Load Changes Research Articles

Forecasting power system flexibility requirements: A hybrid deep-learning approach

The rapid growth of Variable and Renewable Energies (VRE) worldwide poses significant challenges to power systems, particularly in managing rapid changes in load and generation. A critical research gap exists in effectively forecasting Residual Load (RL) to enhance power system flexibility, as existing methods often struggle with the volatility and non-linearities introduced by VRE. This paper addresses this gap by proposing a novel hybrid forecasting framework that integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and a Convolutional Long Short-Term Memory (ConvLSTM-2D) Artificial Neural Network (ANN). This framework is designed to more accurately capture complex patterns in RL data, thereby improving forecast accuracy under high volatility conditions. We apply this methodology to forecast half-hourly RL for 2021 in the French region of Occitanie, achieving an average Mean Absolute Percentage Error (MAPE) of 4.29 %. Our results demonstrate that the proposed framework significantly outperforms existing models, offering consistent accuracy over time and proving highly suitable for practical daily use among energy stakeholders.

Robust adaptive sliding mode control of a bidirectional DC-DC converter feeding a resistive and CPL based on PSO

A DC-DC converter functioning in bidirectional (two-way) mode is a crucial component of direct current (DC) microgrids since it allows electricity to flow in both directions. However, because of load changes and other factors, the DC-bus voltage might become unstable. This research proposes a robust adaptive controller for a half-bridge two-way DC-DC converter founded on particle swarm optimization (PSO). Using a DC-DC half-bridge bidirectional converter, the effectiveness of various conventional and proposed control techniques is investigated. In comparison to a conventional sliding mode controller (CSMC), it is found that a PSO-based sliding mode control with an adaptive law is the optimal control approach for a bidirectional half-bridge DC-DC converter. This is because minimal steady-state error and the shortest rising and settling times are guaranteed. The benefits of robustness, chattering reduction, and simple design are combined in the suggested controller, which is especially beneficial when dealing with load and input voltage changes. The controller ensures robustness and stability in the face of parameter changes. Numerical simulations conducted in a MATLAB-Simulink environment on a DC-DC half-bridge converter operating in bidirectional mode show the controller's improved performance over its existing counterpart.

Load forecasting method based on CNN and extended LSTM

With the continuous development of power systems and the growing demand, accurate power load prediction has become essential to ensure stable system operation and optimize energy allocation. The collection and analysis of historical load data have become increasingly important, and the factors affecting load changes have grown more complex. To address this challenge, this paper proposes a short-term load prediction method based on convolutional neural networks (CNN) and multilayer extended long short-term memory (LSTM) neural networks. The method first extracts local features from historical data using 1D convolution operations in the CNN. Then, a multilayer extended LSTM network captures long-term dependencies in the data from multiple dimensions for more accurate load prediction. The prediction experiments use real load and related factor data from a city in eastern Mongolia. Results demonstrate that the proposed method outperforms other deep learning-based load prediction methods in direct single-step, four-step, and 32-step load predictions in terms of MAPE, RMSE, and MAE indexes. Additionally, the proposed model can be extended to more prediction application scenarios, including intelligent transportation and financial analysis.

Defining within-host SARS-CoV-2 RNA viral load kinetics during acute COVID-19 infection within different respiratory compartments and their respective associations with host infectiousness: a protocol for a systematic review and meta-analysis

IntroductionUnderstanding how RNA viral load changes (viral load kinetics) during acute infection in SARS-CoV-2 can help to identify when and which patients are most infectious. We seek to summarise existing...

