Load Model Research Articles

The improvement of wavelet-based multilinear regression for suspended sediment load modeling by considering the physiographic characteristics of the watershed.

The aim of this study is to model a relationship between the amount of the suspended sediment load by considering the physiographic characteristics of the Lake Urmia watershed. For this purpose, the information from different stations was used to develop the sediment estimation models. Ten physiographic characteristics were used as input parameters in the simulation process. The M5 model tree was used to select the most important features. The results showed that the four factors of annual discharge, average annual rainfall, form factor and the average elevation of the watershed were the most important parameters, and the multilinear regression models were created based on these factors. Furthermore, it was concluded that the annual discharge was the most influential parameter. Then, the stations were divided into two homogeneous classes based on the selected features. To improve the efficiency of the M5 model, the non-stationary rainfall and runoff signals were decomposed into sub-signals by the wavelet transform (WT). By this technique, the available trends of the main raw signals were eliminated. Finally, the models were developed by multilinear regressions. The model using all four factors had the best performance (DC = 0.93, RMSE = 0.03, ME = 0.05 and RE = 0.15).

PEMBEBANAN MODEL PELAT SKALA KECIL PERKERASAN KAKU (RIGID PAVEMENT) DI ATAS TANAH PASIR

Road infrastructure issues need great attention, considering that this was a link and a cross-economy between one region and another. Damage to the pavement (pavement) would have fatal consequences for the development of an area and an increase in financial needs. Therefore, it was necessary to strengthen a solid road body so that it was able to strengthen the road and be comfortable for traffic loads to pass. Damage to the road body was a major concern in road maintenance efforts. This was due to several very complex problems in terms of the materials used, work implementation, traffic loads passing through the road body, and existing natural conditions. This research studies and analyses the behavior of dynamic-loaded rigid pavements. This load was a traffic load model, and the behavior was reviewed in a small-scale laboratory model. The expected result was to know the model’s behavior with and without rigid pavement reinforcement on both sandy and soft soils, namely in the form of analysis and the ability of the reinforcement to accept traffic loads. This research showed that the plate test model shows that multiple plate thickness supports plate stiffness. The cakar reinforcement plate affected the stiffness of the plate. The deflection value due to loading on the 3-layer plates (6.3 mm thick) was comparable to the 1-layer plate (2.1 mm) with cakar. FEM analysis can be performed to predict deflection due to loading in the center of the plate, and this value was very close to the results of the laboratory small-scale loading test. The CBR value used to calculate the deflection was closest to the real condition, namely the value before loading 0.2 kN and after loading 0.8 kN.

Short- and long-term forecasting for building energy consumption considering IPMVP recommendations, WEO and COP27 scenarios

Understanding and predicting power consumption behavior helps estimate costs, seek actions to save energy and plan affirmative actions that raise people's awareness. Organized civil society has made efforts in this context. Our contribution is a framework that first extracts knowledge about consumption through an extensive time series analysis of the building under study. Proper acquisition of meteorological (e. g. dry bulb temperature, humidity, solar radiation, and precipitation) and power consumption data are discussed. The correlation between these time series is verified, which develops knowledge about the problem. We believe forecasts will be more reliable using accurate models with more knowledge. Afterward, we forecast for the short-term period (hour, day and month-ahead) and long-term period (2030 and 2050), considering the scenarios proposed by the World Energy Outlook (WEO-2022) and Convention on Climate Change (COP27). Acquisition, processing, data analysis, as well as predictions, each framework step follows the International Performance Measurement and Verification Protocol (IPMVP-2022) recommendations. Building energy consumption forecasts considering IPMVP, WEO, and COP27 scenarios are originals in the literature. IEEE rigor for load measurement and modeling is achieved. Our study also follows the ISO:50000 energy efficiency purposes. The analysis and forecasting use data from a public building with an approximate circulation of 5,000 people per day. The objective is to contribute to a better understanding of building engineering to structure energy management actions. As stated at COP27: enough greenwashing talk, let us move on to smart actions.

