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Dysarthria, a speech disorder stemming from neurological conditions, affects communication and life quality. Precise classification and severity assessment are pivotal for therapy but are often subjective in traditional speech-language pathologist evaluations. Machine learning models offer objective assessment potential, enhancing diagnostic precision. This systematic review aims to comprehensively analyze current methodologies for classifying dysarthria based on severity levels, highlighting effective features for automatic classification and optimal AI techniques. We systematically reviewed the literature on the automatic classification of dysarthria severity levels. Sources of information will include electronic databases and grey literature. Selection criteria will be established based on relevance to the research questions. The findings of this systematic review will contribute to the current understanding of dysarthria classification, inform future research, and support the development of improved diagnostic tools. The implications of these findings could be significant in advancing patient care and improving therapeutic outcomes for individuals affected by dysarthria.

Parkinson’s Disease (PD) has been found to cause force control deficits in upper and lower limbs. About 50% of patients with advanced PD develop a debilitating symptom called freezing of gait (FOG), which has been linked to force control problems in the lower limbs, and some may only have a limited response to the gold standard pharmaceutical therapy, levodopa, resulting in partially levodopa-responsive FOG (PLR-FOG). There has been limited research on investigating upper-limb force control in people with PD with PLR-FOG, and without FOG. In this pilot study, force control was explored using an upper-and-lower-limb haptics-enabled robot in a reaching task while people with PD with and without PLR-FOG were on their levodopa medication. A healthy control group was used for reference, and each cohort completed the task at three different levels of assistance provided by the robot. Similar significant proportional force control deficits were found in the upper and lower limbs in patients with PLR-FOG versus those without FOG. Some aspects of force control were found to be retained, including an ability to increase or decrease force in response to changes in resistance while completing a reaching task. Overall, these results suggest there are force control deficits in both the upper and lower limbs in people with PLR-FOG.

This paper presents the design, simulation, and implementation of a solid state Tesla coil (SSTC) with music playback functionality through its arcs. It showcases various circuit designs that explore both feedback and non-feedback-based control mechanisms. The non-feedback based mechanism relies on an external oscillator circuit based on NE555 timer IC to drive the Tesla transformer coil at its resonance and the feedback based system relies on the selective amplification of a certain frequency at which the secondary coil is self-resonant. Additionally, to produce tones from the Tesla coil’s arcs, this paper implements a fixed gate signal interrupter circuit design that produces specific tones, as well as a music-based gate signal interrupter circuit design that produces music from the arcs. To verify the functionality of the design, the designed circuits were simulated in the LTspice SPICE simulation software and then implemented on a prototype board followed by a four-layer printed circuit board implementation. The primary coil of the Tesla transformer was controlled using an insulated-gate bipolar transistor (IGBT) based half bridge circuit.

This paper presents a flexible virtual inertia and damping control strategy for a virtual synchronous generator (VSG) for the effective utilization of energy storage. Due to their low inertia and low kinetic energy, power electronics-based renewable energy sources are becoming more and more prevalent, which poses major dependability issues for the grid. However, the typical synchronous generator has the ability to adjust to changes in the grid frequency and voltage thanks to load frequency management and an automatic voltage regulator. So, emulating the synchronous machine characteristics in the power electronics-based converter system increases the stability of the grid and further increases the renewable energy penetration in the grid. However, VSG power and frequency oscillates when a sudden disturbance in the power demand occurs in the distributed generation system. This article focuses on minimizing the frequency oscillations as well as power oscillations of VSG during transient conditions or disturbances. Initially, the impact of varying inertia and damping on the active power control loop of VSG is investigated. In addition, the parameters of the VSG are designed in order to minimize the requirement of discharge/charge from the energy storage. So, in this paper, a control strategy with flexible virtual inertia and damping coefficient is designed for optimizing the energy storage unit to support frequency stability. The proposed control method is verified in the developed experimental prototype. In addition, proposed control algorithm is compared with the currently available adaptive control approaches like adaptive inertia control (adaptive $J$ control) and alternating inertia and damping (alternating $J$ and $D_{P}$ control) based VSG and observed that the energy storage requirement and the oscillations in the active power and frequency are minimum in the proposed control method as compared to the other two methods.

