A discussion about the limitations of the Eurocode’s high-speed load model for railway bridges

High-speed railway bridges are subjected to normative limitations concerning maximum permissible deck accelerations.For the design of these structures,the European norm EN 1991-2 introduces the high-speed load model(HSLM)—a set of point loads intended to include the effects of existing high-speed trains.Yet,the evolution of current trains and the recent development of new load models motivate a discussion regarding the limits of validity of the HSLM.For this study,a large number of randomly generated load models of articulated,conventional,and regular trains are tested and compared with the envelope of HSLM effects.For each type of train,two sets of 100,000 load models are considered:one abiding by the limits of the EN 1991-2 and another considering wider limits.This comparison is achieved using both a bridge-independent metric(train signatures)and dynamic analyses on a case study bridge(the Canelas bridge of the Portuguese Railway Network).For the latter,a methodology to decrease the computational cost of moving loads analysis is introduced.Results show that some theoretical load models constructed within the stipulated limits of the norm can lead to effects not covered by the HSLM.This is especially noted in conventional trains,where there is a relation with larger distances between centres of adjacent vehicle bogies.

Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

In the conventional technique,in the evaluation of the severity index,clustering and loading suffer from more iteration leading to more com-putational delay.Hence this research article identifies,a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects.The polynomial load modelling or ZIP(constant impedances(Z),Constant Current(I)and Constant active power(P))is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security.The process of finding the severity of the line using a Hybrid Line Stability Ranking Index(HLSRI)is used for assisting the concepts of machine learning with J48 algorithm,infers the superior affected lines by adopting the IEEE standards in concern to be compensated in maintaining the power system stability.The simulation is performed in the WEKA environment and deals with the supervisor learning in order based on severity to ensure the safety of power system.The Unified Power Flow Controller(UPFC),facts devices for the purpose of compensating the losses by maintaining the voltage characteristics.The finite element analysis findings are compared with the existing procedures and numerical equations for authentications.

A Study on the Load Modeling of Railway Vehicles Using PSCAD/EMTDC Based on MVDC

This paper,the kinetic equation,traction force,and braking force for railway trains are reviewed.In addition,the driving characteristics are interpreted as to how the power of the electric vehicle relates to the weight,speed,track curve,and track gradient of the electric vehicle.The driving characteristics of these trains are analyzed through PSCAD/EMTDC(power systems computer aided design/electromagnetic transients including DC)modeling.

Thrust and Torque Characteristics Based on a New cutter-head Load Model

Full face rock tunnel boring machine（TBM） has been widely used in hard rock tunnels, however, there are few published theory about cutter-head design, and the design criteria of cutter-head under complex geological is not clear yet. To deal with the complex relationship among geological parameters, cutter parameters, and operating parameters during tunneling processes, a cutter-head load model is established by using CSM（Colorado school of mines） prediction model. Force distribution on cutter-head under a certain geology is calculated with the new established load model, and result shows that inner cutters bear more force than outer cutters, combining with disc cutters abrasion; a general principle of disc cutters＇ layout design is proposed. Within the model, the relationship among rock uniaxial compressive strength（UCS）, penetration and thrust on cutter-head are analyzed, and the results shows that with increasing penetration, cutter thrust increases, but the growth rate slows and higher penetration makes lower special energy（SE）. Finally, a fitting mathematical model of ZT（ratio of cutter-head torque and thrust） and penetration is established, and verified by TB880 E, which can be used to direct how to set thrust and torque on cutter-head. When penetration is small, the cutter-head thrust is the main limiting factor in tunneling; when the penetration is large, cutter-head torque is the major limiting factor in tunneling. Based on the new cutter-head load model, thrust and torque characteristics of TBM further are researched and a new way for cutter-head layout design and TBM tunneling operations is proposed.

