Search Results (1,518)

A new energy storage unit, which is fed by a piezoelectric wind energy harvester, is explored. The outputs of a three-phase piezoelectric wind energy device have been initially recorded from the laboratory experiments. Following the records of voltage outputs, the power ranges of the device were measured at several hundred microwatts. The main issue of piezoelectric voltage generation is that voltage waveforms of piezoelectric materials have high total harmonic distortion (THD) with incredibly high subharmonics and superharmonics. Therefore, such a material reply causes a certain power loss at the output of the wind energy generator. In order to fix this problem, we propose a combination of a rectifier and a storage system, where they can operate compatibly under high THD rates (i.e., 125%). Due to high THD values, current–voltage characteristics are not linear-dependent; indeed, because of capacitive effect of the piezoelectric (i.e., lead zirconium titanite) material, harvested power from the material is reduced by nearly a factor of 20% in the output. That also negatively affects the storage on the Li-based battery. In order to compensate, the output waveform of the device, the waveforms, which are received from the energy-harvester device, are first rectified by a full-wave rectifier that has a maximum power point tracking (MPPT) unit. The SOC values prove that almost 40% of the charge is stored in 1.2 s under moderate wind speeds, such as 6.1 m/s. To conclude, a better harvesting performance has been obtained by storing the energy into the Li-ion battery under a current–voltage-controlled boost converter technique. Full article

Light-emitting diodes (LEDs) have gained widespread adoption as solid-state lighting sources due to their compact size, long operational lifetime, high brightness, and mechanical robustness. This paper presents the development and implementation of an isolated AC-DC LED electronic lighting driver circuit that integrates a modified flyback converter with a lossless snubber circuit, along with inherent power factor correction (PFC). The proposed design operates the transformer’s magnetizing inductor in the discontinuous conduction mode (DCM), thereby naturally achieving PFC without the need for complex control circuitry. Furthermore, the circuit is capable of recycling the energy stored in the transformer’s leakage inductance, improving overall efficiency. The input current harmonics are shown to comply with the IEC 61000-3-2 Class C standard. A 72 W (36 V/2 A) prototype has been constructed and tested under a 110 V AC input. Experimental results confirm the effectiveness of the proposed design, achieving a power factor of 0.9816, a total harmonic distortion (THD) of 12.094%, an output voltage ripple factor of 9.7%, and an output current ripple factor of 11.22%. These results validate the performance and practical viability of the proposed LED driver architecture. Full article

In coastal hot and humid regions, the steel pin of AC porcelain insulators often suffers from severe electrochemical corrosion due to surface contamination and moisture, leading to insulator string breakage. Contrary to the common belief that AC corrosion is negligible, this study reveals the significant role of the DC component in leakage currents and the synergy of this DC component with localized high current densities in accelerating corrosion, based on field investigations and experiments. Using a simulation model based on the Suwarno equivalent circuit, it is shown that non-linear contamination causes highly non-sinusoidal leakage currents, with total harmonic distortion up to 40% and a DC component of approximately 22%. To mitigate this, a conductive silicone rubber coating is proposed to block moisture and distribute leakage current evenly, keeping surface current density below the critical threshold of 100 A/m². Simulations indicate that a 2 mm thick coating with conductivity around 10⁻⁴ S/m effectively reduces current density to a safe level. Accelerated corrosion tests confirm that this conductive coating significantly suppresses pitting corrosion caused by high current densities, outperforming traditional insulating coatings. This study presents a practical and effective approach for protecting AC insulators in harsh environments, contributing to improved transmission line reliability in high-temperature and high-humidity regions. Full article

This study presents a comparative analysis of efficiency and harmonic generation in Triple Active Bridge (TAB) converters under two operating configurations: Case I, with one input source and two loads, and Case II, with two input sources and one load. Two modulation strategies, Single-Phase Shift (SPS) and Dual-Phase Shift (DPS), are evaluated through frequency-domain modeling and simulations performed in MATLAB/Simulink. The analysis is complemented by experimental validation on a laboratory prototype. The results show that DPS reduces harmonic amplitudes, decreases conduction losses, and improves output waveform quality, leading to higher efficiency compared to SPS. Harmonic current spectra and total harmonic distortion (THD) are analyzed to quantify the impact of each modulation method. The findings highlight that DPS is more suitable for applications requiring stable power transfer and improved efficiency, such as renewable energy systems, electric vehicles, and multi-source DC microgrids. Full article