Distance protection is popular in transmission networks and constitutes a large installed base across grid systems. The most widely accepted implementation of distance protection is based on voltage and current phasors. Today the electric grids are becoming increasingly complex and dynamic in nature. With power electronic converter interfaced systems such as renewables, HVDC, FACTS, etc., there is a need for fast, secure and reliable protection decisions. The phasor-based distance protection is prone to reliability issues in such networks and is inherently limited in speed. Recently, ultra-fast protection solutions based on fault induced traveling waves are commercially available. Although promising, such solutions may miss faults near voltage zero-crossing, falsely detects nonfaulty disturbances as faults and as such lack wider acceptance in contemporary transmission lines where protection security is a non-negotiable requirement. In comparison, time-domain based distance protection solutions have appeal in terms of reliability and speed. In addition, an ideal time-domain distance protection should be applicable to various networks such as series compensated lines, lines connected to renewables and long underground/sub-sea cables. In this paper, we propose a method for time-domain based distance protection to meet these requirements. The method operates based on current based operating quantity and a novel dynamic restraining quantity which is calculated for the fault zone boundary point. The proposed method inherently overcomes influence of series compensation, renewable integration and provides a fast and reliable identification of in-zone and out-of-zone faults. It is tested for various networks using laboratory experimental data and field records. Further it is implemented in an IED platform and tested with RTDS simulations in hardware-in-loop mode. The method is found to work satisfactorily and consistently over the extensive test scenarios.

Three-terminal hybrid transmission lines (TTHTLs) are attractive from both environmental and commercial view. Hybrid transmission lines are growing due to urbanization, connecting an industrial load and renewable integration. A TTHTL comprises sections of both overhead lines and underground/subsea cables or overhead lines with different X/R ratios. Faulted section identification (FSI) is key for defining the adaptive/selective auto-reclosing scheme and estimation of the fault location for TTHTLs. In this paper, FSI and fault location algorithms are proposed without using the parameters of any line section. Novelty of the methodology lies in a two-stage approach to the problem. In the first stage, series impedance parameters of all the sections are calculated using closed loop formulae. These parameters are then utilized in identifying the faulted section. In the second stage, the above calculated line section parameters and faulted section are used to estimate complete line parameters including shunt capacitance and subsequently the fault location. The advantage of the proposed method is that it does not require an initial guess of the line section parameters, is non-iterative in the first stage, and provides correct fault section identification for TTHTLs. These features make it suitable for designing the selective auto-reclosing protection scheme for the TTHTLs within traditional protection relaying hardware. More importantly, the series impedance parameters calculated in the first stage constitute good initialization values for the non-linear problem of estimating the complete line parameters. This results in better convergence of the algorithm and accurate parameter estimation. The developed solution is verified using the PSCAD/EMTDC simulations for TTHTLs connected with conventional and different inverter-based renewable resources. The performance of the proposed solution is compared with commercially available solutions, and it is found to be accurate. This solution is amenable for implementation in line differential protection relays without additional infrastructural changes.

Biomedical image segmentation (BIS) task is challenging due to the variations in organ types, position, shape, size, scale, orientation, and image contrast. Conventional methods lack accurate and automated designs. Artificial intelligence (AI)-based UNet has recently dominated BIS. This is the first review of its kind that microscopically addressed UNet types by complexity, stratification of UNet by its components, addressing UNet in vascular vs. non-vascular framework, the key to segmentation challenge vs. UNet-based architecture, and finally interfacing the three facets of AI, the pruning, the explainable AI (XAI), and the AI-bias. PRISMA was used to select 267 UNet-based studies. Five classes were identified and labeled as conventional UNet, superior UNet, attention-channel UNet, hybrid UNet, and ensemble UNet. We discovered 81 variations of UNet by considering six kinds of components, namely encoder, decoder, skip connection, bridge network, loss function, and their combination. Vascular vs. non-vascular UNet architecture was compared. AP(ai)Bias 2.0-UNet was identified in these UNet classes based on (i) attributes of UNet architecture and its performance, (ii) explainable AI (XAI), and, (iii) pruning (compression). Five bias methods such as (i) ranking, (ii) radial, (iii) regional area, (iv) PROBAST, and (v) ROBINS-I were applied and compared using a Venn diagram. Vascular and non-vascular UNet systems dominated with sUNet classes with attention. Most of the studies suffered from a low interest in XAI and pruning strategies. None of the UNet models qualified to be bias-free. There is a need to move from paper-to-practice paradigms for clinical evaluation and settings.

