Sudden Load Changes Research Articles

Effects of Occlusal Plane Inclination on the Temporomandibular Joint Stress Distribution: A Three-Dimensional Finite Element Analysis.

Background Sudden changes in masticatory loads and occlusal conditions contribute to temporomandibular disorders. Clockwise (CW) or counterclockwise (CCW) rotation of the occlusal plane is one of the factors that alter the direction of the occlusal forces transmitted to the temporomandibular joint structures. Finite element analysis was used to identify possible regions of high stress in the temporomandibular joint. Materials and Methods A computer-aided design model of a symmetrical edentulous maxillomandibular bony complex with a temporomandibular joint was manually generated using Rhinoceros 4.0 freeform modeling software. Three-dimensional discrete mesh generation was performed using VRMesh Studio. The reference occlusal plane angle was accepted as 8° in the sagittal plane, and by modifying 4° in the CW and CCW directions, CW and CCW models were obtained, respectively. The present study aimed to evaluate the changes in stress distribution in the condylar cartilage and temporomandibular disc using the von Mises and maximum-minimum principal stress evaluations of three different occlusal plane inclinations. The null hypothesis of this three-dimensional finite element analysis was that “occlusal plane inclination does not change the stress distribution on the temporomandibular joint structures.” Results The compressive stress on the condyle increased with CW rotation of the occlusal plane. The von Mises equivalent stress of the temporomandibular disc shifted to the medial, posterior, and superior directions after CW and CCW rotations of the occlusal plane. The CW rotation of the occlusal plane increased the von Mises equivalent.

Hierarchical frequency and voltage control using prioritized utilization of inverter based resources

We propose a novel hierarchical frequency and voltage control design for multi-area power system integrated with inverter-based resources (IBRs). The design is based on the idea of prioritizing the use of IBRs over conventional generator-based control in compensating for sudden and unpredicted changes in loads and generations, and thereby mitigate any undesired dynamics in the frequency or the voltage by exploiting their fast actuation time constants. A new sequential optimization problem, referred to as Area Prioritized Power Flow (APPF), is formulated to model this prioritization. It is shown that compared to conventional power flow APPF not only leads to a fairer balance between the dispatch of active and reactive power from the IBRs and the synchronous generators, but also limits the impact of any contingency from spreading out beyond its respective control area, thereby guaranteeing a better collective dynamic performance of the grid. This improvement, however, comes at the cost of adding an extra layer of communication needed for executing APPF in a hierarchical way. Results are validated using simulations of a 9-machine, 6-IBR, 33-bus, 3-area power system model, illustrating how APPF can mitigate a disturbance faster and more efficiently by prioritizing the use of local area-resources.

Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms

Solar photovoltaic systems are widely used; however, their performance is bound to weather conditions, depending on irradiation, temperature, and the effect of shadows. Maximum Power Point Tracking techniques have been developed to solve this issue. Standard methods use mainly-two algorithms: Perturb and Observe and Incremental Conductance. However, such algorithms perform differently when the Solar photovoltaic system works under sudden solar irradiation changes, temperature, and load changes. This research proposes an optimized Maximum Power Point Tracking controller based on the Grey Wolf Optimization algorithm using the MATLAB/Simulink software as an alternative to the traditional techniques. Global efficiency and Root Mean Square Error evaluate the controller's performance. The response time is analyzed using the Grey Wolf Optimizer algorithm, Wolf Optimizer Algorithm, Simulated Annealing, and Particle Swarm Optimization. These four metaheuristic algorithms are compared to the Perturb and Observe, and Incremental Conductance algorithms. The models are analyzed for the transient state and full-day operation scenarios for constant and variable irradiations, temperatures, and loads. The comparative results show that the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm has superior performance, giving an average 6% output power higher than the other controllers under the test scenarios evaluated. The efficiency of the proposed model was, on average, 3% higher than the Incremental Conductance and Perturb & Observe controllers. For the MPPT controller tunning stage, the Grey Wolf Optimizer Algorithm had the best performance with an RMSE of 255.3549 with a compute time of 27.3 min; the worst performing was the Particle Swarm Optimization with an RMSE of 332.4075 and 27.8 min computation time. The proposed GWO optimized MPPT controller had the faster settling time for each irradiation level compared, with an average of 0.175 s. Also, results showed an improvement of the system response throughout the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm since a lower curling effect is obtained at power converter outputs.