This paper proposes an enhanced Model Predictive Direct Speed Control (MPDSC) framework for Permanent Magnet Synchronous Motor (PMSM) drives, integrating duty ratio optimization and load torque disturbance compensation to significantly improve both transient and steady-state performance. Traditional finite-control-set MPC strategies, which apply a single voltage vector per sampling interval, often suffer from steady-state ripples, elevated total harmonic distortion (THD), and high computational complexity due to exhaustive switching evaluations. The proposed approach addresses these limitations through a novel dual-stage cost function structure: the first cost function optimizes dynamic response via predictive control of speed error, while the second adaptively minimizes torque ripple and harmonic distortion by adjusting the active–zero voltage vector duty ratio without the need for manual weight tuning. Robustness against time-varying disturbances is further enhanced by integrating a real-time load torque observer into the control loop. The scheme is validated through both MATLAB/Simulink R2020a simulations and real-time experimental testing on a dSPACE 1202 rapid control prototyping platform across small- and large-scale PMSM configurations. Experimental results confirm that the proposed controller achieves a transient speed deviation of just 0.004%, a steady-state ripple of 0.01 rpm, and torque ripple as low as 0.0124 Nm, with THD reduced to approximately 5.5%. The duty ratio-based predictive modulation ensures faster settling time, improved current quality, and greater immunity to load torque disturbances compared to recent duty-ratio MPC implementations. These findings highlight the proposed DR-MPDSC as a computationally efficient and experimentally validated solution for next-generation PMSM drive systems in automotive and industrial domains. Full article

Climate change is transforming energy use at the residential level by increasing temperature fluctuations and sustaining extreme weather events. This study proposes a climate-reactive, multi-objective approach to integrate the demand response (DR) with distributed generation (DG) and power quality improvement under a multi-objective framework of an integrated climate-adaptive approach to residential energy management. A cognitive neural network combination model with bidirectional long short-term memory networks (bidirectional) and a self-attention mechanism was used to successfully predict temperature-sensitive loads. The hybrid deep learning solution, which applies convolutional and bidirectional long short-term memory (LSTM) networks with attention, predicted the temperature-dependent load profiles optimized with an enhanced modified grey wolf optimizer (MGWO). The results of the experimental studies indicated significant gains in performance: in energy expenditure, the studies reduced it by 32.7%; in peak demand, they were able to reduce it by 45.2%; and in self-generated renewable energy, the results were 28.9% higher. The solution reliability rate provided by the MGWO was 94.5%, and it converged more quickly, thus providing better diversity in the Pareto-optimal frontier than that of traditional metaheuristic algorithms. Sensitivity tests with climate conditions of +2 °C and +4 °C showed strategy changes as high as 18.3%, thus establishing the flexibility of the system. Empirical evidence indicates that the energy and peak demand are to be cut, renewable integration is enhanced, and performance is strong in fluctuating climate conditions, highlighting the adaptability of the system to future resilient smart homes. Full article

This paper presents an improved structure of an asymmetrical single-phase multilevel inverter topology with reduced device count. The proposed topology achieves 19 voltage levels at the output using only 12 power switches and 3 DC sources. The topology can be easily extended, resulting in a modular topology with more voltage levels at higher voltages. Moreover, the reliability analysis of the proposed converter results in a higher mean time to fault. The simulation is performed in MATLAB/Simulink, and a hardware prototype is developed to validate the circuit’s performance. A low-frequency Nearest Level Control PWM technique is implemented to generate switching signals and achieves 4.30% THD in output voltage. The PLECS software is used for power loss and efficiency analysis, resulting in a maximum efficiency of 99.08%. The proposed converter has been compared with other MLI topologies to demonstrate its superiority. The results indicate that the proposed topology has proven superior and outperformed other topologies in various parameters, making it suitable for renewable energy applications. Full article

In the current energy landscape, power quality (PQ) emerges as a critical concern. Even when there is no fault on a line, PQ issues are common in all power networks since 90% of power systems’ loads are variable or inductive in nature. Variable loads cannot be avoided; hence, PQ concerns such as voltage swelling and sag will always arise. Voltage sag is one of the main issues within a distribution network, resulting in financial losses for the utility company and the customer. The Dynamic Voltage Restorer (DVR) effectively addresses voltage sags and minimizes total harmonic distortion (THD) in the distribution network. This paper proposed a novel control strategy to increase the PQ in a system. A Frilled Lizard Optimization-optimized fuzzy PI controller is proposed in this work to control the inverter. This proposed method improves the DVR’s ability to correct voltage sag and reduce total harmonic distortion as soon as possible. The PI control scheme is utilized initially to reduce the oscillations and remove the steady-state error. To increase the tendency rate of the error to zero, the PI method is applied to a fuzzy logic-based compensatory stage. The proposed approach is validated using pro-type models, as well as mathematical and Simulink modelling. In the Results Section, the performance of the proposed controllers with the DVR is tabulated and compared with other DVR controller schemes described in other research papers. Full article