Fault-tolerant hierarchical energy management system for an electrical power system on more-electric aircraft

The concept of More-Electric Aircraft (MEA) has the potential to improve the environmental, economic, and reliability performance in the energy and transportation sectors. To achieve this potential, it has become a tendency to develop complex architectures of Electrical Power Systems (EPSs) for MEA to supply increasing electrical power demands. Moreover, a reliable and intelligent Energy Management System (EMS) is critical to coordinate the various EPS subsystems to ensure safe and efficient flight, following the real-time EPS operating requirements and safety criteria, while reducing the operating costs for all flight stages. This paper presents a fault-tolerant hierarchical EMS, for an innovative multi-converter-based aircraft EPS, to configure the system, ensure power distribution, and manage energy storage in multiple faulty scenarios over different time scales. There are two levels in this EMS: The High Level (HL) is based on Model Predictive Control (MPC), formulated by Mixed-Integer-Linear-Programming (MILP), to optimise the long-term EPS performance while considering future predictions; The Low Level (LL) adopts deterministic rules to cope with load changes and fault occurrences over the short term, during the HL sample intervals, with a faster clock. In particular, the LL controller contains four modes: to either cooperate with the HL online MPC or to operate independently, in either EPS normal or faulty conditions. The proposed EMS is evaluated in two cases, firstly considering load deviations in a normal operating scenario, and then considering behaviour in fault scenarios. The results indicate that the proposed EMS successfully reduces the EPS operational costs while ensuring quick responses to dynamic changes with either EPS component faults or EMS internal faults.

Outdoor mesoscale fabricated ecosystems: Rationale, design, and application to evapotranspiration

The disparity in scale, complexity, and control level between laboratory experiments and field observational studies has shaped both the methodologies employed and the nature of the research questions pursued in ecology and hydrology. While lysimeters and fabricated ecosystems suitably fit in this gap, their use as mesoscale experimental facilities has not been fully explored because of the limited manipulating capabilities and integration with imaging and monitoring methods, particularly for soil functioning. The proposed fabricated ecosystem (4.7 L × 1.2 W × 1.2 H m) focuses on the spatiotemporal integration of point sensors and imaging methods along the soil-plant-atmosphere continuum. Because energy and water fluxes are key environmental drivers, the designed setup was first applied to a multi-approach evapotranspiration investigation. Below the ground, electrical resistivity tomography (ERT) was combined with soil water sensors and a distributed temperature profiling system. Together, they provided the 3D monitoring of water and temperature changes, and thus an estimation of the evapotranspiration, as well as the interpretation of its below-ground controlling processes. Above-ground sensors supported a classical energy balance investigation that was compared with the lysimeter load changes and the ERT-based ET estimation. Our results provide first experimental evidence of water and temperature spatiotemporal variability at the lysimeter scale, and thus explain the discrepancies among the three estimated evapotranspiration time series and their seasonality. Beyond evapotranspiration, the multi-approach investigation of water and energy fluxes emphasizes how mesoscale setups can further support the development and upscaling of methods and models, as well as their integration and application under expected climate disturbances.

Real-Time Short-Circuit Current Calculation in Electrical Distribution Systems Considering the Uncertainty of Renewable Resources and Electricity Loads

Existing short-circuit calculation methods for distribution networks with renewable energy sources ignore the fluctuation of renewable sources and cannot reflect the impact of renewable sources and load changes on short-circuit current in real time at all times of the day and in extreme scenarios. A real-time short-circuit current calculation method is proposed to take into account the stochastic nature of distributed generators (DGs) and electricity loads. Firstly, the continuous power flow of distribution networks is calculated based on the real-time renewable energy output and electricity loads. And then, equivalent DG models with low-voltage ride through (LVRT) strategies are substituted into the iterative calculation method to obtain the short-circuit currents of all main branches in real time. The effects of different renewable energy output curves on distribution network short-circuit currents are quantitatively analyzed during the fluctuation in distributed power output, which can provide an important basis for the setting calculation of distribution network relay protection and the study of new principles of protection.

A Comprehensive Approach to Load Frequency Control in Hybrid Power Systems Incorporating Renewable and Conventional Sources with Electric Vehicles and Superconducting Magnetic Energy Storage