Design of a new backstepping controller for control of microgrid sources inverter

<p><br />Emergency power supply is becoming an important capability for many home or industrial electronic and computer devices. Therefore, the performance of the designed unintermptible power supplies (UPS) inverters has low distortion at the output voltage. Initially, such inverters were controlled by proportional integral (PI) control classic rules. This method is difficult to understand the limitations of stability and to apply transient response to strong external disturbances. In this paper, an inverter is simulated and offered for single-phase and three-phase voltage controlled by a non-linear controller. For this purpose, a comparison has been made between the controller performance and the PI controller. In the first step, there is a backstepping regulator that uses the stability tool next to the Lyapunov function. And the other regulator operates according to the PI method. The performance of these two regulators is simulated during a change in reference or a load change in MATLAB. Also, a method of feedback voltage control based on the Lyapunov theory for controlling of the distributed generation (DG) unit independent Inverter is presented. The proposed controller is not only simple, but also against the sudden changes in load and the unspecified system is resistant.</p>

Interfacing Standalone Loads With Renewable Energy Source and Hybrid Energy Storage System Using a Dual Active Bridge Based Multi-Port Converter

Batteries used for providing backup power in renewable energy sources (RES) fed standalone power systems often suffer from a limited lifetime because of high charging and discharging currents arising from sudden changes in load and/or generation. To prevent this, supercapacitors (SCs) are used to supply the high-frequency (HF) power surges. In this article, a new way of interfacing hybrid energy storage systems (HESSs) (Battery + SC) with RES and loads by employing a current fed dual active bridge (DAB) converter based multi-port converter (MPC) is proposed. The proposed approach enables the MPC to regulate the load voltage while tracking the maximum power point (MPP) of the RES and protecting the battery from transients arising from variations in load and/or renewable generation. The SC is used for tracking MPP so that the transient changes in RES generation do not cause a sudden rise/fall in the battery current. The employed MPC structure is designed in such a way that most of the power processing takes place in one stage only resulting in lower losses. The number of switches is reduced by merging the power conversion stages, which helps in keeping the cost low. Experimental results on a laboratory prototype under various static and dynamic conditions are presented.

Effects of sudden change in wind loads on running performance of trains on a highway-railway one-story bridge in crosswinds

Effects of sudden change in wind loads on running performance of trains on a highway-railway one-story bridge in crosswinds

A new tuning rule for stabilized integrator controller to enhance the indirect control of incremental conductance MPPT algorithm: Simulation and practical implementation

The Incremental Conductance (IncCond) algorithm based on direct control mode is one of the highest Maximum Power Point Tracking (MPPT) algorithms ensuring multiple performances compared to some other classical methods. Unfortunately, these performances can deteriorate, especially in the case of sudden changes in weather conditions and load variation., Preventing these drawbacks will form the basis of a new IncCond-MPPT scheme based on indirect control mode in which a smooth electrical power response generated by photovoltaic (PV) panels is well ensured, regardless of quick changes in solar irradiance, absolute temperature and load variation. The proposed MPPT approach uses two stages of control. The first one is used to provide the reference PV-module voltage. The second control loop is formulated as a transfer function that is then controlled using an appropriate Integral controller. Its integral gain is well tuned by applying the Routh’s stability criterion on the characteristic equation of the obtained closed loop transfer function. This allows providing the proposed new guideline, which represents the main contribution of this paper. The proposed IncCond-MPPT scheme is compared with the standard one in terms of MPP tracking accuracy and electrical power ratio, which exceeds 97 %, where quick changes of weather conditions and load variations are considered.

