Local Generation Research Articles

Tackling Class-imbalanced Learning Issues Based on Local Neighborhood Information and Generative Adversarial Networks

Tackling Class-imbalanced Learning Issues Based on Local Neighborhood Information and Generative Adversarial Networks

Flame Combustion State Detection Method of Cement Rotary Furnace Based on Improved RE-DDPM and DAF-FasterNet

It is of great significance to effectively identify the flame-burning state of cement rotary kilns to optimize the calcination process and ensure the quality of cement. However, high-temperature and smoke-filled environments bring about difficulties with respect to accurate feature extraction and data acquisition. To address these challenges, this paper proposes a novel approach. First, an improved denoising diffusion probability model (RE-DDPM) is proposed. By applying a mask to the burning area and mixing it with the actual image in the denoising process, local diversity generation in the image was realized, and the problem of limited and uneven data was solved. Secondly, this article proposes the DAF-FasterNet model, which incorporates a deformable attention mechanism (DAS) and replaces the ReLU activation function with FReLU so that it can better focus on key flame features and extract finer spatial details. The RE-DDPM method exhibits faster convergence and lower FID scores, indicating that the generated images are more realistic. DAF-FasterNet achieves 98.9% training accuracy, 98.1% test accuracy, and a 22.3 ms delay, making it superior to existing methods in flame state recognition.

Magnetically Integrated Multiport Converter for Energy Management in DC-Powered Buildings

Multiport converters have gained attention in the last few years as a key component for dc-powered buildings, more electric aircraft, and maritime applications. For buildings, the prevalence of dc appliances and electronic loads increases the need for efficient integration with both ac grid and local generation. Ac-dc multiport converters play an important role in this integration because dc distribution has been considered for power integration in modern buildings. In addition, the growing complexity of loads and sources within buildings has driven interest in developing flexible solutions to provide highly efficient integration. Furthermore, ongoing developments in standardization for in-building dc grids underscore the importance of considering specific requirements for future designs. This paper proposes a multiport power converter (ac/dc/dc) to integrate dc-powered buildings into an ac grid. By providing a multiport solution, it is possible to reduce the power processing stages and the component count. To evaluate the effectiveness of this concept, a 5-kW prototype was built and tested, including efficiency evaluation. In addition, emerging standards are discussed to tailor the power converter design for building applications.

Exploring local chlorine generation through seawater electrolysis to Extend optical sensor lifespan in marine environments

Biofouling in marine optical sensors poses a significant challenge as it can compromise data accuracy and instrument functionality. This study investigates the effectiveness of local chlorine generation by seawater electrolysis in mitigating biological fouling and extending the operational lifespan of optical oceanographic instruments. Eight similar turbidity probes integrated with a local chlorine generation system, along with a turbidity probe constructed from ABS and another from PLA with copper filament, were developed for testing in the marine environment. The chlorine probes were designed into two groups: four utilizing standard FTO glass and four featuring FTO glass coated with platinum nanoparticles. Each set of probes employed different excitation currents for chlorine generation. All probes underwent laboratory calibration using formazine before deployment in a coastal environment for 97 days. The findings demonstrate a correlation with higher electrical power leading to prolonged operation intervals free from biofouling interference. Additionally, probes coated with platinum nanoparticles demonstrate higher performance in comparison to those with standard FTO glass. The copper probe did not effectively shield the optical transducers from microfouling, although it effectively demonstrated its efficacy in protecting the structural housing of the device. Overall, this work offers a compelling in situ demonstration of local chlorine generation as a promising strategy for enhancing the performance and longevity of optical oceanographic instruments in marine environments.