This study addresses the load frequency control (LFC) within a multiarea power system characterized by diverse generation sources across three distinct power system areas. area 1 comprises thermal, geothermal, and electric vehicle (EV) generation with superconducting magnetic energy storage (SMES) support; area 2 encompasses thermal and EV generation; and area 3 includes hydro, gas, and EV generation. The objective is to minimize the area control error (ACE) under various scenarios, including parameter variations and random load changes, using different control strategies: proportional-integral-derivative (PID), two-degree-of-freedom PID (PID-2DF), fractional-order PID (FOPID), fractional-order integral (FOPID-FOI), and fractional-order integral and derivative (FOPID-FOID) controllers. The result analysis under various conditions (normal, random, and parameter variations) evidences the superior performance of the FOPID-FOID control scheme over the others in terms of time-domain specifications like oscillations and settling time. The FOPID-FOID control scheme provides advantages like adaptability/flexibility to system parameter changes and better response time for the current power system. This research is novel because it shows that the FOPID-FOID is an excellent control scheme that can integrate these diverse/renewable sources with modern systems.

A Novel Approach for Monitoring Training Load and Wellness in Women's College Gymnastics.

Monitoring training load has the potential to improve sport performance and reduce injuries in athletes. This study examined training load and its association with wellness in artistic gymnastics. Training load and changes in training load (acute:chronic workload ratio [ACWR]) vary throughout 1 season; wellness is inversely correlated with training load and ACWR. Prospective case series. Level 3. A total of 30 female collegiate gymnasts from 4 Division I National Collegiate Athletic Association teams participated (mean age, 20 ± 2 years). During 4 months, before daily training, wellness surveys assessed sleep, energy, soreness, and mood (1-10; higher = better). After daily training, training load surveys assessed training duration per event (warm-up, vault, bars, beam, floor, strength and conditioning) and session rating of perceived exertion (RPE; 1-10; 10 = hardest) per event. Coaches reported technical complexity of training per event (1-4; 4 = hardest). Training load was calculated as [duration] × [RPE] × [technical complexity]. ACWR represented a ratio between acute [1-week] and chronic [4-week rolling average] training loads. ACWR and weekly training load fluctuated throughout the season (ACWR mean weekly range: 0.68-1.11; training load mean weekly range: 2073-6193 arbitrary units). ACWR and weekly training loads were trichotomized into low, medium, and high groups; positive correlations were observed between each wellness variable and ACWR (P < 0.01) and between each wellness variable and weekly training load (P < 0.01). Our novel training load monitoring framework for women's college gymnastics enabled us to characterize training load and its relationship with wellness throughout 1 season. This method should be explored in gymnasts across various ages and competitive levels. This study proposes a framework and the initial findings of monitoring training load and wellness in collegiate women's gymnastics.

“Acute responses to barefoot running are related to changes in kinematics, mechanical load, and inflammatory profile”

This study investigated the acute effects of barefoot (BF) running on biomechanical parameters and cytokine concentrations. Seventy-one habitually shod runners had biomechanical parameters evaluated during running shod (SH) and BF, while a sub-group of 19 runners had their inflammatory profile analyzed before and after a running session, using their habitual shoes or barefoot. Running BF changed spatiotemporal and joint kinematics, including the stride frequency (increased) and length (decreased), and foot strike pattern (more plantarflexed ankle at initial contact). An increased impact force was observed (p < 0.05), while joint moment, power, and work were also affected by BF running: a shift of joint load from the knee and hip to the ankle occurred (p < 0.05). In cytokine levels, maintenance (all cytokines, except Eotaxin, IL-12p40, IL-2, IL5, and MIP-1 beta) or reductions (IL-12p40, IL-2, and IL5) were observed as an acute response to BF running, what means to keep or reduce the levels of pro-inflammatory cytokines and immunological/chemoattraction proteins when compared to SH. Summarily, a single session of BF running may not represent enough stress to induce changes in the inflammatory profile. Besides the increased impact force, the joint load was reduced during short-term BF running. Nevertheless, short-term BF running should be cautiously applied due to the shift of joint load from the knee and hip to the ankle.

