Substation system simulation models for transformer risk assessment analysis

This paper comprises a study which is carried out to investigate and evaluate the effect of lightning stresses on the 132 kV substation in the way to improve its reliability in the event of active lightning activities. The paper also detailed the modelling parameters of substation for this transient analysis in order to evaluate the performance and to recommend such configuration to optimize its design to be not only to withstand the stresses but to be more cost effective. The modelling and simulation are carried out using one of the most powerful power system simulations tools that is PSCAD-EMTDC and the substation layout design is adapted from 132/11 kV Simpang Renggam -- Ayer Hitam substation, courtesy of TNB. The model is based on single phase line model as it was suggested by the IEEE to be adequate to represent the substation in transient analysis simulation. The outcome of this paper would be the results of lightning stresses in term of voltage level measured at particular points in substation. The results are then compared with the suggested BIL for assessment of transformer failure

Application of substation transient modelling technique for surge arrester studies

This paper presents the application of transient modelling technique in representing the substation and performing the analysis on the prediction of the transformer damage. Modelling parameters and the substation layout design are based and adapted from 132/11 kV Simpang Renggam – Ayer Hitam substation in Johor Baharu, Malaysia, courtesy of the Tenaga Nasional Berhad (TNB). The model is based on single phase line model as it was suggested by the IEEE to represent the substation in transient analysis simulation. Extensive analyses on the placement of the surge arresters at the substation and prediction of the transformer damage are also presented. The results obtained from this analysis are then compared with the suggested Basic Lightning Insulation Level (BIL) by the TNB, according to the standards, for assessing the percentage of transformer damage and optimizing the substation performance in terms of its reliability and cost effectiveness

Robust composite nonlinear feedback for nonlinear Steer-by-Wire vehicle’s Yaw control

Yaw control is a part of an Active Front Steering (AFS) system, which is used to improve vehicle manoeuvrability. Previously, it has been reported that the yaw rate tracking performance of a linear Steer-by-Wire (SBW) vehicle equipped with a Composite Nonlinear Feedback (CNF) controller and a Disturbance Observer (DOB) is robust with respect to side wind disturbance effects. This paper presents further investigation regarding the robustness of the combination between a CNF and a DOB in a nonlinear environment through a developed 7-DOF nonlinear SBW vehicle. Moreover, in contrast to previous studies, this paper also contributes in presenting the validation works of the proposed control system in a real-time situation using a Hardware-in-Loop (HIL) platform. Simulation and validation results show that the CNF and DOB managed to reduce the influence of the side wind disturbance in nonlinearities

Evaluation and assessment of transformer failure on 132kV substation

Insulation coordination models are an essential part of power system studies and are used to determine the expected overhead line back-flashover rate. A study is carried out to investigate and evaluate the effect of lightning stresses on the 132 kV substation in the way to improve its reliability in the event of active lightning activities. This paper also presents the modeling guidelines on substation for this transient analysis in order to evaluate the performance and to recommend such configuration to optimize its design to be not only to withstand the stresses but to be more cost effective. The modeling and simulation are carried out using one of the most powerful power system simulations tools that is PSCAD-EMTDC and the substation layout design is adapted from 132/11 kV Simpang Renggam-Ayer Hitam substation, courtesy of Tenaga Nasional Berhad, Malaysia (TNB). The model is based on single phase line model as it is suggested by the IEEE to be adequate to represent the substation in transient analysis simulation. The outcome of this paper will be the results of lightning stresses in term of voltage level measured at particular points in substation. The results are then compared with the suggested basic lightning insulation level (BIL) for assessment of transformer failure

Wheel slip control based on composite nonlinear feedback

To produce faster vehicle acceleration and avoid wheelspin on slippery roads, the wheel slip must be controlled to achieve maximum traction. Recent researches in slip control always had to compromise between speed of time response and overshooting. This research studies the application of Composite Nonlinear Feedback (CNF) controller for vehicle wheel slip control, particularly for in-wheel electric vehicle. A strategy for applying the CNF controller which involves feedback linearization is proposed. The CNF is a combination of a linear feedback law and a nonlinear feedback law without any switching element. The CNF control focuses on improving the transient performance. The proposed control strategy is validated by simulation

A systematic review on the autonomous emergency steering assessments and tests methodology in ASEAN

Safety should be the top priority for any automaker - because traffic accidents roughly killed 1.4 million people worldwide, ranking tenth on the World Health Organization's list of leading causes of death. Two decades ago, the focus was on passive safety, where it helps vehicle occupants to survive the crash. However, the frontier in safety innovation has moved beyond airbags and side-impact protection. Today, the frontier is active safety for preventing collisions before they occur. In Euro NCAP 2025 Roadmap, this active safety frontier falls under the primary safety and has become one of the overall safety rating initiatives toward safer cars. The primary safety features four technologies to be assessed, including driver monitoring (2020), automatic emergency steering (2020, 2022), autonomous emergency braking (2020, 2022), and V2x (2024). However, this initiative is partially encapsulated in the ASEAN NCAP Roadmap 2021-2025 under – 'Safety Assist' technological feature. For instance, in the new roadmap, ASEAN NCAP only focuses on Auto Emergency Braking (AEB) technology. This AEB is a feature to alert drivers to an imminent crash and help them use the car's maximum capacity. Therefore, as benchmarked to the EURO NCAP, this paper comprehensively reviews the AES demand, assessments, control, and testing methodology and can be further developed to consolidate for the ASEAN NCAP safety rating schemes