Assessing the impact of local energy generation and storage to achieve the decarbonization of the single-family housing stock in Germany

Assessing the impact of local energy generation and storage to achieve the decarbonization of the single-family housing stock in Germany

Observations of Elevated Mixing and Periodic Structures Within Diurnal Warm Layers

AbstractSurface drifters (SWIFTs) equipped with down‐looking high‐resolution acoustic doppler current profilers (ADCPs) were used to estimate the turbulent kinetic energy (TKE) dissipation rate within highly stratified diurnal warm layers (DWLs) in the Southern California Bight. Over a 10‐day period, five instances of DWLs were observed with strong surface temperature anomalies up to 3°C and velocity anomalies up to 0.3 m . Profiles of in the upper 5 m suggest turbulence is strongly modulated by the DWL stratification. Burst‐averaged (8.5 min) is stronger than predicted by law‐of‐the‐wall boundary layer scaling within the DWLs and suppressed below. Predictions for within the DWLs are improved by a shear‐production scaling using observed shear and linearly decaying turbulent stress. However, is still under‐predicted. Examination of the un‐averaged acoustic backscatter data suggests elevated is related to the presence of turbulent structures in the DWLs which span the layer height and strongly modulate TKE. Evolution in the bulk Richardson number each day suggests the DWLs become unstable to layer‐scale overturning and entrainment each afternoon, thus the turbulent structures may result from shear‐driven instability. This interpretation is supported by a conditional average of the data during a burst characterized by strongly periodic structures. The structures resemble high‐frequency internal waves with strong asymmetry in the along‐flow direction (steepening) which suggests they are unstable. Coincident asymmetric patterns in upwelling/downwelling and corresponding regions of strong vertical convergence/divergence suggest that both vertical transport and local TKE generation are plausible sources of elevated in the DWLs.

Thresholds for the value judgement of health technologies in the United Arab Emirates: a consensus approach through voting sessions

BackgroundIn the evolving healthcare landscape of the United Arab Emirates (UAE), establishing cost-effectiveness thresholds (CETs) is pivotal to informing decision-makers about the value of health technologies.ObjectiveThis study aimed to establish...

Intracranial voltage profiles from untangled human deep sources reveal multisource composition and source allocation bias.

Intracranial potentials are used as functional biomarkers of neural networks. As potentials spread away from the source populations, they become mixed in the recordings. In humans, interindividual differences in the gyral architecture of the cortex pose an additional challenge, as functional areas vary in location and extent. We used source separation techniques to disentangle mixing potentials obtained by exploratory deep arrays implanted in epileptic patients of either sex to gain access to the number, location, relative contribution and dynamics of co-active sources. The unique spatial profiles of separated generators made it possible to discern dozens of independent cortical areas for each patient, whose stability maintained even during seizure, enabling the follow up of activity for days and across states. Through matching these profiles to MRI, we associated each with limited portions of sulci and gyri, and determined the local or remote origin of the corresponding sources. We also plotted source-specific 3D coverage across arrays. In average, individual recording sites are contributed to by 3-5 local and distant generators from areas up to several centimeters apart. During seizure, 13-85 % of generators were involved, and a few appeared anew. Significant bias in location assignment using raw potentials is revealed, including numerous false positives when determining the site of origin of a seizure. This is not amended by bipolar montage, which introduce additional errors of its own. In this way, source disentangling reveals the multisource nature and far intracranial spread of potentials in humans, while efficiently addressing patient-specific anatomofunctional cortical divergence.Significance Statement Field potentials are used to better localize zones showing normal and pathological activity. However, as potentials spread throughout the brain volume, they mix with others and make their place of origin uncertain, even when recorded intracranially. We used advanced algorithms to disentangle the activity of each these zones by their unique spatial profiles, which allowed us to determine the 3D outline of normal and epileptic areas and follow their activity for days. Dozens of independent sources per patient can be explored and precisely located. The findings show that standard stereoEEG recordings are contributed by 3-5 populations, which after separation will help to plan clinical intervention to break epileptic networks by more accurately marking epileptic foci and avoiding false positives.

Exploring the Frontiers of Cell Temperature Measurement and Thermogenesis.