Piled-supported embankment responses to tunnelling in soft ground: An investigation of settlement and load transfer mechanisms

The escalation in infrastructure such as highways and high-speed railways has necessitated construction on soft and compressible ground, prompting the adoption of innovative solutions like piled-supported embankments. With the surge in tunnelling for transportations projects, the necessity of constructing tunnels in close proximity to piled embankments has become apparent. This study examines into settlement and load transfer mechanisms in piled-embankments affected by tunnel excavation at varying depths relative to pile lengths, employing a hypoplastic model to capture the nonlinear behaviour of soft soil. The findings indicate that the deepest tunnel caused the largest settlement, while the shallowest tunnel in led to the smallest settlement in the embankment due to pile settlements playing a significant role. The pile-soil stress ratio near the tunnel increased significantly when excavated close to pile shaft, contrasting substantially with decreased ratio in the tunnelling beneath the piled-embankment case. The bending moments in the piles exhibited differing behaviours in each case, with distinct trends observed in lateral movement and stress-induced responses. The axial load changes were influenced by factors such as negative skin friction, positive shaft resistance, and embankment weight transfer through arching, leading to unique load patterns along the pile length caused by the shallowest tunnel.

Simulation and experimental study of local high frequency resistance distribution in proton exchange membrane fuel cells under steady and dynamic conditions

Proton-exchange membrane (PEM) dry–wet variation during PEM fuel cell (PEMFC) operation markedly affects PEMFC lifespan. Therefore, deeper insights into the mechanical degradation mechanism of PEM require analysis of the membrane dry–wet change process. The stress changes caused by PEM dry–wet variations may induce mechanical failure. In practice, although high-frequency resistance (HFR) is often used to indirectly characterize PEM dry–wet degrees, numerical simulation can effectively analyze the mass transfer inside a PEMFC for parameters that are difficult to measure directly experimentally (such as membrane water content). Additionally, three-dimensional (3D) model validation requires more comprehensive experimental methods. In this study, we validate the simulated resistance distribution results through local electrochemical impedance spectroscopy. We also discuss the mass- and heat-transfer distribution characteristics under different current densities and analyze the influence of these characteristics on local HFR distribution variations. The calculated HFR distribution results show a certain degree of agreement with the experimental results. Due to the membrane self-humidification effect, the position of the minimum HFR value shifts upstream of the cathode at a high current density. The observed change in membrane stress results from variations in membrane water and temperature distributions with changes in current density. Steady-state HFR distribution analysis to uncover the membrane dry–wet variations caused by load changes—which would affect the HFR distribution changes—reveal that the HFR at the air outlet and the membrane dry–wet variations are more pronounced than at other locations due to the influence of reaction rate and gas velocity. Overall, this study demonstrates that 3D simulations can reliably predict the local HFR distribution of PEMFCs, enabling membrane stress variation analysis and providing guidance for fuel cell design and operation.

Abrupt changing aerodynamic loads resulting in diminished ride comfort when two high-speed trains intersect in a tunnel

The lateral force exerted when two trains pass each other can adversely affect train safety, and this adverse effect becomes more pronounced as the train speed increases. When trains cross paths in tunnels, the aerodynamics differ from those in open lines due to the restrictive nature of tunnel walls. Utilizing the Renormalization Group (RNG) k-ε turbulence model and the “Mosaic” grid method, this research examines changes in aerodynamic load of the train and ride comfort during a intersection at 400 km/h in a tunnel and contrasts this with conditions at 350 km/h. The results indicate that the change in aerodynamic load on each carriage is more pronounced when the head train of the oncoming train passes than when its tail train passes, with the largest variation observed during the passing of both the head and tail trains. This alteration in aerodynamic load is primarily attributed to the air being pushed in the locomotive area and the negative pressure from the vortex structure between trains. When the speed is increased from 350 km/h to 400 km/h, the aerodynamic load on the train increases by approximately 20 % to 40 %, and the acceleration of the head train grows by 20 % to 50 %. The most noticeable decrease in ride comfort is observed in the head train, with the highest increase in the head train’s Overall Vibration Total Value (OVTV), which rises by 30.1 %.