Dynamic Stability Analysis of Isolated Power System

The islanded mode of operation of an electric power system (EPS) that has generation capabilities provided by conventional thermal power plants, by a pumped-storage power station, or from an interlink with a neighboring electric power system through an HVDC BtB converter is addressed in this paper. The risk for electrical power systems to fall into an islanded mode has recently grown, as it is caused not just by technical reasons but by a geopolitical situation as well. The current strains demand the close consideration of problems related to EPS operation in an islanded mode. This paper considers several. The research covers the following issues. The response of the islanded system to a sudden and spasmodic load change is analyzed in cases when the system deals with the disturbance with internal resources alone and with the help of an HVDC BtB converter’s frequency control functionality. Analysis of the impact of the settings of the HVDC BtB converter on the system’s response to disturbances is presented and the optimal set of parameters found. The impact of the system’s extended inertia on the system’s response is evaluated by using an additional unit of the pumped-storage power station in synchronous condenser mode. Transients in the system when switching a unit operating in synchronous condenser mode on and off are analyzed. The capability of the system to withstand major disturbances, such as disconnection of the pumped-storage power station’s unit operating in a pump mode and disconnection of the HVDC BtB converter in emergency modes, if a situation demands, is researched. The research is carried out by numerical simulations using PSS Sincal Electricity Basic software. Updated operating parameters of the isolated power system and the LCC HVDC BtB converter, as well as frequency control automation provided by ABB, were used in the simulations.

Improved Active Disturbance Rejection Control Strategy for LCL-Type Grid-Connected Inverters Based on the Backstepping Method

In the process of grid connection of an LCL inverter, sudden changes in load, high harmonics of the grid voltage, sudden changes in power, and other disturbances often occur. These will cause sharp degradation of the grid-connected power quality, so this paper proposes a new solution to the problem of how to reduce and eliminate disturbances in power quality by using a first-order linear active disturbance rejection control (LADRC) strategy with precise compensation via splitting the total disturbance term. An improved overall direct compensation method for total disturbance was proposed. The use of a subdivision compensation term could avoid the misjudgment arising from the estimation of the overall perturbation by the linear expanded state observer (LESO) within the first few weeks of the feedback when the overall compensation was applied. It aimed to reduce the overshooting caused by the overcompensation of the estimated disturbance term and to shorten the system convergence speed. Backstepping control was introduced to optimize the intermediate quantities of LADRC to estimate the error design outer-loop control law. The controlled quantity tracking the input quantity had excellent characteristics, and could set the desired error range quantity as the purpose of approximation. Therefore, backstepping control was suitable as a feedforward control of the system to preprocess the error in the estimated total disturbance of LESO and feed it into the inner loop improvement LADRC. Secondly, an improved control cascade PWM modulation with a PLL phase-locked loop to regulate the inverter output resulted in the elimination of the effects of internal and external disturbances on the grid-connected current and voltage. Finally, the amplitude–frequency characteristics were analyzed and compared for the trackability and antidisturbance of the improved linear active disturbance rejection controller, showing a good performance of the improved active disturbance rejection. At the same time, comparative simulations were conducted to confirm that the grid-connected current of the LCL inverter could obtain a better stability and grid entry quality in the first-order improved linear active disturbance rejection control.

Vector Control of Permanent Magnet Synchronous Motor Based on MRAS Method

In recent years, the application range of electric energy in modern industry has gradually expanded. Permanent magnet synchronous motor has the characteristics of high efficiency and energy saving, and has obvious advantages in traction application. In order to achieve good vector control of permanent magnet synchronous motor in the full speed range, Research on model reference adaptive system (MRAS) and pulsating high frequency injection method to construct the permanent magnet synchronous motor vector control system, and combined with the flux weakening control algorithm to control the motor under the condition of limited inverter output, so as to realize the sensorless vector control of the motor in the full speed range. The difference between the estimated value of the algorithm and the actual value is compared on the actual experimental platform to verify the feasibility of the control algorithm. The experimental results show that, Under medium and high-speed working conditions, the motor speed and rotor position tracking accuracy of MRAS algorithm is high, and the tracking error is less than 0.01rad. The pulsating high-frequency injection method can accurately track the permanent magnet synchronous motor under low-speed working conditions, the speed error is less than 1n / R / min, and the rotor position error is less than 0.03rad. The static and dynamic performance of the control system is good, It can better deal with the sudden change of motor load. Using MRAS algorithm and pulsating high frequency injection method to control permanent magnet synchronous motor in full speed range is of great significance to improve the speed control performance of permanent magnet synchronous motor.