The precise measurement of cell temperature and an in-depth understanding of thermogenic processes are critical in unraveling the complexities of cellular metabolism and its implications for health and disease. This review focuses on the mechanisms of local temperature generation within cells and the array of methods developed for accurate temperature assessment. The contact and noncontact techniques are introduced, including infrared thermography, fluorescence thermometry, and other innovative approaches to localized temperature measurement. The role of thermogenesis in cellular metabolism, highlighting the integral function of temperature regulation in cellular processes, environmental adaptation, and the implications of thermogenic dysregulation in diseases such as metabolic disorders and cancer are further discussed. The challenges and limitations in this field are critically analyzed while technological advancements and future directions are proposed to overcome these barriers. This review aims to provide a consolidated resource for current methodologies, stimulate discussion on the limitations and challenges, and inspire future innovations in the study of cellular thermodynamics.

Buildings as Batteries

Aggregators are increasingly using portfolios of various end-user resources such as local renewable generation, batteries, EVs, and demand-side management to participate in the electricity markets as virtual power plants. Whilst the smart control of energy within buildings is well established for cost optimization, the prospect of an aggregator collaborating with the energy managers of buildings to trade electricity in the wholesale markets is under researched. This paper uses a state-of-the-art architectural simulator to model the thermal inertia of a typical high-rise building in London and represent the thermodynamics of its hourly occupancy and weather responses. The building is simulated as a virtual battery by manipulating the HVAC settings. Price arbitrage on the electricity wholesale market and contracting with the local distribution network for flexible reserve services are both feasible and profitable. It is concluded that aggregators can apparently use buildings as additional assets within their trading portfolios. JEL Classification: L85 and L94.

Collaborative Optimization Framework for Coupled Power and Transportation Energy Systems Incorporating Integrated Demand Responses and Electric Vehicle Battery State-of-Charge

The growing adoption of electric vehicles (EVs) and advancements in dynamic wireless charging (DWC) technology have strengthened the interdependence between power distribution networks (PDNs) and electrified transportation networks (ETNs), leading to the emergence of coupled power and transportation energy systems (CPTESs). This development introduces new challenges, particularly as DWC technology shifts EV charging demand from residential plug-in charging to charging-while-driving during commuting hours, causing simultaneous congestion in both ETNs and PDNs during peak times. The present work addresses this issue by developing a collaborative optimization framework for CPTESs that incorporates integrated demand responses (IDRs) and EVs battery state-of-charge (SOC). In the ETN, a multiperiod traffic assignment model with time-shiftable traffic demands (MTA-TSTD) is established to optimize travelers’ routes and departure times while capturing traffic flow distribution. Meanwhile, effective path generation models with EVs battery SOC are proposed to optimize charging energy during driving and construct the effective path sets for MTA-TSTD. In the PDN, a multiperiod optimal power flow model with time-shiftable power demands (MOPF-TSPD) is formulated to schedule local generators and flexible power demands while calculating the power flow distribution. To enhance temporal and spatial coordination in CPTESs, a distributed coordinated operation model considering IDRs is proposed, aiming to optimize energy consumption, alleviate congestion, and ensure system safety. Finally, an adaptive effective path generation algorithm and an ETN–PDN interaction algorithm are devised to efficiently solve these models. Numerical results on two test systems validate the effectiveness of the proposed models and algorithms.

Implementation of ANFIS-based UPQC for Power Quality and Thermal Management Enhancement in the Distribution System

Conventional distribution systems generally operate with voltage and current waveforms being sinusoidal, though they slightly deviate from the ideal sinusoidal waveform, which is measured as distortion. The increase in power demand has led to the local generation and storage of power (Micro Grid systems). For its adoption, we need to implement smart grid architecture. Power electronics is a technologically sound way to limit different kinds of power quality (PQ) disturbances. It can also be used to control power flow, boost energy transmission capacity, enhance dynamic behavior and voltage stability, and ensure better power quality at distribution within established bounds. Unified Power Quality Conditioners (UPQC), one of the well-known Flexible AC Transmission System (FACTS) devices, are typically used to address problems in distribution systems such as voltage surges, flickers, neutral current reduction, and PQ. Additionally, thermal management is crucial for maintaining system stability and preventing overheating. While dealing with sensitive loads, a UPQC injects harmonics into the system, which can compromise system stability. This article describes an artificial neural network with harmonics elimination techniques for a modified UPQC connected with a Smart Grid. The performance of the proposed system is evaluated using MATLAB/Simulink software.