Design of Coil-Wound Once-Through Steam Generator System for Concentrating Solar Power Plants

The viability of solar tower plants is endangered owing to multiple failures, mainly in their steam generators. These failures produce unscheduled shutdowns with significant economic losses that increase the financing costs of this technology due to its technological risk. On the other hand, if the flexibility of the steam generator rises, solar power tower plants could participate in the energy adjustment market, improving their returns, encouraging the penetration of variable renewable energies, and providing security to the power grid. A novel steam generator system design based on a once-through steam generator composed of two coil-wound heat exchangers is proposed for a highly reliable, flexible, and quick response steam generator. Coil-wound heat exchangers reduce thermal stress and allow part load operation, while once-through steam generators permit fast load changes and reduce the number of components. Compared with traditional shell and tube designs, the results indicate that the proposed steam generator reduces heat exchange area by 22%, molten salt pressure drop by 79%, and tube-to-tubesheet joints by 73%.

Optimization of low-velocity impact behavior of FML structures at different environmental temperatures using taguchi method and grey relational analysis

Carbon fiber-reinforced Aluminum Laminate (CARALL) is a new generation of Fibre Metal Laminate (FML) material. This study investigates the low-velocity impact behavior of CARALL structures at different environmental temperatures (−40°C, 23°C, and 80°C). Two different groups of CARALL composite structures with varying fiber orientations were produced by hot pressing in a 3/2 arrangement: C1 (Al/0°90°/Al/90°0°/Al) and C2 (Al/0°0°/Al/0°0°/Al). Low-velocity impact tests were conducted at 23 J, 33 J, and 48 J energy levels using a Ø20 mm spherical impactor tip. The area of damage was detected by ultrasonic C-Scan. In addition, analysis of variance (ANOVA) was applied to reveal the influential parameters and their effect levels. After conducting experiments using the Taguchi L18 test set, it was observed that the C2-coded specimen yielded better results in terms of maximum peak load, maximum displacement, and damage area. While the decrease in temperature increased the damage and maximum peak load, the increase in temperature did not cause a significant change in the maximum peak load. The primary damage mechanisms observed in damage investigations were matrix cracks and delamination between composite layers. Although delamination is present between the Al/CFRP layer, it is not significant. According to ANOVA results, impact energy was the most effective parameter for maximum impact force, maximum displacement, and damage area, with contribution rates of 81%, 74%, and 76%, respectively. The optimal experimental conditions (23°C temperature and 23 J impact energy with the C1-coded sample) were determined using grey relational analysis based on principal component analysis.

Control Conditions for Equal Power Sharing in Multi-Area Power Systems for Resilience Against False Data Injection Attacks

Power cyber–physical systems such as multi-area power systems (MAPSs) have gained considerable attention due to their integration of power electronics with wireless communications technologies. Incorporating a communication setup enhances the sustainability, reliability, and efficiency of these systems. Amidst these exceptional benefits, such systems’ distributed nature invites various cyber-attacks. This work focuses on the equal power sharing of MAPSs in the event of false data injection (FDI) attacks. The proposed work uses a sliding mode control (SMC) mechanism to ensure timely detection of challenges such as FDI attacks and load change, making MAPSs reliable and secure. First, a SMC-based strategy is deployed to enable the detection and isolation of compromised participants in MAPS operations to achieve equal power sharing. Second, time-varying FDI attacks on MAPSs are formulated and demonstrate their impact on equal power sharing. Third, a robust adaptive sliding mode observer is used to accurately assess the state of the MAPS to handle state errors robustly and automatically adjust parameters for identifying FDI attacks and load changes. Lastly, simulation results are presented to explain the useful ability of the suggested method.

Evaluation of the performance of different internal insulation systems in real-life conditions ‐ A case study

Thermal retrofitting of historic buildings is essential to reducing heat loss in all buildings. Although exterior insulation often is hygrothermally a better solution, internal insulation is the only option in facades worthy of preservation (e.g., solid masonry external walls). However, mold growth has frequently been discovered in buildings with internal insulation at the interface between the insulation and the original wall, while simulations and lab tests show minimum risk, and vice versa. Therefore, real-life testing is required so that the building owners are more likely to accept these measures.This paper presents a case study of an 1837-built typical historic building. The study focuses on the building's top floor, a residential area (commune). Eight different rooms have four different types of internal insulation installed. The performance of the insulation systems was determined by monitoring the interior and exterior climate and the temperature and relative humidity at the intersection of the insulation and the existing wall for 20 months. The risk of mold growth was estimated based on the measurements. In the wall interfaces, the Mold Index indicated that the risk for mold growth is not severe. Hygrothermal simulations for the measured period and ten years were also performed. To increase simulation accuracy, the original exterior masonry bricks underwent laboratory testing to determine their precise material properties. The main outcome from the simulations was that the three vapor-open systems were more susceptible to indoor moisture load changes and had an elevated risk of mold growth, whereas the vapor-tight system was more robust to variation in insulation thickness and internal moisture level changes, and in this case, demonstrated the best performance in respect to moisture safety.