Comparative Study of BLDC Motor Drives with Different Approaches: FCS-Model Predictive Control and Hysteresis Current Control

The control techniques of the brushless DC (BLDC) motor have gained a large amount of interest in recent years, with their use being implemented in order to achieve a high-performance drive, including quick transient response and high-quality waveforms at the steady state. This paper provides a comparative study between three control schemes of BLDC motors: the direct power control scheme using a finite control set model predictive control (FCS-MPC) approach, the stator current controlled scheme using an FCS-MPC approach, and the stator current controlled scheme using ON–OFF hysteresis current controllers. The three systems were studied and investigated under the same operating conditions. The comparative study included investigating the performance of the BLDC drive in both steady state and transient operations. Qualitative and quantitative analyses were performed on the results obtained with each control scheme. The obtained results demonstrate the validity and effectiveness of the three investigated schemes in controlling the motor speed to the desired value under sudden load changes and achieving satisfactory quick transient responses. However, the results indicate the superiority of the direct power control scheme using an FCS-MPC approach over the others in terms of its minimum torque ripple, lowest torque and speed pulsations, minimum active and reactive power ripples, and high-quality waveforms of the stator currents drawn by the motor with minimum THD.

A Novel PV Maximum Power Point Tracking Based on Solar Irradiance and Circuit Parameters Estimation

This research paper presents a novel maximum power point taking (MPPT) algorithm. The algorithm uses an adaptive calculation block to estimate the solar irradiance and the PV I–V curve circuit parameters based on the PV panel’s measured output current and voltage. In the proposed algorithm, the output power does not oscillate around the maximum power point (MPP) compared to conventional MPPT methods. Moreover, the proposed algorithm does not require expensive solar irradiance sensors compared with trackers that depend on measured solar irradiance. In addition, the proposed MPPT can handle the fast variation in solar irradiance. The PV panel nonlinear I–V curve was modeled using a single-diode PV. The algorithm with the adaptive block was tested separately to verify the ability of the system to estimate the solar irradiance and the circuit parameters. The solar system was then simulated using MATLAB/Simulink to evaluate the robustness of the proposed method under steady-state and during sudden changes in solar irradiance and load. The proposed solar system reaches the steady-state in 8 ms after a step-change in the solar irradiance. In the worst-case scenario, the proposed system achieves a relative error of around 2.64% in estimating the solar irradiance at 600 W/m2 with an efficiency of 99.3%.

A multi-rate sampling PMU-based event classification in active distribution grids with spectral graph neural network

Phasor measurement units (PMUs) are time-synchronized measurement devices that have been proliferated in transmission networks during the last two decades. Recently, there have been efforts to bring this technology to distribution grids for different applications such as three-phase state estimation, fault and event analyses, and phase identification. Streamed time-synchronized voltage and current phasor data can be used for events classification and region identification along distribution feeders to determine the type and location of events, which are important features of any fault and event detection, location, and isolation software. In this paper, the spectral theory-based graph convolution is used for event classification and region identification. The proposed model uses modified graph convolution filters to aggregate the regional multi-rate samples of PMU data, i.e., voltage magnitude and angles from several nodes. Besides these temporal data of the measured nodes, the physical configuration of the network containing edge features are given to the graph convolution network (GCN) to not only classify the event type, but also identify the affected region and location. The proposed graph-based method is tested on a standard test system with capacitor and distributed energy resources-related events, malfunction of voltage regulator, sudden load changes, and different types of faults. The results are compared with baseline methods, Chebyshev graph neural network (GNN), decision tree, logistic regression and K-nearest neighbor using the accuracy, recall, precision and F-1 score metrics. Furthermore, performance sensitivity analysis is carried out with respect to the number of installed PMUs, measurement noise level, size of available historical data, availability of network edge features, and different designs of GNN.