Radiative-conductive heat transfer dynamics in dissipative dispersive anisotropic media

Abstract We develop a self-consistent theoretical formalism to model the dynamics of heat transfer in dissipative, dispersive, anisotropic nanoscale media, such as metamaterials. We employ our envelope dyadic Green’s function method to solve Maxwell’s macroscopic equations for the propagation of fluctuating electromagnetic fields in these media. We assume that the photonic radiative heat transfer mechanism in these media is complemented by dynamic phononic mechanisms of heat storage and conduction, accounting for effects of local heat generation. By employing the Poynting theorem and the fluctuation-dissipation theorem, we derive novel closed-form expressions for the radiative heat flux and the coupling term of photonic and phononic subsystems, which contains the heating rate and the radiative heat power contributions. We apply our formalism to the paraxial heat transfer in uniaxial media and present relevant closed-form expressions. By considering a Gaussian transverse temperature profile, we also obtain and solve a system of integro-differential heat diffusion equations to model the paraxial heat transfer in uniaxial reciprocal media. By applying the developed analytical model to radiative-conductive heat tranfer in nanolayered media constructed by layers of silica and germanium, we compute the temperature profiles for the three first orders of expansion and the total temperature profile as well. The results of this research can be of interest in areas of science and technology related to thermophotovoltaics, energy harvesting, radiative cooling, and thermal management at micro- and nanoscale.

A study on the temperature rise characteristics of high-speed ball bearings under starvation lubrication

Purpose This paper aims to study the problem of starvation lubrication of high-speed ball bearings due to temperature rise during operation and to avoid thermal failure of bearing lubrication. Design/methodology/approach Under the quasi-statics model of grease lubrication, both the oil film dragging force and the rolling friction between the balls and raceways collectively counteract the gyroscopic torque. Initially, the static model for grease lubrication is solved, followed by calculating the generated heat using the local heat generation method and ultimately the multinodal thermal network model is solved, and the solved results of the quasi-statics are updated by the temperatures of the grease nodes based on the relationship of the grease temperature and viscosity, as well as the relationship of the viscosity and the film thickness. Findings By comparing the numerical calculation results of bearings under different working conditions, the influence of starvation lubrication on the oil film thickness, oil film drag force and rolling friction of bearings is discussed, and it is found that the numerical calculation results of the outer ring temperature of bearings under the starvation lubrication due to the consideration of temperature rise are closer to the experimental values. Originality/value This study reveals the dynamic characteristics of bearings under starvation lubrication, which is more practical and engineering guiding significance for the design of bearings, and introduces a new method and basis for the calculation of temperature rise of rolling bearings. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0208/

One-Pot Synthesis of Fe-Norepinephrine Nanoparticles for Synergetic Thermal-Enhanced Chemodynamic Therapy.

Chemodynamic therapy (CDT) is an innovative and burgeoning strategy that utilizes Fenton-Fenton-like chemistry and specific microenvironments to produce highly toxic hydroxyl radicals (•OH), with numerous methods emerging to refine this approach. Herein, we report a coordination compound, Fe-norepinephrine nanoparticles (Fe-NE NPs), via a one-pot synthesis. The Fe-NE NPs are based on ferrous ions (Fe2+) and norepinephrine, which are capable of efficient Fe2+/Fe3+ delivery. Once internalized by tumor cells, the released Fe2+/Fe3+ exerts the Fenton reaction to specifically produce toxic •OH. Moreover, the internal photothermal conversion ability of Fe-NE NPs allows us to simultaneously introduce light to trigger local heat generation and then largely improve the Fenton reaction efficiency, which enables a synergetic photothermal and chemodynamic therapy to realize satisfactory in vivo antitumor efficiency. This proof-of-concept work offers a promising approach to developing nanomaterials and refining strategies for enhanced CDT against tumors.

