This paper focuses on investigating the most effective methods for reducing magnet eddy current loss. These techniques were utilised on permanent magnets in a surface-mounted permanent magnet synchronous machine with a distributed winding. Magnet segmentation and optimization of the segmented magnet shape comprise the initial methodology. On the other hand, the second method involves placing a conductive cylinder, known as a shielding cylinder, around the magnets to provide protection. The electromagnetic field analysis and computation of eddy current losses in the studied machine were performed using a two-dimensional finite element method.

The objective of this paper is to examine various methods for reducing eddy current losses in a surface-mounted Permanent Magnet Synchronous Machine (PMSM). The initial phase focuses on reducing the loss of eddy currents in the magnet through magnet segmentation. This technique is frequently employed to enhance the efficiency of Permanent Magnet Synchronous Motors (PMSMs). In this study, the objective is to improve the efficiency of this technique through the appropriate selection of segmentation parameters, specifically focusing on the shape of the segmented magnet. To achieve this, a constrained optimization process based on a genetic algorithm method is employed. Next, the goal is to analyse the eddy current loss, which can be reduced by adding a shielding conductive cylinder around the magnets.

The finite element method was used to analyse the eddy current loss in the machine under consideration.

This research investigates the effectiveness of various chromatic dispersion compensation (CDC) techniques, particularly numerical methods, in a Dual Polarization-Return to Zero-Quadrature Phase Shift Keying (DP-RZ-QPSK) optical transmission system. The primary goal is to evaluate how these techniques can mitigate distance penalties and improve the bit error rate (BER), a critical metric for the reliability of optical communication systems.

The study compares optical and electronic compensation scenarios, analyzing parameters such as launch power, Q factor, and bit error rates. Results indicate that electronic compensation offers superior quality and transmission distance performance. However, it requires a higher launch power (4 dBm) than optical compensation. This trade-off between power consumption and performance must be carefully considered in practical applications.

As symbol rates increase, the study finds that tolerance to chromatic dispersion decreases, leading to a reduction in the quality factor and maximum range. This highlights the importance of developing more advanced CDC techniques to address the challenges posed by higher-speed transmission. Despite these limitations, electronic compensation remains a promising solution for high-speed optical transmission due to its flexibility and adaptability.

The study concludes that the maximum reach achievable with electronic compensation is 4000 km at a 12 dB Q factor. This result demonstrates the potential of electronic CDC to enable long-haul optical communication systems with high data rates. However, further research is needed to explore the limitations of electronic compensation and develop more efficient and power-efficient algorithms.

Long wavelength semiconductor lasers, such as InGaAsP/InP lasers emitting at 1.3 and 1.55 mm, are widely used as light sources in optical communication systems. The dynamical behavior of semiconductor lasers is significantly influenced by optical feedback from an external reflector. To achieve the highest static and dynamic performance in semiconductor lasers, it is essential to thoroughly grasp how the strength of optical feedback affects their stability. This knowledge is fundamental for creating innovative designs that meet advanced performance standards. In this work, the instability of semiconductor lasers with external cavities in terms of noise and photon number probability distributions is investigated for the first time over a wide range of optical feedback. We successfully numerically solved improved time-delay rate equations across various optical feedback strengths [1,2]. Our analysis will classify the laser's dynamics based on detailed bifurcation diagrams of the photon number, providing valuable insights into its behavior. The study analyzes the temporal trajectory of photon numbers and intensity noise and statistically examines variations in output photon number fluctuations, probability distributions, and corresponding intensity noise at different optical feedback strengths. The simulations indicate that optical feedback strength significantly affects the intensity noise and photon number probability distributions. Intensity noise is reduced at relatively weak and strong optical feedback regimes. The shape of the photon number probability distributions is strongly influenced by optical feedback strength, transitioning from symmetric to asymmetric at weak to strong optical feedback, respectively. In the moderate optical feedback range (chaotic region), the photon number probability distributions exhibit a peak at low intensity and tail off at several times the average photon number. The authors suggest that operating semiconductor lasers under weak or strong optical feedback regimes may reduce their instability.