Locating fault precisely on power transmission line is highly beneficial to utilities and accurate fault location can expedite the repair of the faulted components, speed-up restoration, and reduce outage time. In this paper, a setting-free double ended fault location method for power transmission line is proposed using both end voltage and current measurements. This algorithm estimates the required setting parameters using pre-fault data and fault location is calculated using estimated parameters and during fault data. The proposed method is verified using the EMTDC simulations for lines connected with conventional and inverter-based renewable resources. The method is not affected by the error in line parameters and renewable integration. The method is implemented in Intelligent Electronic Device (IED) using 1kHz sampling rate and successfully installed on a 400 kV, 233.07 km line from Power Grid Corporation of India (POWERGRID), India and on a 220 kV, 265.6 km line from Svenska Kraftnat (SVK), Sweden. This paper presents laboratory test results as well as field experimental results in which line patrolling crews found the actual location. Pilot installation results match the performance demonstrated with laboratory experimental results. The method gives average fault location error of ~ 0.1 %. The method can locate the fault within two-tower span distance (~300m) which is comparable with traveling wave-based method that requires 1000 times higher sampling rate, high-cost hardware, more complex commissioning, and settings. These geographically diverse pilot installation results stand as testimony to the fault location accuracy of the proposed setting-free fault location solution.

Electric vehicles (EVs) are poised to lead the transportation sector as the primary choice of automobile due to their efficiency and environmental benefits. EVs with enhanced autonomy and reduced pricing have become feasible in the market, enabling a gradual transition for higher EV penetration. However, electric vehicles require highly efficient and stabilized charging stations in urban areas to ensure the vehicle’s charging time is not compromised. In this regard, the Vienna rectifier with a voltage-oriented controller (VOC) plays a significant role in improving the power quality of the utility grid for EV battery charger applications. The low stability of the battery charger’s output voltage and current is due to the trial-and-error method used to select the PI controller gains. In order to improve the voltage and current stability, the particle swarm optimization (PSO) technique is used to optimize VOC’s PI controller gains. The code composer studio (CCS) platform integrates the PSO technique for EV battery chargers in the experimental setup. The Vienna rectifier with VOC for EV battery charger is implemented using TMS 320F28337 digital signal controller in the test board. Findings indicate that the PSO optimized VOC improves the output voltage and current stability by 12% compared to the existing trial-and-error technique. Furthermore, the proposed system is tested in an experimental setup that provides input current THD to less than 5% for different load variations (up to 1.5kW) to meet the IEEE-519 standards. Results from simulations and experimental setup verify that the proposed PSO-PI controller-based Vienna rectifier significantly improves EV battery chargers’ output voltage and current stability.

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a two-layered approach: the first layer formulates the optimization as a generalized convex program, while the second layer solves the optimization decentrally using the alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of the WSEE metric to incorporate heterogeneous EE requirements of users. We show that low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