To address the challenges posed by harmonic distortion and DC offset in the power grid, this paper proposes a novel Phase-Locked Loop (PLL) architecture tailored for single-phase grid-connected systems. The design integrates an Enhanced Adaptive Second-Order Generalized Integrator (EA-SOGI) with a Quasi-Proportional Resonant (QPR) controller. The proposed EA-SOGI extends the conventional SOGI by incorporating an all-pass filter and an additional integrator, which enhance the symmetry of the orthogonal signals and effectively suppress the estimation errors caused by DC offset. In addition, the conventional PI controller is replaced by a QPR controller, whose parameters are tuned using a hybrid Levy-AsyLnCPSO optimization algorithm to improve frequency locking performance and enhance system robustness under steady-state conditions. Simulation and experimental results demonstrate that the proposed PLL achieves a Total Harmonic Distortion (THD) as low as 2.8653% based on Fast Fourier Transform (FFT) analysis, indicating superior adaptability compared to conventional PLL structures and validating its effectiveness in DC offset suppression and harmonic mitigation. Full article

The adoption of synchronous optimal pulse-width modulation (SOPWM) in two-level voltage-source inverters (2L-VSIs) offers low switching-to-fundamental-frequency ratio (SFR) operation while maintaining reduced current total harmonic distortion (THD). Despite these advantages, the performance of SOPWM is highly sensitive to signal noise in the modulation index and reference voltage angle. To prevent degradation, conventional PI controllers are conservatively tuned with slow dynamic response, which limits overall system performance. Finite control set model predictive control (FCS-MPC) integrated with SOPWM offers a promising solution, combining the fast dynamic response of FCS-MPC with the optimal steady-state performance of SOPWM. Nevertheless, the intricate tuning of weighting factors in FCS-MPC presents a significant challenge, particularly in balancing between enhanced harmonic performance and fast dynamic response. This paper introduces a simplified FCS-MPC approach that eliminates the need for complex weighting factor tuning while retaining the excellent dynamic performance of FCS-MPC and ensuring the low current THD achieved by SOPWM under steady-state conditions. The efficacy of the proposed method is validated through MATLAB/Simulink (R2023b) simulations and experimental results. Full article

The quality of electrical energy in mining plants is still a topic that is not directly linked to occupational safety and the efficiency of the mining process. Modernisation of hoisting machines should be carried out, taking into account the impact of such a drive on the mine’s power grid. A hoisting machine is one of the largest consumers of electricity in this grid and, as such, can pose a real threat to its proper functioning. The aim of the study was to determine the impact of the hoisting machine drive system on the mine network after a thorough modernisation process. Measurements were taken before and after the process. The assessment was carried out in two aspects, i.e., the measurement results obtained after the modernisation were compared with the applicable regulations. The second approach was to compare the results before and after modernisation. In the authors’ opinion, this second approach is a way of preventing potential phenomena that may occur in the network as a result of the operation of the power electronic system and should complement the analysis described in the regulations. The assessment of the current operation of the system in relation to the previous one makes it possible to evaluate the correctness of the solution applied and may provide guidelines for further steps in the event of a failure or unsafe events. Full article