The smart home culture is widely spread across the world by transforming traditional homes into smart homes with technological advancements. In addition, the consumers are becoming prosumers by adding renewable energy namely solar, wind, etc., to their homes along with traditional energy sources. However, intermittent weather conditions impact the power generation of renewable sources. Hence, there is a need to understand the correlation between several weather parameters and power generation. Traditional statistical methods such as Pearson and Spearman’s, Kendall’s Tau, and Phi correlation coefficients are available but are limited to only two variables. Instead, multiple linear regression (MLR) offers multivariate analysis. Thus, this paper employs MLR to analyze the correlation between weather conditions such as temperature, apparent temperature, visibility, humidity, pressure, wind speed, dew point, and precipitation, and the power generation in kW. All the weather conditions are independent variables, and the generated power is a dependent variable. The key objective is to investigate the significant predictors and their impact on power generation. To implement this, a recent smart home dataset titled “Smart Home Dataset with Weather Information” that gives the required information is downloaded from Kaggle. This dataset contains 32 columns and 503,910 observations. The whole dataset is considered for implementing the proposed correlation analysis. A regression model is developed to find the correlation between the above-mentioned parameters in the dataset, and the multicollinearity between the independent variables is presented using the variance inflation factor (VIF). If the VIF value is greater than 10, it represents high multicollinearity. The results showcase that the variables such as temperature, humidity, apparent temperature, and dew point have VIF values of 298.96, 37.54, 126.86, and 152.95, respectively, and are thereby considered critical weather parameters that significantly influence solar energy generation. This aids in better planning of generation and load management in smart homes.

In this paper, we investigate the application of the Manta Ray Foraging Optimization (MRFO) metaheuristic algorithm for optimizing routing protocols within Mobile Ad Hoc Networks (MANETs). MANETs are decentralized wireless networks consisting of mobile nodes that establish temporary connections independently of any pre-existing infrastructure. Routing protocols, a critical component of MANETs, consist of rules and algorithms that manage the forwarding of data packets across the network. We propose an improved routing protocol based on MRFO, named MantaNet, to identify optimal routes for data transmission. Simulations were conducted using MATLAB software to design a dynamic network comprising nodes moving within a defined zone. The optimization problem focuses on minimizing the distance traversed by data from the sender to receiver, thereby reducing energy consumption, overload, and congestion. The MantaNet algorithm begins with a random initialization of candidate routes, which are then evaluated using a fitness function. The MRFO updating processes are applied to refine the search through multiple iterations. To assess the performance of the MantaNet approach, we conducted several simulations, varying the distance between the sender and receiver, the number of nodes, the candidate solutions, and the iterations. The results demonstrate that the proposed MantaNet algorithm consistently identifies optimal routes across various network sizes and scales. The algorithm maintains strong performance even with a small number of candidate solutions and iterations, thereby reducing computational time. Overall, the MantaNet routing method offers a promising solution for efficient data transmission in MANETs.

The integration of High Voltage Direct Current (HVDC) technology into power systems has emerged as a pivotal solution for enhancing the efficiency and reliability of long-distance energy transmission. This study investigates the implementation of HVDC technology within the Algerian power system, utilizing the Power System Analysis Toolbox (PSAT) to simulate its impact on power flow and voltage profiles. The Algerian power system, characterized by its extensive geographical spread and varying energy demand across regions, presents unique challenges for energy transmission, especially from renewable sources located in remote areas. By incorporating HVDC links into the system, we aimed to address these challenges, focusing on improvements in the active power distribution and voltage stability across the network. The simulation results indicate a significant enhancement in the voltage profiles of various bus bars, which previously fell below acceptable limits. The implementation of HVDC not only brought these within the 10% voltage stability margin but also optimized the active power distribution throughout the system. These findings under score the potential of HVDC technology in bolstering the Algerian power system's capacity for efficient, reliable energy transmission over long distances, providing a valuable frame work for future infra-structure development and policy formulation aimed at sustainable energy growth.

In our study, we investigated how the strength of optical feedback and the non-radiative recombination rate impact a laser diode's dynamics and phase noise. To analyze laser dynamics, we solved numerically improved time-delay rate equations across a wide range of optical feedback strength and non-radiative recombination rates. The laser's dynamics will be categorized based on the bifurcation diagrams of the photon number. Our findings show that the non-radiative recombination rate has a significant effect on the intensity, states, and dynamic behavior of the laser diode's phase noise. A decrease in the non-radiative recombination rate results in the laser transitioning faster from a continuous wave to periodic oscillation under strong optical feedback. In the chaotic region, the non-radiative recombination rate causes a slight shift in the phase fluctuations compared to the laser operating without optical feedback. Lower non-radiative recombination rates stabilize the laser output and enable continuous wave or periodic oscillation at higher current levels. In the strong optical feedback region, a reduction in the non-radiative recombination rates shifts the chaotic operation to stable modes such as a continuous wave or periodic oscillation, and the phase noise approaches the quantum noise level. Our study emphasizes the key roles of the non-radiative rate and optical feedback in manipulating the dynamics and phase noise of a laser diode. We have shown that losses due to non-radiative rates could be practically useful for engineering laser behaviors. The strength of optical feedback can be adjusted to achieve the optimal goals of stabilizing laser operation. Our work is driven by the ongoing interest in finding effective ways to control and optimize the output of a laser diode. We believe that our findings may have potential applications in future experimental design and optimization, which will be of general interest to the community studying solid-state semiconductor laser diodes.