Load optimal design for a primary test stand facility based on a zero-dimensional load model

In order to couple the numerical simulation of a primary test stand driver with an optimal load design, a zero- dimensional wire array load model is designed based on the Saturn load model using PSPICE, which is an upgraded version of the Simulation Program with Integrated Circuit Emphasis （SPICE） designed by the ORCAD Corporation to perform circuit simulations. This paper calculates different load parameters and discusses factors influencing the driving current curve. With appropriate driving current curves chosen, further magneto-hydrodynamic calculations are carried out and discussed to provide the best results for experiments. The suggested optimal load parameters play an important role in experimental load design.

Measurement-based approach for identification of static load model of electric power system

The validity of electric power system simulation or prediction models depends on static load model. Measurement- based approach is the unique method to identify them adequately. The measured power depends on both load reaction to supply voltage alteration and random process of load alteration Basically, there is no any universal method that can single out the inherent static load model from experimental data. The paper offers a proprietary technique which is the particular solution of the task. The technique considers the selection of neighboring measurement pairs with the supply voltage altering significantly be-tween them, the exclusion of selected pairs by load power factor and subsequent selection of the inherent static load model presented as the polynomial load model. The usage of the technique to identify static load model at “Fenster” industrial enterprise （in Borisov city） is presented. The ideas considered in the paper can be used for future development of static load model identification methods with the data obtained during both active experiment and in other operating models of electric power systems.

Study of Load Modeling Technology on Hardware-in-the-Loop Simulator of Gun Servo System

A hardware-in-the-loop (HWIL) simulator for gun servo system is described in this paper, and its load modeling technologies,such as road spectrum model,sea wave model are studied. The simulation results show that the models can be used in HWIL and satisfy the requirements of hardware-in-the-loop simulator of gun servo system.

Reinforcement Learning Algorithm for Solving Load Commitment Problem Considering a General Load Model

Under the smart grid paradigm, in the near future all consumers will be exposed to variable pricing schemes introduced by utilities. Hence, there is a need to develop algorithms which could be used by the consumers to schedule their loads. In this paper, load scheduling problem is formulated as a LCP （load commitment problem）. The load model is general and can model atomic and non-atomic loads. Furthermore, it can also take into consideration the relative discomfort caused by delay in scheduling any load. For this purpose, a single parameter ＂uric＂ is introduced in the load model which captures the relative discomfort caused by delay in scheduling a particular load. Guidelines for choosing this parameter are given. All the other parameters of the proposed load model can be easily specified by the consumer. The paper shows that the general LCP can be viewed as multi-stage decision making problem or a MDP （Markov decision problem）. RL （reinforcement learning） based algorithm is developed to solve this problem. The efficacy of the algorithm is investigated when the price of electricity is available in advance as well as for the case when it is random. The scalability of the approach is also investigated.

Impact of Weather Conditions and Dynamic Load Models on Steady State and Dynamic Response of Power System

This paper gives an insight on the effect of transmission line temperature variations, resulting from loading and weather conditions changes, on a power system＇s steady state and dynamic performance. The impact of dynamic load models on system stability is also studied. The steady-state and dynamic stability simulation results of a 39 bus system for constant line impedance （the traditional simulation practice） are compared to the results with estimated, but realistic, temperature varied line impedances using PSLF （positive sequence load flow） software. The modulated line impedances will affect the thermal loading levels and voltage profiles of buses under steady state response, while the dynamic results will show improved damping in electro-mechanical oscillations at generator buses.

Harmonic Contributions of Utility and Customer Based on Load Model Using Field Measurements

In recent years, sinusoidal waveform of the current and voltage disturbs in the electrical distribution system because of the due to the increasing number of non-linear loads. Many standards of IEC and IEEE standards have been published in order to limit the voltage and current waveform distortion. The operators of the electricity distribution network widely use the power quality monitoring systems at the point of common connection (PCC). It has been identified that there are substantial number of harmonic currents excess of the standards transferred to the grid according to the data obtained from power quality monitoring systems. In case of exceeding the limits specified in the standards, there is a need to determine the network and customer responsibilities for the implementation of required sanctions. In this study, using recorded data at the PCC of a medium voltage electrical distribution system, voltage and current harmonic distortion responsibilities of the network and customer are determined by the improved harmonic current vector method. Up-to-date load model based on field measurement which provides more accurate results has been used instead of the constant load impedance in the proposed method.