Power System Stability Improvement by LQR Approach and PSS Considering Electric Vehicle as Disturbance

Low frequency oscillations result due to heavy loading conditions line faults, sudden change of generator output and also due to poor damping of interconnected power systems. There are different types of disturbances in the power system like sudden change of load, generation, faults, switching of lines. This hampers the power transmission capacity of the lines and the stability of the system There are significant impacts on the system stability during the charging and discharging operation of Electric Vehicle (EV). In the present work the charging operation of EV is considered as a load disturbance. The introduction of these vehicles in the system creates the problem of low frequency oscillation and endanger the system stability and security. In the present work the Single machine infinite bus system (SMIB) is first developed using mathematical modelling with consideration of EV disturbance. The LQR approach from optimal control theory is then applied in the system to damp the system oscillations, improving the system eigenvalues and enhancing the stability. The stability is seen in the system after LQR from various figures. In the second work the plotting of variation of different state variables is done using three different methods which are the transfer function model method, using code and then using state space representation of the system. The work is further extended by adding Power system stabilizer (PSS) to the system, again considering the EV disturbance. The time domain simulation results showed the improvement in stability using PSS device. Thus, in the present work the oscillations problems created due to the introduction of electric vehicles are solved by two methods. The first is implementing LQR approach from optimal control theory in the system and the second method is by adding PSS device in the same system.

Transient Stability Analysis of an HPR-1000 Power Plant using ETAP Software

Transient stability analysis has become an important subject, as the world’s demand for electricity is increasing with an enormous speed, and power systems are facing different challenges, new power plants are being installed to fulfill the demand and supply mismatch, in addition to that degradation of equipment, sudden load changes and switching operations are also some of the problems in large networks. For large power systems it is a highly non-linear problem and also used to analyze whether the system remain in synchronism or not following a disturbance. To analyze the effect of these disturbances and consequences of the outages transient stability analysis is usually performed. In this paper this analysis is performed for an HPR-1000 nuclear power plant connected to the 500kV network of NTDC Grid. Different external 3-phase fault scenarios are considered on the 500kV network and simulated using ETAP (Electric Transient Analyzer Program) software. To analyze the system behavior during and after the fault has occurred, certain parameters are monitored. It was observed that the HPR-1000 power plant-maintained synchronism and remained stable in all the fault scenarios.

A Reliable Loss of Excitation Protection Technique Based on EPFA for Synchronous Generators

Loss of excitation (LOE) is one of the most important issues of synchronous alternators, which may be a source of genuine harms and could lead to power system instability. The principle issue to recognize LOE and stable power swing (SPS) is the time delay, which is a primary segment of the recognition time in all ongoing promise strategies. This paper introduces an effective scheme based on the first derivative of equivalent power factor angle (EPFA) of 3-phase voltage and current quantities in the direct-quadrature axis, to detect the LOE. The new algorithm, based on EPFA, is developed to reduce the required time of LOE recognition scheme. Comprehensive simulation studies are accomplished using MATLAB/Simulink as a robust simulation tool for various generator conditions such as full load and sudden load changes in addition to 3-phase faults with different location and duration times. The relay setting is determined and the algorithm performance is evaluated depending on various scenarios in power system. The simulated study results confirm that the proposed method can discriminate SPS from LOE conditions under different modes of operations.

Integral sliding mode based direct power control of isolated DC‐DC converter for improved voltage regulation

AbstractThis article presents an isolated bidirectional DC‐DC dual active bridge (DAB) converter with an integral sliding mode‐based direct power control (SM‐DPC). Maintaining the dc‐link stability and obtaining a robust control for the converter during sudden load change is a significant challenge. The sliding mode control is well known for its robustness, stability, and tracking performance. The sliding surface based on output voltage error is selected, while the proposed method utilizes the equivalent control approach to generate the power reference for the DAB converter. The direct power control provides an easy control method for the DAB converter as the output voltage depends on the transmitted power, governed by the phase shift angle of two H‐bridges of the converter. The proposed method enhances the steady‐state performance and renders a fast transient response under load change and input voltage variation. Moreover, the method avoids complicated converter modeling and utilizes the voltage dynamic equation and power transfer equation for the controller design. The controller performance and effectiveness are validated with experimental results for a 2‐kW DAB converter.