Analysis of EMG signals during stance and swing phases for controlling Magnetorheological Brake applications

The development of ankle foot orthoses (AFO) for lower limb rehabilitation have received significant attention over the past decades. Recently, passive AFO equipped with magnetorheological brake had been developed based on ankle angle and electromyography (EMG) signals. Nonetheless, the EMG signals were categorized in stance and swing phases through visual observation as the signals are stochastic. Therefore, this study aims to classify the pattern of EMG signals during stance and swing phases. Seven-time domains features will be extracted and fed into artificial neural network (ANN) as a classifier. Two different training algorithms of ANN namely Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) will be applied. As number of inputs will affect the classification performance of ANN, different number of input features will be employed. In this study, three participants were recruited and walk on the treadmills for 60 seconds by constant the speed. The ANN model was designed with 2, 10, 12, and 14 inputs features with LM and SCG training algorithms. Then, the ANN was trained ten times and the performances of each inputs features were measured using classification rate of training, testing, validation and overall. This study found that all the inputs with LM training algorithm gained more than 2% average classification rate than SCG training algorithm. On the other hand, classification accuracy of 10, 12 and 14 inputs were 5% higher than 2 inputs. It can be concluded that LM training algorithm of ANN was performed better than SCG algorithm with at least 10 inputs

Motion sickness mitigation in autonomous vehicle: a mini-review

An autonomous vehicle is a rapidly evolving technology that received attention from researchers due to its potential benefits. Besides the advantages, there are also non-negligible issues that need to be overcome in the middle of the autonomous vehicle development process. Among all the challenges, one of the important topics that have not gained adequate consideration is motion sickness (MS). This paper reviews the benefit and challenges of autonomous vehicles, MS factors, the quantifying methods of MS, and the mitigation strategies of MS. Considering the importance of minimizing MS, it is concluded that the number of strategies to lessen MS's severity is still lacking; hence, requiring more attention from automotive researchers

Modeling of 132 kV substation for insulation coordination

Substation is an essential part of the grid systems which often regarded as the most expensive component in the power systems. In general, insulation coordination studies are an important and are used to determine the reliability of the substation. In most blueprints, the default design of a substation always being designed to have an absolute protections where all the possible stresses had already put into account according to the applied standard which sometimes being overprotected and expensive. The intention of this work is to model an existing substation in the way to investigate its design capability to withstand the excessive transient over voltage (i.e. lightning surge), in an attempt to have a more cost effective design model. The selected substation model is adopted from a 132 kV Simpang Renggam-Ayer Hitam substation. The substation is modeled using PSCAD/EMTDC software and the substation drawing details has been courteousness provided by the Tenaga Nasional Berhad (TNB). Throughout the model, several issues have been addressed and carried out in this study regarding the optimization of the substation design. Issues such as arrester placement strategies, determination of transformer breakdown current, arrester placement distance, as well as the energy handling capability for the arrester have been investigated. The findings unveil that; proper placement of arrester is crucially needed in order to optimize the substation performance in term of its reliability and cost effective. Besides that, the determination of current level associated to the breakdown of the transformer, could help the engineers to estimate the capability of the protection scheme in a way to improve the design. Moreover, the development of energy within the arrester which could cause the reduction of protection scheme potential is not only due to the magnitude of the stress current, but also influenced by other factors such as stress waveform durations and the geographical location of the substation. Finally, the highlight of this work is basically through the development of the substation model via PSCAD. It has become an alternative option for researchers to conduct various investigations in subject to substation design improvement and insulation coordination studies

Cartographer local SLAM optimization using multistage distance scan scheduler

This paper presents the utilization of Google’s simultaneous localization and mapping (SLAM) called Cartographer, and improvement of the existing processing speed using multistage distance scheduler. The presented approach optimizes the Local SLAM part in Cartographer to correct local pose based from Ceres scan matcher by integrating scheduling software, which controls the distance of light detection and ranging (LiDAR) sensor and scan matcher’s search window size. In preceding work, the multistage distance scheduler was successfully tested in the actual vehicle to map the road in real-time. Multistage distance scheduler means that local pose correction is done by limiting the distance scan of LiDAR and search window with the help of scheduling algorithm. The scheduling algorithm manages the SLAM to swap between small scan size (25 m) and large scan size (60 m) LiDAR at a fixed time during map data collection; thus it can improve performance speed efficiently better than full-sized LiDAR while maintaining the accuracy of full distance LiDAR. By swapping the scan distance of sensor between small and long-range scan, and adaptively limit search size of scan matcher to handle difference scan size, it can improve pose generation performance time around 15% as opposed against fixed scan distance 60 m while maintaining similar pose accuracy and large map size