There is a growing need for stability enhancement in modern electrical networks integrated with wind energy, particularly due to different oscillation modes disturbances. Power system stabilizers (PSSs) are used to mitigate oscillations and improve the stability of the power system. This paper presents a comprehensive analysis of single-band PSS1A and multi-band PSS4C (MB-PSS4C) connected to the ST1A excitation system. An efficient approach in the selection of the parameters of MB-PSS4C using Particle Swarm Optimization (PSO) is proposed. A comparative investigation linked to the common Pattern Search and Simplex Search, from previous work, has been conducted to gauge the efficacy of PSO. The generator’s transient stability with considerations of relative power angle (power angle differences), speed deviation, and active power of synchronous generators (SGs) are analyzed. Different wind penetration levels ranging from 36MW to 108 MW are integrated into the network and are investigated. Results demonstrate that PSO-MB-PSS4C connected to ST1A stabilizes the system effectively with reduced settling time while mitigating the peak power angle differences of SGs. Reduced settling time of 1.35 s is observed for wind penetration of 48 MW, with 43.31° peak power angle; while for high wind penetration of 108 MW, the settling time is around 8 s with peak power angle of 43.9°.

Modern power utilization has been forced to operate close to their stability limits, which may lead to voltage instability or collapse owing to the stressed operating conditions of networks. This raises the need to develop a new technique to predict the level of voltage security under different operating conditions to detect critical lines or buses that operate close to its stability limit. This study proposes a new line voltage stability index (BVSI) to identify weak lines and buses for various loading conditions and network configurations. Comparative studies between the existing voltage stability indices (VSIs) and the proposed index have been performed to comprehensively highlight the indices’ foundation, performance, and overall behavior for several different IEEE benchmark test systems; 14-bus, 30-bus, 118-bus test systems and 33-bus radial distribution system. The sensitivity towards different loading conditions due to variables such as active power, reactive power, angular difference between sending and receiving bus voltage, line resistance, and shunt admittance, which have been neglected in the formulation of VSIs, are briefly discussed. The findings of this work are aimed to provide a general guideline for other researchers in selecting the appropriate VSIs for various applications, particularly in solving optimization problems such as distributed generation (DG) and reactive power compensation (RPC) placement, optimal power flow, optimal reactive power dispatch, optimal network reconfiguration for various loading occasions, and different networks. Lastly, the application of the proposed index has been adopted as an analytical approach for solving optimal location and sizing of DG(s) problems. The results prove the effectiveness of the proposed index in accessing the voltage stability state and stress condition of lines. Besides, the proposed approach also capable of determining the potential candidate bus for single DG location and sizing effectively.

Vienna rectifiers have gained popularity in recent years for AC to DC power conversion for many industrial applications such as welding power supplies, data centers, telecommunication power sources, aircraft systems, and electric vehicle charging stations. The advantages of this converter are low total harmonic distortion (THD), high power density, and high efficiency. Due to the inherent current control loop in the voltage-oriented control strategy proposed in this paper, good steady-state performance and fast transient response can be ensured. The proposed voltage-oriented control of the Vienna rectifier with a PI controller (VOC-VR) has been simulated using MATLAB/Simulink. The simulations indicate that the input current THD of the proposed VOC-VR system was below 3.27% for 650V and 90A output, which is less than 5% to satisfy the IEEE-519 standard. Experimental results from a scaled-down prototype showed that the THD remains below 5% for a wide range of input voltage, output voltage, and loading conditions (up to 2 kW). The results prove that the proposed rectifier system can be applied for high power applications such as DC fast-charging stations and welding power sources.

Two-port equivalent model of the system around a transmission line is commonly used for various line protection related analyses. The main aim of the paper is to present methods that can be adopted in a decentralized manner at the substation level for estimating such an equivalent model. Firstly, the paper contributes to methods for estimation of simple two-source equivalents based on events such as fault on the line or shunt element switching at its terminals. The paper extends a discussion towards limitations of such models in the presence of a transfer path across the line terminals and proposes an extension of the estimation techniques to overcome the issue. Lastly, the paper proposes methods for updating the two-port equivalent model when network topology in the vicinity of the line of concern changes. This contribution differs in the aspect that it only seeks to update the two-port equivalent model, unlike the previous contributions wherein the aim is to estimate the equivalent model without assuming the availability of an initial solution. The methods for updating utilize the equivalent model parameters in a base network scenario and the measurements excited from a topology event. The proposed methods use only limited measurements of bus voltages and line currents, and model parameters of the line of concern and other neighboring apparatus (such as other incident lines or shunt reactors/capacitors). This is an advantage as the availability of the complete network model at any substation is always a challenge. Therefore, the methods can be deployed directly at substations in a decentralized manner. The proposed solutions are computationally easy and amenable for implementation in the framework of digital substations with advanced communication infrastructure. Testing and analysis are done using a simple two source transmission system and the IEEE 39 bus test system.