This paper introduces a method for reducing the conservatism in Takagi–Sugeno (TS) fuzzy systems through the use of a non-quadratic Lyapunov function (NQLF), also known as the line integral Lyapunov fuzzy function. By leveraging this function in combination with an efficient methodological approach, the stability analysis of TS systems is significantly improved. The stability conditions for these systems are initially formulated as Bilinear Matrix Inequalities (BMIs), which present a challenge due to their nonlinear nature and computational complexity. To address this difficulty, we propose an iterative algorithm designed to transform the BMI problem into a more tractable form by converting it into a set of Linear Matrix Inequalities (LMIs). LMIs are easier to solve using established optimization techniques, thereby simplifying the stability analysis process without sacrificing its accuracy. This transformation allows for more efficient computation and reduces the conservatism typically associated with BMI-based methods. To validate the effectiveness of our approach, a numerical example is provided, demonstrating how the proposed method outperforms traditional approaches by offering an enhanced stability analysis. The example illustrates the reduction in conservatism, thereby highlighting the practicality and robustness of the approach. Overall, this method offers a promising solution for improving the stability analysis of TS fuzzy systems by reducing the complexity and providing more reliable results. This contribution underscores the potential of using non-quadratic Lyapunov functions to address challenges in system stability with increased computational efficiency.

Abstract :This paper analyses the Interleaving technique applied to Boost DC-DC Converter. It is achieved by interconnection of multiple switching cells in series with diode and parallel with inductors, hence it will increase the effective pulse frequency by synchronizing several smaller sources and operating them with relative phase shift. Energy can be saved and power conversion can be increased without affecting conversion efficiency by interleaving technique. In this , two phases are used and three devices are connected per phase, three phases are used and two devices are connected per phase. The converters are tested at constant input voltage and variable duty cycle using simulation by Matlab/simulink. The ripple content of the output voltage and input current of the converter are obtained from design calculation and compared with simulated results

Introduction: With the increased need of renewable energy sources and energy storage, high-voltage-gain dc–dc power electronic converters used in green energy systems.The step-up converter provides low current ripple, high efficiency.

Methods & Results: The Multi device interleaved boost dc-dc converters are tested by simulation at duty cycle of 0.25 and 0.375 respectively . These duty cycles are selected based on the output voltage (Vo). Considering Vo is known. Fixed as 200V for both the converters

Conclusion: These Converters are analyzed, designed and simulated. Two Phase Three Device per phase boost dc-dc Converter provides 87.9 % of efficiency of power and provides ripple of 0.0106 % volts of output voltage .Three Phase Two Device per phase boost dc-dc Converter provides 92.8 % of efficiency of power provides ripple of 0.125 % volts of output voltage. By comparing these, Two phase Three Device Converters provides Low Output Voltage gain, Low efficiency of Power, Low Ripple Output Voltage and Three phase Two device Converter provides High Output Voltage gain, High efficiency of Power, High Ripple Output Voltage.

The increasing adoption of solar photovoltaic (PV) systems as a renewable energy source is driven by their ability to provide clean, sustainable power. However, dust accumulation on solar panels significantly impacts their efficiency by reducing the amount of sunlight reaching the photovoltaic cells, leading to a decrease in energy output. This project aims to develop an automated cleaning system to address the efficiency losses caused by soiling on solar PV panels. The system employs a rotating brush mechanism driven by a DC motor and controlled by an Arduino microcontroller, which automates the cleaning process while minimizing water usage and manual intervention. The experimental results demonstrate that the automated cleaning system can restore solar panel efficiency by up to 18% under optimal conditions, thereby enhancing power output and reducing the operational costs associated with manual cleaning. This improvement not only increases energy yield but also extends the operational life of the solar PV systems by preventing potential damage caused by dirt buildup. The system’s cost-effectiveness, scalability, and reduced reliance on manual labor make it particularly suitable for large-scale solar installations where regular cleaning is both labor-intensive and hazardous. Moreover, this work highlights the importance of optimizing water usage in the cleaning process, making the system more sustainable, especially in arid regions. By focusing on a dry-brush mechanism, the design minimizes water consumption while maintaining effective cleaning performance. This study's findings underscore the importance of regular, efficient, and cost-effective cleaning methods to maintain solar PV system performance.