during the SOFOG3D Campaign

Abstract This paper evaluates fog forecasts of a new AROME configuration dedicated to fog thanks to observations of the recent field campaign SOuth westFOGs 3Dimensions (SOFOG3D). This new configuration takes advantage of an upgraded horizontal and vertical resolution of a two-moment microphysical scheme [Liquid Ice Multiple Aerosols (LIMA)], and of the inclusion of a parameterization of the droplet’s deposition onto vegetation. A statistical study conducted over the 6 months of the SOFOG3D field campaign allowed the evaluation of the quality of fog forecasts produced by this new configuration to compare it to the current operational configuration of AROME. The main findings are as follows: the new configuration forecasts more fog events, with a few more false alarms, but improved the amount of fog events with low top height and with a low water content, underestimated by the reference configuration. The importance of the first level height for a good representation of the first few meters above the ground is crucial to improve the fog formation forecast. A delay of fog dissipation in the morning was highlighted in operational simulations and slightly reduced thanks to LIMA. This two-moment scheme produced thinner fogs, with less water content. These are more realistic, compared with observations, and thinner fog is also easier for solar radiation to dissipate.

NETWORK KPI ANALYSIS IN NETWORK SHARING TECHNOLOGY CONFIGURATION BASED ON MULTI-OPERATOR CORE NETWORK (MOCN)

The reliable spread of BTS networks with high system capacity poses a challenge for operators in delivering services. An alternative strategy is network sharing, one of which is MOCN (Multi Operator Core Network). MOCN BTS is configured to share RF module and antenna resources by combining frequencies between operators while maintaining each operator's core. On the other hand, BTS not-pair is the conventional operator configuration where RF modules and antennas are installed independently without any connection to other operators. In this final project, a KPI data analysis is conducted for both BTS configuration to assess their reliability. Four BTS samples from two operators (IM3 and 3ID) are taken for this analysis. The analyzed KPI categories include Accessibility KPI, Retainability KPI, and Service Integrity KPI during busy hours. KPI data is obtained from field results and assisted by the technical team from Indosat Ooredoo Hutchison Pontianak. The analysis results indicate that in terms of Service Integrity KPI, BTS MOCN outperforms BTS not-pair, with a difference of 2.590175 Mbps for downlink and 0.286065 Mbps for uplink. Regarding Accessibility KPI and Retainability KPI, BTS managed by 3ID demonstrates better performance compared to those managed by IM3.

Hollow fiber membrane integrated water cooler: A novel liquid cooling solution

To address the issues of water–air cross-contamination, liquid droplet carryover, and high maintenance costs of traditional water-mediated evaporative cooling systems, the hollow fiber membrane integrated water cooler (MWC) is proposed as a novel liquid cooling solution. The MWC incorporates hydrophobic porous membranes that enable water vapor migration while avoiding direct contact between liquid water and air. In addition, the MWC offers advantages over conventional evaporative cooling paddings in terms of high specific surface area, corrosion resistance, and anti-scaling. To evaluate the cooling performance of a countercurrent MWC, an experimental bench was built to test its outlet water temperature under various operating conditions. The developed numerical model was verified with the measured data. Then, the influence of nine critical parameters, including operating conditions and membrane module specifications, on the outlet water temperature and cooling efficiency of the countercurrent MWC was numerically investigated. The results show that evaporative heat dissipation contributes to more than 80% of the total heat exchange in MWC. Cold and dry ambient air, high inlet water temperature, low water velocity, and high air/water ratio contribute to superior cooling capability. Moreover, the cooling performance of MWC improves with increasing fiber length, inner diameter, packing fraction, and decreasing membrane thickness. In addition, the MWC offers a cooling capacity per unit volume of up to 1094.72 kW/m3, an order of magnitude greater than conventional wet cooling towers. Overall, this work presents theoretical guidelines for optimizing the operating conditions and configuration of countercurrent MWCs.