The paralleling of power converters connected to the grid for power-sharing is a widely used technique. In this context, the design framework for a low-cost, lightweight, compact and high-performance optimum configuration is an open problem. This paper proposes an innovative Multi-Objective Hierarchical Optimization Design Framework (MO-HO-DF) for an AC grid interface with $N$ interleaved H-bridges, each with $M$ parallel “to-be-determined” switches, connected through coupling inductances ($L_f$). A total of eight figures of merit (FOMs) were identified for the design framework optimization. A rigorous model of the power electronic system is presented. Next, a highly computationally efficient algorithm for the estimation of the required frequency modulation ratio ($m_f$) to meet current harmonic performance requirements for any given configuration is proposed. Then, the concept and implementation of the algorithm are presented for the MO-HO-DF. The effectiveness of the design optimization framework is demonstrated by comparing it to a base case solution. Finally, the design calculations are validated via PLECS simulation with manufacturer-provided 3D power semiconductor models that include thermal modelling.

With the modernization of power grids, the network optimal utilization is essential to ensure that voltage profile at each bus is maintained within an acceptable range, voltage stability of the system is enhanced, power losses in lines are minimized, reliability and security of system are improved and etc. These can be achieved by introducing reactive power compensation devices such as Flexible Alternating Current Transmission System (FACTS) devices, Custom Power (CP) devices, synchronous condenser, capacitor bank and etc in distribution or transmission networks. Optimal location and sizing of the reactive power compensation devices are significantly important to ensure sufficient investment onto this device. Recently, most of conducted studies had focused on the techniques for determining the optimal location and sizing of various reactive power compensation devices in the power system using various indices proposed in the literature to access the power loss, voltage stability, voltage profile and line loadability. However, no review paper had discussed on the application of the existing indices adopted in the available techniques for solving the optimal location and sizing problems for all types of reactive power compensation devices. In this paper, current literature survey on optimal location and sizing of reactive power compensations had been discussed which includes analytical, conventional, metaheuristic and hybrid based approaches. The main objectives are to reduce power losses, to mitigate voltage deviations, to increase voltage stability and to improve reliability and security of the system.

Locating fault position in a series compensated transmission line is a difficult task due to the non-linear characteristics of the metal-oxide varistor which is present in the protection system of the compensator. In this paper, a model-free two-terminal traveling wave-based fault location method for a series compensated line is proposed. The technique makes use of two subroutines which calculate the fault locations assuming that the fault position to be on the left and right side of the series compensator respectively. The method then selects the correct fault location of the two by a special logic based on faulted half-section identification. The first two traveling wave arrival times recorded at both the terminals of the line are used in the method. The proposed technique does not require model information of the series capacitor and transmission line. It has been verified using the PSCAD/EMTDC model of a 400-kV, 300 km transmission line which is compensated by a fixed series capacitor in the middle and line ends. The performance of the proposed method is compared with a commercially available classical two-ended techniques and setting-free method.

The integration of network reconfiguration and distributed generation (DG) can enhance the performances of overall networks. Thus, proper sizing and siting of DG need to be determined, otherwise it will cause degradation in system performance. However, determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space. This search space mostly contains non-radial network configurations. Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution. To reduce the searching complexity, this paper considers the discretized network reconfiguration via dataset approach. Water cycle algorithm (WCA) is used to obtain the near optimal solution of network reconfiguration, and sizing and sitting of DG. In addition, the power factor of DG is also optimized to reduce the power loss. The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor. The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima. The proposed method outperforms other technique such as harmony search algorithm (HSA), fireworks algorithm (FWA), Cuckoo search algorithm (CSA) and uniform voltage distribution based constructive algorithm (UVDA) and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20% and 27.88%, respectively.