Numerical Modelling of Loads on the Structural Elements of an Innovative Mechanism Enabling Wheelchairs to Negotiate Stairs

Numerical Modelling of Loads on the Structural Elements of an Innovative Mechanism Enabling Wheelchairs to Negotiate Stairs

Traffic load simulation on bridges based on improved non-contact machine vision technique and multi-source information fusion

This study presented a novel traffic load simulation method. Specifically, an improved You Only Look Once (YOLO) detector based on the k-means++ clustering algorithm is implemented to identify vehicle types, and the multi-objective tracking algorithm is used to obtain the spatial location and velocity information of vehicles. Based on the results of detection and tracking, multi-source information fusion techniques are applied to build a vehicle database. Meanwhile, a Monte Carlo-Intelligent Driving Model can be developed for traffic load simulation based on the vehicle database. The applicability and effectiveness of the method are verified by the suspension bridge field test. The results show that the identification accuracy of vehicle type and vehicle number is about 88.28% and 74.09%, respectively. Meanwhile, the vehicle speed error is less than 6.5%. The method can be used to provide a reasonable traffic load model for large-span bridges without the aid of a deck-embedded weigh-in-motion system.

Modeling and Analysis of a Reconfigurable Rover for Improved Traversing over Soft Sloped Terrains.

Adjusting the roll angle of a rover's body is a commonly used strategy to improve its traversability over sloped terrains. However, its range of adjustment is often limited, due to constraints imposed by the rover design and geometry factors such as suspension, chassis, size, and suspension travel. In order to improve the rover's traversability under these constraints, this paper proposes a reconfigurable rover design with a two-level (sliding and rolling) mechanism to adjust the body's roll angle. Specifically, the rolling mechanism is a bionic structure, akin to the human ankle joint which can change the contact pose between the wheel and the terrain. This novel adjustment mechanism can modulate the wheel-terrain contact pose, center-of-mass projection over the supporting polygon, wheel load, and the rover driving mode. Combining the wheel-load model and terramechanics-based wheel-terrain interaction model, we develop an integrated model to describe the system dynamics, especially the relationship between rover pose and wheel slippage parameters. Using this model, we develop an associated attitude control strategy to calculate the desired rover pose using particle swarm algorithm while considering the slip rate and angle constraints. We then adjust the sliding and rolling servo angles accordingly for slope traversing operations. To evaluate the proposed design and control strategies, we conduct extensive simulation and experimental studies. The results indicate that our proposed rover design and associated control strategy can double the maximum slope angles that the rover can negotiate, resulting in significantly improved traversability over soft sloped terrains.

Off-line measuring sampling data identification parameters for digital twins mirroring load modelling and stability analysis

Currently, the methods used to represent loads do not differ between the characteristics that compose them or the nature of these. Therefore, the purpose of this research is to develop digital twins mirroring load models that can be used for more precise studies on power-flows and stability within the National Transmission Grid (NTG). Off-line sampling data of different electric measurements have been used in six substations of the Guayaquil (Ecuador) area. These values were organized by statistical methods and by time periods, to determine the parameters that make up the static load model. Dynamic models are also constructed for the same six substations using the analysis of current and voltage signals obtained from the substations. All data is organized to show a digital twin mirroring visual representation of the disturbances that may occur in the substation buses. A more accurate description of the static and dynamic responses can be obtained by replacing the general model that is currently used by engineers and planners with off-line sampling data. Digital twins help the electric utility businesses gather, visualise, and contextualise data from different sources, and enable to act on data, and to understand what-if modelling stability scenarios.

Probabilistic Transition-Based Optimal Energy Transaction of a Non-Convex CHP-Microgrid during Generation and Load Uncertainty

Combined heat power dispatch with improved operation remains a popular preference in microgrid having uncertain and non-convex nature of the system. This research work deploys an efficient energy management system driven by a novel stochastic transitions tuned unscented Gaussian distribution (ST-UnGD) for optimal energy transaction. The proposed scheme has been introduced with uncertainty modeling of available generations and load using probabilistic transition-based timed petri net. Echo algorithm has been used to influence prioritized transition for appropriate number of token distribution. The control over the process during transition has been supervised with UnGD. A uniform probability density function has been created using Gaussian distribution to characterize random variables for effective time series scenario generation. The mean and variance which helps in sorting ten competent scenarios from one thousand scenarios, has been computed with the proposed strategy and compared with other methods. The improvement has been noticed with standard deviation of 0.0162% after 40 trials run with average operational cost of 254.211€ when token distribution was updated by 100, 200, 300, 400, and 500 firings. A statistical analysis by parametric and non-parametric test confirmed the effectiveness of the proposed algorithm showing appropriate confidence level in the mentioned case study.