100 MHz Symmetric Current-Mode Class D Wireless Power Transfer

Power conversion for wireless power transfer (WPT) at 100MHz is important for miniaturization and integration, which is critical for charging wearable consumer electronics, and devices for the Internet of Things (IoT). Design and implementation at this frequency are challenging in the selection of components and circuit configurations for operation over a wide load range. The optimization of the tuned compensation networks together with a step-by-step guide for a systematic and rigorous optimal design is derived in this paper from fundamental circuit models for symmetric current-mode class D (CMCD) WPT systems. Symmetric CMCD WPT systems can have inherently constant output current for a wide load range with small current ripple for the optimal design, which is useful in direct battery charging applications. Both uncontrolled and synchronous rectifiers are analyzed, demonstrated, and compared in hardware with the optimal designs. A 100MHz prototype with an output peak power of 6.9W has a power circuit dc–dc efficiency of 81.9% despite only natural convection cooling of miniaturized GaN devices. The prototype maintains nearly constant power circuit efficiency above 80.5% with a peak of 83.2% over a wide power range that spans from 1.7W to 6.9W.

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

One of the approaches to improve operation indices, such as power loss and reliability, is to smoothen voltage profiles. Energy management of generation units and network reconfiguration are two methods to achieve this. Hence, the latter is presented in this paper in a distribution with distributed generation units. To this end, an objective function is formulated aiming to minimize power loss and enhance the operating situation of the network. This problem is subject to various constraints and limits such as AC power flow equations, operation limits, planning model, and operation model of distributed generations. It is an integer nonlinear optimization problem and is solved using the crow search algorithm and the optimal solution is obtained. Two major innovations of the study include modeling generation units’ operation and network configuration mathematical expression of operation indicators. The method is applied to a test system and results demonstrate the high performance of this approach in improving the operation of the network. Finding the solution in less time with a satisfying standard deviation are two advantages of the proposed algorithm. Adopting this method, the network operator can reduce power loss through proper management of distributed generation power and optimal scheduling of switches. Moreover, the obtained voltage profile is more desirable in comparison to that of power flow studies.

A time-based double-sided readout concept of 100 mm LYSO:Ce,Ca fibres for future axial TOF-PET

BackgroundPositron emission tomography (PET) requires a high signal-to-noise ratio (SNR) to improve image quality, with time-of-flight (TOF) being an effective way to boost the SNR. However, the scanner sensitivity and resolution must be maintained. The use of axially aligned 100-mm LYSO:Ce,Ca scintillation crystals with double-sided readout has the potential of ground-breaking TOF and sensitivity, while reducing parallax errors through depth-of-interaction (DOI) estimation, and also allowing a reduction in the number of readout channels required, resulting in cost benefits. Due to orientation, these fibres may also facilitate the integration of TOF-PET with magnetic resonance imaging (MRI) in hybrid imaging systems. The challenge of achieving a good spatial resolution with such long axial fibres is directly related to the achievable TOF resolution. In this study, the timing performance and DOI resolution of emerging high-performance materials were investigated to assess the merits of this approach in organ-dedicated or total-body/large-scale PET imaging systems.MethodsLYSO:Ce,Ca scintillation fibres of 20 mm and 100 mm length were tested in various operating and readout configurations to determine the best achievable coincidence time resolution (CTR) and DOI resolution. The tests were performed using state-of-the-art high-frequency (HF) readout and commercially available silicon photomultipliers (SiPMs) from Broadcom Inc.ResultsFor the 100-mm fibre, an average CTR performance of 137 pm 1 ps FWHM and an average depth-of-interaction resolution within the fibre of 12.3 pm 0.5 mm FWHM could be obtained. The 20-mm fibre showed a sub-100 ps CTR of 98 pm 1 ps FWHM and a fibre resolution of 8.5 pm 0.2 mm FWHM in the double-sided readout configuration.ConclusionWith modern SiPMs and crystals, a double-sided readout of long fibres can achieve excellent timing resolution and field-advancing TOF resolution, outperforming commercial PET systems. With 100-mm fibres, an electronic channel reduction of about a factor 2.5 is inherent, with larger reduction factors conceivable, which can lead to lower production costs. The spatial resolution was shown to be limited in the axial direction with 12 mm, but is defined to 3 mm in all other directions. Recent SiPM and scintillator developments are expected to improve on the time and spatial resolution to be investigated in future prototypes.