The evaluation and enhancement of image aesthetics play a pivotal role in the development of visual media, impacting fields including photography, design, and computer vision. Composition, a key factor shaping visual aesthetics, significantly influences an image’s vividness and expressiveness. However, existing image optimization methods face practical challenges: compression-induced distortion, imprecise object extraction, and cropping-caused unnatural proportions or content loss. To tackle these issues, this paper proposes an image aesthetic evaluation with composition and similarity (IACS) method that harmonizes composition aesthetics and image similarity through a unified function. When evaluating composition aesthetics, the method calculates the distance between the main semantic line (or salient object) and the nearest rule-of-thirds line or central line. For images featuring prominent semantic lines, a modified Hough transform is utilized to detect the main semantic line, while for images containing salient objects, a salient object detection method based on luminance channel salience features (LCSF) is applied to determine the salient object region. In evaluating similarity, edge similarity measured by the Canny operator is combined with the structural similarity index (SSIM). Furthermore, we introduce a Framework for Image Aesthetic Evaluation with Composition and Similarity-Based Optimization (FIACSO), which uses semantic segmentation and generative adversarial networks (GANs) to optimize composition while preserving the original content. Compared with prior approaches, the proposed method improves both the aesthetic appeal and fidelity of optimized images. Subjective evaluation involving 30 participants further confirms that FIACSO outperforms existing methods in overall aesthetics, compositional harmony, and content integrity. Beyond methodological contributions, this study also offers practical value: it supports photographers in refining image composition without losing context, assists designers in creating balanced layouts with minimal distortion, and provides computational tools to enhance the efficiency and quality of visual media production. Full article

Ripples in the electromagnetic torque of electric vehicle (EV) motors due to poor stator voltage and control cause jerky movements, equipment failure, discomfort for passengers and drivers, and damage to the associated civil works. This paper presents the implementation of Finite Control Set Model Predictive Control (FCSMPC) for a high-level modified W-type inverter (MWI) driving a three-phase induction motor (IM), along with validation of its performance. The proposed control strategy aims to minimize motor torque ripples and has been tested under various driving torque patterns. The results demonstrate a significant reduction in torque ripples—down to less than 1%—and acceptable levels of total harmonic distortion (THD), as verified through quality analysis of the stator currents. Moreover, a comparative assessment of voltage profiles for the electromagnetic torque and rotor speed curves has been presented for nine cases of simultaneous variations in multiple motor parameters; the results indicate that the MWI-fed motor has the best performance and the lowest sensitivity to the variations. Full article

Battery Energy Storage Systems (BESSs) are critical to smart grid functioning but are exposed to mounting cybersecurity threats with their integration into IoT and cloud-based control systems. Current solutions tend to be deficient in proper multi-class attack classification, secure encryption, and full integrity and power quality features. This paper proposes a comprehensive framework that integrates machine learning for attack detection, cryptographic security, data validation, and power quality control. With the BESS-Set dataset for binary classification, Random Forest achieves more than 98.50% accuracy, while LightGBM attains more than 97.60% accuracy for multi-class classification on the resampled data. Principal Component Analysis and feature importance show vital indicators such as State of Charge and battery power. Secure communication is implemented using Elliptic Curve Cryptography and a hybrid Blowfish–RSA encryption method. Data integrity is ensured through applying anomaly detection using Z-scores and redundancy testing, and IEEE 519-2022 power quality compliance is ensured by adaptive filtering and harmonic analysis. Real-time feasibility is demonstrated through hardware implementation on a PYNQ board, thus making this framework a stable and feasible option for BESS security in smart grids. Full article

Clinical application of AI/DL-aided acquisitions for quantitative bi-parametric (q-bp)MRI requires validation and harmonization across vendor platforms. An AI/DL-accelerated q-bpMRI, including 5-echo T₂ and 4-b-value apparent diffusion coefficient (ADC) mapping, was implemented on two 3T clinical scanners by two vendors alongside the qualitative standard-of-care (SOC) MRI protocols for six patients with biopsy-confirmed prostate cancer (PCa). AI/DL versus SOC bpMRI image quality was compared for MR-visible PCa lesions on a 4-point Likert-like scale. Quantitative validation and protocol bias assessment were performed using a multiparametric phantom with reference T₂ and diffusion kurtosis values mimicking prostate tissue ranges. Six-minute q-bpMRI achieved acceptable diagnostic quality comparable to the SOC. Better SNR was observed for DL/AI versus SOC ADC with method-dependent distortion susceptibility and resolution enhancement. The measured biases were unaffected by AI/DL reconstruction and related to acquisition protocol parameters: constant for spin-echo T₂ (−7 ms to +5 ms) and ADC (4b-fit: −0.37 µm²/ms and 2b-fit: −0.19 µm²/ms), while nonlinear for echo-planar T₂ (−37 ms to +14 ms). Measured phantom ADC bias dependence on b-value range was consistent with that observed for PCa lesions. Bias correction harmonized lesion T₂ and ADC values across different AI/DL-aided q-bpMRI acquisitions. The developed workflow enables harmonization of AI/DL-accelerated quantitative T₂ and ADC mapping in multi-vendor clinical settings. Full article