Analytic Formulae for Estimating Motor Proportion of Load Model Under Small Disturbance

In the composite load model(CLM),which is commonly used in China,an equivalent motor and equivalent static load are used to represent all electrical equipment and networks connected to a load bus.Existing research has determined typical values of electrical and mechanical parameters for load models of different load types,which improves the basis for load modeling.However,the motor proportion parameter is not the same for different load buses or at different times;therefore,obtaining the actual motor proportion is key to establishing an accurate load model.In the existing load modeling method,motor proportion is commonly identified along with other parameters under rare large disturbances;therefore,the value of the motor proportion is fixed by the time when a large disturbance occurs.In this paper,formulae are derived to estimate motor proportion under small disturbances,and these formulae allow direct calculation of motor proportion without using any optimization algorithm.The proposed estimation formulae do not rely on any parameters of load model or power system but instead rely only on measurement of the voltage and active power at steady-state points before and after a small disturbance.Because of universality of small disturbances in power systems,estimating time-varying motor proportion under small disturbances will be helpful for solving the time-varying problem of load models.Finally,the proposed motor proportion estimation formulae are validated by simulations,physical experiments,and field experiments.

In-Depth Study on Synthesis Load Modeling

Detailed procedures for the modeling of synthesis load models (SLM) of actual power network are presented, then the classification indices based on 1oad characteristics and the principle of load classification are expounded. Based on the results of general investigation of 220 kV and 330kV substations in China’s power grid, the load characteristics are classified, and detailed load characteristic investigation of selected different kinds of typical substations are carried out. By use of statistical synthesis, the SLM for typical substations, in which the distribution networks are taken into account, are built;and the modeling results are disseminated and applied to whole Chinese power grid. Besides, the load model parameters are evaluated and verified via post-disturbance simulation method. The effectiveness of the built SLM is validated by the fitting of some disturbance incidents.

Analysis of Commutation Failure in Multi-Infeed HVDC System under Different Load Models

HVDC technology has been widely used in modern power system. On one hand, HVDC has the advantages of economy, high efficiency and strong controllability. While on the other hand, it makes the dynamic characteristics of the power system becoming more and more complex. That puts forward a new challenge to system stability and raises new questions for power system simulation. This paper focuses on the interaction between AC and DC systems, especially the problem of commutation failure caused by AC system fault. Based on the data of China Southern Power Grid, this paper calculates the fault regions that may cause commutation failure and calculates the system critical clearance time under different load models, analyzes the impacts of different load models on commutation failure and the stability of AC/DC hybrid system.

Optimal Placement of Multi DG Units Including Different Load Models Using PSO

This paper proposes a multi-objective index-based approach to optimally determine the size and location of multi-distributed generators (DG) units in distribution system with different load models. It is shown that load models can significantly affect the optimal location and sizing of DG resources in distribution systems. The proposed multi-objective function to be optimized includes a short circuit level parameter to represent the protective device requirements. The proposed function also considers a wide range of technical issues such as active and reactive power losses of the system, the voltage profile, the line loading and the MVA intake by the grid. The optimization technique based on particle swarm optimization (PSO) is introduced. The analysis of continuation power flow to determine the effect of DG units on the most sensitive buses to voltage collapse is carried out. The proposed algorithm is tested using the 38-bus radial system and the IEEE 30-bus meshed system. The results show the effectiveness of the proposed algorithm.

Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability

The recently proposed ambient signal-based load modeling approach offers an important and effective idea to study the time-varying and distributed characteristics of power loads.Meanwhile,it also brings new problems.Since the load model parameters of power loads can be obtained in real-time for each load bus,the numerous identified parameters make parameter application difficult.In order to obtain the parameters suitable for off-line applications,load model parameter selection(LMPS)is first introduced in this paper.Meanwhile,the convolution neural network(CNN)is adopted to achieve the selection purpose from the perspective of short-term voltage stability.To begin with,the field phasor measurement unit(PMU)data from China Southern Power Grid are obtained for load model parameter identification,and the identification results of different substations during different times indicate the necessity of LMPS.Meanwhile,the simulation case of Guangdong Power Grid shows the process of LMPS,and the results from the CNNbased LMPS confirm its effectiveness.

Experimental investigation on single person's jumping load model

This paper presents a modified half-sine-squared load model of the jumping impulses for a single person. The model is based on a database of 22,921 experimentally measured single jumping load cycles from 100 test subjects. Threedimensional motion capture technology in conjunction with force plates was employed in the experiment to record jumping loads. The variation range and probability distribution of the controlling parameters for the load model such as the impact factor, jumping frequency and contact ratio, are discussed using the experimental data. Correlation relationships between the three parameters are investigated. The contact ratio and jumping frequency are identified as independent model parameters, and an empirical frequency-dependent function is derived for the impact factor. The feasibility of the proposed load model is established by comparing the simulated load curves with measured ones, and by comparing the acceleration responses of a single-degree-of-freedom system to the simulated and measured jumping loads. The results show that a realistic individual jumping load can be generated by the proposed method. This can then be used to assess the dynamic response of assembly structures.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Accuracy assessment of global vertical displacement loading tide models for the equatorial and Indian Ocean

The three-dimensional displacements caused by ocean loading effects are significant enough to impact spatial geodetic measurements on sub-daily or longer timescales,particularly in the vertical direction.Currently,most tide models incorporate the distribution of vertical displacement loading tides;however,their accuracy has not been assessed for the equatorial and Indian Ocean regions.Global Positioning System(GPS)observations provide high-precision data on sea-level changes,enabling the assessment of the accuracy and reliability of vertical displacement tide models.However,because the tidal period of the K_(2) constituent is almost identical to the orbital period of GPS constellations,the estimation of the K_(2) tidal constituent from GPS observations is not satisfactory.In this study,the principle of smoothness is employed to correct the systematic error in K_(2) estimates in GPS observations through quadratic fitting.Using the adjusted harmonic constants from 31 GPS stations for the equatorial and Indian Ocean,the accuracy of eight major constituents from five global vertical displacement tide models(FES2014,EOT11a,GOT4.10c,GOT4.8,and NAO.99b)is evaluated for the equatorial and Indian Ocean.The results indicate that the EOT11a and FES2014 models exhibit higher accuracy in the vertical displacement tide models for the equatorial and Indian Ocean,with root sum squares errors of 2.29 mm and 2.34 mm,res-pectively.Furthermore,a brief analysis of the vertical displacement tide distribution characteristics of the eight major constituents for the equatorial and Indian Ocean was conducted using the EOT11a model.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Identifiability Analysis of Load Model Parameters by Estimating Confidential Intervals

The identification of load model parameters from practical measurement data has become an essential method to build load models for power system simulation,analysis and control.In practical situations,the accuracy of the load model parameters identification results is impacted by data quality and measurement accuracy,which leads to the problem of identifiability.In this paper,an identifiability analysis methodology of load model parameters,by estimating the confidential intervals(CIs)of the parameters,is proposed.The load model structure and the combined optimization and regression method to identify the parameters are first introduced.Then,the definition and analysis method of identifiability are discussed.The CIs of the parameters are estimated through the profile likelihood method,based on which a practical identifiability index(PII)is defined to quantitatively evaluate identifiability.Finally,the effectiveness of the proposed analysis approach is validated by the case study results in a practical provincial power grid.The results show that the impact of various disturbance magnitudes,measurement errors and data length can all be reflected by the proposed PII.Furthermore,the proposed PII can provide guidance in data length selection in practical load model identification situations.