Optimal resource optimisation based on multi‐layer monitoring

AbstractThe satisfaction of the Quality of Service (QoS) levels during an entire service life‐cycle is one of the key targets for Service Providers (SP). To achieve this in an optimal way, it is required to predict the exact amount of the needed physical and virtual resources, for example, CPU and memory usage, for any possible combination of parameters that affect the system workload, such as number of users, duration of each request, etc. To solve this problem, the authors introduce a novel architecture and its open‐source implementation that a) monitors and collects data from heterogeneous resources, b) uses them to train machine learning models and c) tailors them to each particular service type. The candidate solution is validated in two real‐life services showing very good accuracy in predicting the required resources for a large number of operational configurations where a data augmentation method is also applied to further decrease the estimation error up to 32%.

Aerodynamic Characteristics Analysis of Rectifier Drum of High-Speed Train Environmental Monitoring Devices

To study the aerodynamic characteristics of the convex structure of a surface-monitoring device on a high-speed train and to evaluate its impact on the aerodynamic performance of the high-speed train, numerical simulation research was conducted on three different layouts of the monitoring device. The computational fluid dynamics (CFD) method was used for the simulation study, and the unsteady compressible NS equation was used as the control equation. Hexagonal grid technology was used to reduce the demand for the grid quantity. The rationality of the grid size and layout was verified through grid independence research. To increase the accuracy of the numerical simulation, the γ-Reθ transition model and improved delayed detached eddy simulation (IDDES) method were coupled for the simulation research. The aerodynamic characteristics of the different operation directions and configurations were compared and analyzed. The research results showed that the windward side of the single pantograph detection device experienced positive pressure, and the sideline and leeward sides experienced negative pressure. Increasing the fillet radius of the sideline could appropriately reduce the aerodynamic resistance. When the speed was about 110 m/s, the drag force coefficient of the detection device was 210~410 N, and the lateral force was small, which means that it had little impact on the overall aerodynamic force of the train. According to the results of the unsteady analysis of the layout with a large space, the resistance during forward travel was greater than that during negative travel. The streamlined upwind surface was conducive to reducing the scope of the leeward separation zone and the amplitude of the pressure fluctuation in the leeward zone, and it thus reduced the resistance. For the running trains, a vortex was formed on their leeward surface. The pressure monitoring results showed that the separated airflow had no dominant frequency or energy peak. The possibility of the following train top and other components experiencing resonance damage is low.

Investigation of the feasibility of microgrid under three operational configurations using whale optimization algorithm

PurposeThis study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.Design/methodology/approachThree operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.FindingsThe obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.Originality/valueThe value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

Modeling Public Concerns for Unmanned Aerial System Operations in the National Airspace System

The Unites States commercial unmanned aerial system (UAS) market was valued at $99.6 million in 2020 and is projected to reach $3.7 billion by 2030. Applications for these commercial UAS range from risk mitigation and surveillance to package delivery. Coupled with these emerging applications are the unique factors that arise with a commercial UAS’s compact size and low-altitude flights among the civilian populace. In this work, a value model was created to attempt to aid in determining the infringement of a UAS operation configuration on a civilian environment. Value functions were developed in an additive model that measures infringement (a UAS’s encroachment or trespass on a right or privilege of a civilian) based on these attributes. The resulting value model was tested by running 100,000 random simulations. Analysis of the simulation results and sensitivity analysis of the model showed that fleet size, proximity, duration of the operation within a certain proximity, and total operation duration were the attributes that drove a UAS operation’s infringement on an environment. A use case of an Amazon delivery application was then examined. This is a realistic scenario simulated to study if duration of an operation and time near a structure are kept to a minimum, the infringement of an operation remained low. This study provides initial determination of how infringement of UAS can be quantified and what infringement values may look like for different operational scenarios.