A Multi-Layer Techno-Economic-Environmental Energy Management Optimization in Cooperative Multi-Microgrids with Demand Response Program and Uncertainties Consideration.

This paper presents a multi-layer, multi-objective (MLMO) optimization model for techno-economic-environmental energy management in cooperative multi-Microgrids (MMGs) that incorporates a Demand Response Program (DRP). The proposed MLMO approach simultaneously optimizes operating costs, MMG operator benefits, environmental emissions, and MMG dependency. This paper proposed a new hybrid ε-lexicography-weighted-sum that eliminates the need to normalize or scalarize objectives. The first layer of the model schedules MMG resources with DRP to minimize operating costs (local generation and power transactions with the utility grid) and maximize MMG profit. The second layer achieves the environmental operation of the MMG, while the third layer maximizes MMG reliability. This paper also proposed a new application of a recently developed enhanced equilibrium optimizer (EEO) for solving the three-layer EM problem. In addition, the uncertainties of solar power generation, wind power generation, load demand, and energy prices are considered based on the probabilistic 2m + 1 Point estimation method (PEM) approach. Three case studies are presented to verify the proposed MLMO approach on an MMG test system. In Case I, a deterministic EM is solved to simulate the MMG as a single layer to minimize costs and maximize benefits through DRP, while Case II solves the MLMO optimization problem. Simulation results show that the proposed MLMO technique reduces environmental emissions by 2.45% and 3.5% in its optimization layer and at the final layer, respectively. The independence index is also enhanced by 2.49% and 4.8% in its layer only and as a total increase, respectively. Case III is for the probabilistic EM simulation; due to the uncertain variables effect, the mean value in this case is increased by about 2.6% over Case I.

Evolution Characteristics and Typical Pollution Episodes of PM2.5 and O3 Complex Pollution in Bozhou City from 2017 to 2022

In China, atmospheric pollution exhibits a complex pattern, with simultaneous exceedances of fine particulate matter （PM2.5） and ozone （O3） levels becoming evident. To understand the complex pollution characteristics and evolution patterns of PM2.5 and O3 in Bozhou City, various methods such as weather classification, analysis of typical pollution processes, and investigation of precursor sources were employed to explore the pollution and variations of PM2.5 and O3 in Bozhou City from 2017 to 2022 and subsequently analyze their causes and precursor sources. The results indicated that： ① PM2.5-O3 complex pollution in Bozhou City mostly occurred under high-pressure weather conditions, with daytime high temperatures and low humidity promoting the formation of O3 pollution, whereas nighttime high humidity and atmospheric oxidative conditions promoted the generation of secondary components such as nitrates and ammonium salts in PM2.5. ② During the pollution process, PM2.5 in Bozhou City mainly originated from biomass burning, secondary generation, traffic pollution, coal combustion, and dust sources. Volatile organic compounds （VOCs） primarily emerged from plant sources, traffic pollution, oil and gas evaporation, solvent use, fossil fuel combustion, residential emissions, and industrial emissions. Biomass burning and traffic pollution made significant contributions to the pollution process. ③ Analysis of air mass trajectories and regional pollution situations indicated that the overlay of northern and southern air masses, along with local generation, were the main causes of the PM2.5-O3 complex pollution in Bozhou from October 18th to 27th, 2022.

Modeling building energy self-sufficiency of using rooftop photovoltaics on an urban scale