Load Modelling for a Federal Medical Center in Nigeria under Erratic Power Supply

Load data of a Federal Medical Center (FMC) in Nigeria, under prevailing erratic power supply from Nigeria’s electric power distribution company (DisCo) feeders, were considered to develop model load curve and electricity use values for planning effective electricity use and management. The analytical methods applied include nominal load evaluation for the entire FMC, data acquisition by direct hourly load monitoring for 12 months, diesel fuel consumption observation for power supply during DisCo outages, energy metering, outage events and durations, descriptive statistical evaluations of data. The results obtained and analysed include the following: nominal load, daily load and electricity use models. The results established daily load curve and parameters, such as load factor, daily average power and expected electrical energy consumption model in a typical Nigerian FMC. Model load factor is 0.545, which would be uneconomical especially when using standby generators the whole day due to failure of Disco feeder.

Neural Networks Based Dynamic Load Modeling for Power System Reliability Assessment

The reliability of a power system is considered as a critical requirement in planning and operating the system due to the increasing demand for more reliable service with a lower frequency and duration of interruption. Hence, reliability is also considered as a major challenge in the development of future power systems as they become more advanced and complex, making the accuracy of the reliability assessment dependent on several factors such as supply and load modeling. Recent studies on power systems’ reliability and stability have focused on load modeling, where loads are either assumed to be static or dynamic, by introducing significant constraints. However, the emergence of new types of loads necessitates the development of models that can incorporate them with accuracy, as this would facilitate their effective use in flow and stability simulation studies, as well as reliability analyses. In this study, dynamic loads are modeled using a feed-forward neural network where a simulation test bed is developed in MATLAB/Simulink to generate operating data used during training and validating of the neural network model. Subsequently, Electrical Transient Analyzer Program (ETAP) software is used to verify the effect of load modeling on power system reliability assessment platform. Bus 2 of Roy Billinton Test System (RBTS) is employed as a case study to investigate the sensitivity of the reliability indices, such as System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI), on the load modeling technique with mixed loads (dynamics and statics).

Semi-analytical load models describing the progressive immersion of a fixed vertical cylinder in a breaking wave

This paper is part of the DIMPACT (Design of floating wind turbines and impacts of energetic steep and breaking waves) project concerning slamming loads on floating offshore wind turbines. Two semi-analytical models accounting for the progressive immersion of a vertical cylinder in a breaking wave are presented. These models are based on the rate of change of the fluid momentum and the continuity of the added mass during immersion. The first model is based on the Generalized von Kármán Model where the real shape of the body and its added mass are accounted for. To account for the nonlinearity of the flow kinematics, the second-order terms of the momentum equation are considered in the inertia load. The total load is obtained by adding the drag force using a variable drag coefficient. To better predict the slamming load, a second model based on Wagner’s theory is presented. The Modified Logvinovich Model provides the pressure distribution at the first instants of impact. It is assumed that the flow does not separate from the structure. The load models are applied in a strip-theory approach under the Froude–Krylov assumption. For comparison, a Navier–Stokes solver is used to generate four phase-focused breaking waves. The resulting free surface shape and the ambient kinematics of the two-dimensional waves are used in the semi-analytical models. The present models are compared with existing slamming load formulations and a three-dimensional numerical simulation with an actual cylinder, where the load on four sections of the cylinder are considered. The force in the deeply immersed sections is in good agreement in all models considered. In the partially submerged section, the proposed load formulations and the three-dimensional simulation predict a similar load. Other standard engineering formulas predict a much lower force in this section. In the area impacted by the crest, the Froude–Krylov-based approaches predict a much higher force than that given by the Navier–Stokes result, likely due to the free surface being disturbed by the cylinder.

Study on Typical Aerodynamic Faults of Variable Pitch Wind Turbine

The variable-speed variable-pitch wind turbine is an important part of China's power and energy systems, and is also the main conversion form of wind energy utilization. Aiming at the problem that the traditional blade element-momentum theory cannot achieve the modeling and simulation of wind turbine plane wind unbalance caused by wind shear and tower shadow effect, the modeling and simulation numerical calculation method of aerodynamic load of wind turbine actuation disk with different blade wind unbalance pitch angles is proposed, This method can derive the analytical expressions for solving the key variables of load calculation, axial induction factor and tangential induction factor, and realize the aerodynamic load solution. At the same time, it is also verified that the characteristic vibration component of 3 times the low speed shaft rotation frequency (3P) is a typical dynamic load feature of tower shadow effect, and is also the most important aerodynamic load fluctuation feature of variable-speed variable-pitch wind turbine, However, under normal conditions, the wind shear effect has little effect on the wind turbine load fluctuation.