Mapping adsorbent properties to optimal process performance of two-bed temperature swing adsorption by superstructure optimization

Temperature swing adsorption (TSA) is one of the promising separation techniques for large-scale CO2 capture, and many adsorbents are being developed today. However, it is difficult to identify the optimal operating configurations of multi-bed TSA process to fully utilize the potential of a given adsorbent. This is because optimal operating conditions and cycle configurations are highly dependent on the adsorbent properties. In this work, we propose a comprehensive approach that maps adsorption isotherms to the optimal multi-bed TSA operation identified from various alternatives. A case study for separation of CO2 and N2 is presented where isotherm properties of the adsorbent are parameterized to analyze the influence on the optimal TSA operating cycle configurations and process performance. Our analysis shows that the optimal throughput increases by 68% when the CO2 selectivity is doubled, and 96% when the CO2 selectivity and capacity are both doubled. Furthermore, the frequency of the reflux operations and the cycle time in the optimal operating cycle are found to be dependent on the CO2 capacity.

$\Delta V-\Delta I$ Plane-Based Line Faults Detection and Classification in DC Microgrid

The high fault current rise due to instantaneous capacitor discharge necessitates quick line fault detection in DC microgrids. Hence, this paper proposes a communication-less <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Delta V-\Delta I$</tex-math></inline-formula> plane-based line faults detection and classification scheme in a Low-Voltage (LV) DC microgrid using local parameters. Simultaneous threshold violations of difference of successive line current and bus voltage samples, with sum of squared currents and disagreement of instantaneous line current to its average echo, aid the scheme to identify forward and backward faults and categorize Pole-to-Ground (PG) and Pole-to-Pole (PP) faults. The proposed scheme is time-efficient as it quickly detects and classifies the worst possible close-in and line-end PG and PP High Resistance Faults (HRFs) within 0.72 ms. The proposed method's feasibility is validated in Real-Time Digital Simulator (RTDS), Numerical Relay Development Environment (NRDE), and microcontroller-based hardware in loop setup. Comparison with previous techniques and tests on two LV DC microgrids indicate that the thresholds in the proposed scheme can aid in quick fault (even line-end HRFs) detection. Also, the proposed scheme is robust to grid-connected and islanded modes of operation, ring and radial configurations, noise, and non-fault events, like load switching, varying power output of sources, and AC side and internal converter faults.

Comparison of Numerical Strategies for Historic Elevated Water Tanks: Modal Analysis of a 50-Year-Old Structure in Italy

The seismic vulnerability assessment of existing structures is a well-known challenging task, due to a combination of several aspects. The use of analytical or finite element (FE) numerical models can offer robust support in this analysis but necessitates the accurate calibration of geometrical and mechanical input, with related uncertainties. In this paper, attention is focused on the identification of dynamic parameters, based on modal numerical analysis, of a 50-year-old, reinforced concrete, elevated water tank (EWT) characterised by a reservoir with a truncated cone shape. The structure is located in a high seismic region of northern Italy and presently necessitates retrofit plans to preserve its functionality. Based on the limited available experimental evidence and technical drawings, major efforts are spent for the numerical prediction of fundamental vibration modes and frequencies of the structure, which represent a first key step for seismic analyses, under various water-filling levels. To this aim, four different FE numerical strategies able to include both structural features and possible fluid–structure interaction (FSI) effects are developed. By progressively increasing the computational cost (and expected the accuracy of the solutions), FE models based on added-mass (M0 model), spring-mass (M1-DM or M1-DS models), or acoustic (M2 model) strategies are taken into account and combined with increasing detailing in geometrical description of the structure. Results from parametric modal analyses are discussed for the case-study EWT, in terms of computational cost, possible numerical limitations, accuracy of predicted frequencies/modal shapes, sensitivity to water-filling levels and operational configurations, with the support of several pieces of experimental evidence and consolidated analytical formulations for fundamental frequency estimations.

Commentary from the left to the right side of the ledger: Fully expressing the real value of nursing.

Commentary from the left to the right side of the ledger: Fully expressing the real value of nursing.