The significant contribution of buildings to global energy-related CO2 emissions and climate change has led to projections of a carbon–neutral building stock by 2050. This study evaluates the potential contribution of rooftop photovoltaics to urban energy self-sufficiency by developing an enhanced CityBEM framework, our in-house urban building energy model (UBEM). This methodology enables city-scale, simultaneous simulations of building energy use and rooftop photovoltaic retrofitting with low computational time. CityBEM’s robustness and high spatiotemporal resolution facilitate transient simulations of individual buildings with diverse usage types across large urban areas, addressing common computational constraints and input data limitations in UBEM applications. The rooftop photovoltaic model in CityBEM utilizes a comprehensive approach with physics-based modeling of crystalline PVs, model validation, and a proper design of array networks to manage self-shading effects. More than 57,000 buildings with a combined footprint of 32.37 million square meters are located in the simulation test case covering downtown Montreal (Quebec, Canada) and the surrounding areas. Results indicate that rooftop PV adoption in these buildings could potentially generate 5.9 TWh of electricity annually, reduce energy demand by 27.3%, and achieve an average annual energy saving of 40%. This local generation could also reduce operational CO2 equivalent emissions by over 0.2 megatons. Overall, this study highlights the significant potential of rooftop photovoltaics for a cleaner, more energy self-sufficient urban future.

Evaluation of transition to 100% electric vehicles (EVs) by 2052 in the United States

With the rising need to transition from fossil fuel consumption to renewables, the transportation industry is foreseeing large-scale adoption of electric vehicles (EVs). According to various studies, the petroleum resources will last until or around 2052. Utilizing the US Federal Highway Administration (FHWA) published data on the number of registered vehicles by each state, the profile of vehicles by 2052 was forecasted using a time series. The vehicle profile comprised vehicles by each type classified as automobiles, buses, trucks, and motorcycles. This future profile became the basis of the quantification of total EVs by the end of 2052. Based on the available fuel economy data published by the US Department of Energy, the average energy consumption per mile (kWh/mile) of each vehicle type was factored into the energy demand calculation for 100% electrification by 2052. A roof-top solar photovoltaic system is easy to install on unoccupied roof space for US house owners. Obtaining the capacity of such a roof-top solar PV system acts as a good decision-making criterion for both house owners and developers. However, for city-dwellers living in multi-family residential buildings, the potential of utilization of roof-top solar PV becomes a subject of future work when effective sharing of resources for local power generation by renewables and development of community-shared EV charging infrastructure is concerned. How well EVs performed against internal combustion engine (ICE) vehicles in terms of fuel efficiency and reduced carbon emissions is a driving factor for this transition. For energy demand calculations, a base model was framed, and results were obtained by utilizing mathematical and statistical tools. After accounting for the effects of improved fuel efficiency or reduced energy consumption by EVs over time, the model was modified to obtain revised energy demand and, thus, effective energy generation required. Accordingly, the capacity of EV charging infrastructure required by each state determined the need for preparation by utility companies and local jurisdictions. With limitations on battery size and thus increased frequency for drivers to return for charging, additional fast chargers (level 3) at existing gasoline stations become an option that requires further assessment.

Experimental study on how the settings of plasma affect its effectiveness of suppression of thermoacoustic oscillations in a Rijke tube

Thermoacoustic instabilities, frequent in a wide range of combustors, arise from the intricate coupling between the flame’s unsteady heat release and the combustor acoustic. The application of plasma, characterized by its substantial local energy addition and radical generation, has demonstrated potential in disrupting this coupling and thereby mitigating thermoacoustic oscillations. Notably, open-loop control using discharge plasma has been successfully implemented to suppress self-excited oscillations in a Rijke tube setup. Considering the broader context of a complex system that integrates both thermoacoustic systems and discharge plasma, experiments were done to see its performance in stability under different arrangement and discharge repetition rates of discharge plasma. These experimental investigations identified critical operating conditions essential for complete suppression: (A) the optimal location of discharge actuations, and (B) the minimum energy required for complete suppression. Moreover, the impact of discharge plasma, particularly when tuned to the eigenfrequencies of oscillations within the thermoacoustic system, was thoroughly examined. The insights gained from these successful suppression trials are instrumental in guiding the strategic design of both physical arrangement and electrical configurations for the control of combustion instabilities via discharge plasma. Furthermore, through the photographing of the swinging arcs and their thermal disturbances by high-speed camera and high-speed schlieren, the characteristics of arcs’ thermal disturbances and the reasons affecting its suppression effectiveness were determined.