Analysis of Pre- and during COVID-19 Mixed Load Models on Unbalanced Radial Distribution System Using a New Metaphor-Less Rao Optimization

An unbalanced electrical distribution system (DS) with radial construction and passive nature suffers from significant power loss. The unstable load demand and poor voltage profile resulted from insufficient reactive power in the DS. This research implements a unique Rao algorithm without metaphors for the optimal allocation of multiple distributed generation (DG) and distribution static compensators (DSTATCOM). For the appropriate sizing and placement of the device, the active power loss, reactive power loss, minimum value of voltage, and voltage stability index are evaluated as a multiobjective optimization to assess the device’s impact on the 25-bus unbalanced radial distribution system. Various load models, including residential, commercial, industrial, battery charging, and other dispersed loads, were integrated to develop a mixed load model for examining electrical distribution systems. The impact of unpredictable loading conditions resulting from the COVID-19 pandemic lockdown on DS is examined. The investigation studied the role of DG and DSTATCOM (DGDST) penetration in the electrical distribution system for variations in different load types and demand oscillations under the critical emergency conditions of COVID-19. The simulation results produced for the mixed load model during the COVID-19 scenario demonstrate the proposed method’s efficacy with distinct cases of DG and DSTATCOM allocation by lowering power loss with an enhanced voltage profile to create a robust and flexible distribution network.

New fatigue load models for assessing railway bridges in Europe

Train axle load measurements performed between 2012 and 2019 at 87 locations in the Dutch railway network are used to evaluate fatigue of railway bridges. The theoretical fatigue damage using realistic influence lines is determined for the measured loads and for the load model from Eurocode EN 1991-2 Annex D. It appears that this load model is (very) conservative for most cases, but unconservative for a few cases. Large differences in fatigue relevant loads are observed between different tracks. Two alternative load models that more closely represent the measured railway traffic in terms of trains and fatigue damage are presented, together with a third model based on historical train types. These models use track-specific traffic characteristics. Uncertainties are quantified and safety factors are established from a reliability analysis.

Identification of a load model for crowd-rhythmic activities based on acceleration measurements of a building floor

The floors of modern buildings are prone to excessive vibrations induced by human actions, especially when a group of people perform rhythmic activities in a coordinated manner. A reliable model for this load case, taking into account the experimentally observed group effect, is thus essential for the serviceability assessment of such structures. In this paper, a frequency-domain load model for either a single person or multiple individuals was established for two rhythmic activities. The model parameters were determined by an indirect identification method from acceleration responses. An extensive experimental test campaign was conducted on a steel–concrete composite floor in order to provide input data for identification, including experimental modal analysis and human-induced vibration tests for up to 32 individuals. The load parameters were first determined for the single-person load model. Root Mean Square (RMS) forces were then calculated from the identified load models, and corresponding coordination factors as a function of crowd size are suggested. A decreasing exponential was obtained for up to 8 persons for skipping and 12 persons for jumping, followed by a constant plateau for larger groups. The proposed models involve a global coordination factor to be used in conjunction with the identified model corresponding to skipping and jumping activities. A comparison of the proposed model and three existing coordination factor models against experimentally identified forces was performed. The comparison revealed the accuracy of the suggested models with respect to experimentally identified forces, whereas differences to existing factors were found especially for jumping.

Semi-automatic generation of shear wall structural models

Manual creation and adjustment of a structural model is time-consuming and could be erroneous. Thus, a semi-automatic generation method based on little manual operation for shear wall structural models is proposed. It includes fast room identification based on graph structure and depth-first search, a complete process of generating structural members including shear walls, structural beams, and slabs, and a rapid process of load modeling. The method is proven accurate and effective in member and load modeling, as demonstrated by two actual engineering cases. Specifically, the structural model is adequately controlled by parameters; the members are correctly generated and interconnected; the load magnitude and arrangement are consistent with the manual results; and the time consumption is generally within one minute. Thus, the proposed method can assist in structural modeling tasks and provide a high-speed information communication between architectural drawings and structural calculation software.