Dynamic Performance Evaluation of the Secondary Control in Islanded Microgrids Considering Frequency-Dependent Load Models

Performance analysis is challenging in modern power distribution networks due to the increasing penetration of distributed energy resources (DERs) interfaced by voltage source converters (VSCs). Parameter uncertainty, black-box models of the components, and low inertia are some of the issues that must be addressed. The latter can represent high vulnerabilities to sudden load changes in a microgrid (MG). Additionally, the islanded operation represents a challenge for inverter-based (DERs), where secondary control must regulate the microgrid frequency and voltage to its nominal values. When a secondary control strategy is implemented, it is necessary to validate its performance under several conditions. Most existing research papers focus on the microgrid’s small-signal and transient stability. At the same time, little has been done on the influence of the load model on voltage stability. This type of analysis is required to ensure an adequate transition between the grid-connected and stand-alone modes. This paper provides a voltage stability analysis of a microgrid, considering secondary control based on receding horizon and frequency-dependent load models. Simulation results demonstrate the robust performance of the secondary control and validate the importance of considering or adapting voltage stability indices to ensure adequate microgrid performance.

Golden Eagle Optimized Control for a Dual Stage Photovoltaic Residential System with Electric Vehicle Charging Capability

ABSTRACT In this article, the control of a grid-connected, single-phase, dual-stage photovoltaic (PV) residential system with electric vehicle (EV)-charging capability is being presented. A residential system faces a lot of dynamic conditions such as changing atmospheric condition or random patterns of load connection or disconnection as well as power failure. In this regard, this article proposes the optimization of proportional and integral gains selection of the bidirectional DC/DC converter (BDC) PI controller through golden eagle optimization (GEO) algorithm to improve the system performance. The system is subjected to various induced dynamic conditions simulated in MATLAB Simulink environment and the performance is compared with particle swarm optimization, genetic algorithm, and gains obtained through hit and trial. In comparison with other techniques, GEO algorithm provides optimum BDC PI gains, as a result, the DC-link voltage achieves 1.5 times shorter settling time. During the non-linear load changes and voltage swell condition, the settling time is 2 times shorter. Settling time of the EV battery power shows 1.7 times reduction. The transient response of the PV power also shows dramatic improvement with 3 times faster settling time during solar insolation changes. During the sudden non-linear load changes, the momentary transients die 1.5 times faster. Moreover, a seamless control is developed to achieve a seamless transition from islanded mode to grid connected mode and vice versa. The proposed system achieves unity power factor and complies with the IEEE -519 power quality standard.

Control Design and Parameter Tuning for Islanded Microgrids by Combining Different Optimization Algorithms

Load and supply parameters may be uncertain in microgrids (MGs) due for instance to the intermittent nature of renewable energy sources among others. Guaranteeing reliable and stable MGs despite parameter uncertainties is crucial for their correct operation. Their stability and dynamical features are directly related to the controllers’ parameters and power-sharing coefficients. Hence, to maintain power good quality within the desirable range of system parameters and to have a satisfactory response to sudden load changes, careful selection of the controllers and power-sharing coefficients are necessary. In this paper, a simple design approach for the optimal design of controllers’ parameters is presented in an islanded MG. To that aim, an optimization problem is formulated based on a small-signal state-space model and solved by three different optimization techniques including particle swarm optimization (PSO), genetic algorithm (GA), and a proposed approach based on the combination of both PSO and GA. The optimized coefficients are selected to guarantee desirable static and dynamic responses in a wide range of operations regardless of the number of inverters, system configuration, output impedance differences, and load types. Through the proposed design and tuning method, the performance of the MG is improved as compared to those obtained using state-of-art techniques. This fact is demonstrated by using numerical simulations performed on a detailed model implemented in PSIM© software.