Numerical Investigations of a Single Loop Pulsating Heat Pipe for Cryogenic Applications

Abstract The thermohydraulics of a single-loop pulsating heat pipe (PHP) for cryogenic applications have been simulated. The 120 mm long PHP tube is made of a 1.5 mm diameter inner tube of thickness 0.83 mm. The computation fluid dynamics (CFD) analysis performed with the ansysfluent software is a 2D numerical study using pure nitrogen as the working fluid in binary phases. The boundary condition on the evaporator is of constant heat flux, while the same on the condenser is of constant temperature. The phase behavior of the liquid and vapor and their interactions are accounted for through the volume of fluid (VOF) method and the Lee model. The numerical model is validated using the existing experimental data, with an agreement of less than 8% between them. The thermo-hydraulic variations of temperature, pressure, and velocity have been simulated for different heat loads and fractional liquid contents (fill ratios). The temperature and pressure oscillations set in the PHP-fluid increase with the heat added to the evaporator while the fluid velocity remains independent. The heat load and the fill ratio dictate the effective thermal conductivity—attaining nearly 3400 W/mK for a fill ratio of 70% in the chosen PHP geometry. An alteration has been made in the Jacob number to predict the dominance of sensible heat over latent heat in a PHP, postulated by other researchers. The constant fill ratio assumption is not truly valid as it indicates a small yet finite variation with the change in the heat load.

Seismic Azimuthal Anisotropy Within the Juan de Fuca ‐ Gorda Plate System

AbstractWe estimate seismic azimuthal anisotropy for the Juan de Fuca ‐ Gorda plates from inversion of a new 10–80 s period Rayleigh wave dataset, resulting in a two‐layer model to 80 km depth. In the lithosphere, most anisotropy patterns reflect the kinematics of plate formation, as approximated from seafloor‐age‐based paleo‐spreading, except for regions close to propagator wakes and near plate boundaries. In the asthenosphere, the fast propagation orientations align with convective shear as inferred from the NUVEL1A plate motion model, which is indicative of a ∼3 Myr average, rather than with the more recent, ∼0.8 Myr, motions inferred from MORVEL. Regional anisotropy of this young plate system thus records convection like older plates such as the Pacific. On smaller scales, anisotropy imaging provides insights into dynamics of plate generation and can further elucidate plate reorganizations and changes in boundary loading.

Time Series Analysis in Electrical Load Forecasting

Time series analysis in electricity load projection is a key part of the energy sector because it makes it possible to control and distribute energy more efficiently. It is important to have accurate load forecasts in order to balance supply and demand, make power systems run more efficiently, and lower operating costs. This essay covers a wide range of ways that time series analysis can be used to guess how much electricity will be used. The study looks at a number of different models, such as the autoregressive integrated moving average (ARIMA), exponential smoothing, and machine learning methods like Long Short-Term Memory (LSTM) networks. These models are judged by how well they can show the patterns and time relationships that are common in electricity load data. A lot of attention is paid to the problems that come up because of non-stationarity, timing, and outside factors like weather that cause load changes. The study talks about how feature selection, data pre-processing, and model evaluation can help make forecasts more accurate. The study shows the trade-offs between model interpretability and forecasting power by comparing how well standard statistical methods and new machine learning techniques work. The study also talks about how mixed models, which take the best parts of more than one method and combine them, might help make forecasts more accurate. The results make it clear how important time series analysis is for building accurate load predicting models, which are needed to keep modern power systems reliable and efficient.