Three-dimensional flow simulation and cavitation erosion modeling for the assessment of incubation time and erosion rate

A compressible three-dimensional in-house flow solver is employed for the assessment of cavitation erosion. The flow solution method provides the wall load, which is coupled to a one-dimensional ductile material model and which yields the incubation time and erosion rate. Due to the assumption of a homogeneous mixture in the flow solver, details of collapsing wall adjacent single bubbles cannot be resolved, so that two different wall load models are presented. In the first method, a collapse detection algorithm based on the mass flux divergence is applied, load collectives are statistically evaluated by the multitude of detected collapses, and a spectrum of distinct loads is passed on to the material model. Since the physical simulation time is much shorter than the real exposure time, a method for the time extrapolation of the wall load to capture realistic time scales is presented. In the second method, a sub grid scale micro jet model is applied, and the wall load is approximated by mean values, so that a time extrapolation is dispensable. Both methods require calibration to e.g. experimentally measured incubation time. An application to the widely used Grenoble axisymmetric impinging jet test case reveals, that the first method fails to capture the location of maximum wear. Due to the inclusion of an erosion probability for the detection of prospectively erosive collapse events in the second method, a good match with data is obtained. Beyond a validation for a broad range of erosive flow conditions, the use of alternative material models including high cycle fatigue as important wear mechanism is planned in future studies.

Longitudinal Seismic Analysis of Tunnels with Nonuniform Strata Considering the Effect of Karst

The longitudinal direction of shield tunnels is prone to seismic damage due to excessive deformation under seismic action, especially in nonuniform stratum. In this paper, the longitudinal dynamic response of the tunnel under different seismic effects is calculated based on the longitudinal equivalent stiffness model using the stratigraphic load model, and the seismic indexes such as longitudinal corner, tube sheet and joint bolt stresses are verified. The calculation results show that the longitudinal seismic weakness of the shield tunnel is in the interface between soft and hard strata and karst development. The longitudinal axial force of the structure is larger during the longitudinal excitation of seismic waves, and the maximum bending moment is mainly in the vertical plane, i.e., the vertical bending moment. The axial force of the tunnel is smaller during the transverse excitation of seismic waves. The maximum bending moment is mainly the bending moment in the horizontal plane, i.e., the transverse moment. The South Lake section of the Two Lakes Tunnel has good seismic performance in the event of a rare earthquake with a 50-year exceedance probability of 2%. The investigation can guide the seismic design of the South Lake section of the Two Lakes Tunnel.

Demand response method considering multiple types of flexible loads in industrial parks

With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before. It is highly important to model flexible loads based on demand response. Therefore, a new demand response method considering multiple flexible loads is proposed in this paper to character the integrated demand response (IDR) resources. Firstly, a physical process analytical deduction (PPAD) model is proposed to improve the classification of flexible loads in industrial parks. Scenario generation, data point augmentation, and smooth curves under various operating conditions are considered to enhance the applicability of the model. Secondly, in view of the strong volatility and poor modeling effect of Wasserstein-generative adversarial networks (WGAN), an improved WGAN-gradient penalty (IWGAN-GP) model is developed to get a faster convergence speed than traditional WGAN and generate higher quality samples. Finally, the PPAD and IWGAN-GP models are jointly implemented to reveal the degree of correlation between flexible loads. Meanwhile, an intelligent offline database is built to deal with the impact of nonlinear factors in different response scenarios. Compared with Fourier, SVM, and BP-NET, the root mean square error is reduced by 2.854MW, 3.576MW, and 3.507MW, respectively. The relative error of the amount of unresponsiveness has been reduced significantly by over 25% compared to the traditional methods. Numerical examples have been performed with the results proving that the proposed method is significantly better than the existing technologies in reducing load modeling deviation and improving the responsiveness of park loads.

Distributed Generation and Load Modeling in Microgrids

Solar PV and wind energy are the most important renewable energy sources after hydroelectric energy with regard to installed capacity, research spending and attaining grid parity. These sources, including battery energy storage systems, and well-established load modeling have been pivotal to the success of the planning and operation of electric microgrids. One of the major challenges in modeling renewable-based DGs, battery storage, and loads in microgrids is the uncertainty of modeling their stochastic nature, as the accuracy of these models is significant in the planning and operation of microgrids. There are several models in the literature that model DG and battery storage resources for microgrid applications, and selecting the appropriate model is a challenging task. Hence, this paper examines the most common models of the aforementioned distributed energy resources and loads and delineates the mathematical rigor required for characterizing the models. Several simulations are conducted to demonstrate model performance using manufacturers’ datasheets and actual atmospheric data as inputs.