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An active magnetic bearing (AMB) is an evolving research topic in the bearing industry. Compared to the conventional approach, AMB is more advantageous and has different industrial applications. The design of this bearing needs to be improvised to get more optimized performance. This leads us to focus on the better-designed structure of the actuator, which plays an essential role in AMB performance. Thus in this manuscript, we have designed and compared the I-type and U-type actuators’ performances in terms of their resistance, inductance profile, and force profile to show the characteristics of these actuators. These designed actuators are simulated in Ansys Maxwell software, and compared with the simulation results. Further, these results are verified using hardware results, and the tested actuators are used to design two different AMB systems. One current controller is designed and simulated to achieve the stable levitated position of the rotor. This rotor is rotated by inserting an AC magnet in the system and finally, a rotational system is attained, and its speed is observed by the tachometer for both AMB systems. Both the proposed AMB systems are simple and compact in structure as these are having single coil and single power amplifier. These axial AMB systems are used in many high-speed applications as they are having features like less installation space, less cost and more room for heat dissipation.

This paper suggests an alternate level enhancing algorithm to operate the nine-level cascaded multilevel inverter (CHBMLI) for a 31-level output, which involves an inventive selection of optimal asymmetrical voltage values in separate DC sources (SDCs) and a quarter-wave symmetry pulse pattern pulse width modulation (QSP-PWM). The symmetrical CHBMLI structure involves the same DCs with an objectionable value of component count, especially at higher level outputs; consequently, there is a need to reduce the component count. It can be supported largely by the optimal set of asymmetrical voltage values (say 1:2:4:8), such an actualization is quite easy with photovoltaic (PV) applications. Additionally, many of the commonly used PWM methods of MLI are tedious especially when it comes to the generation of pulses. This paper also engraves a straightforward switching strategy apposite to the developed MLI topology. In addition, three new switching angle modulation schemes have been proposed to get the optimum performance, namely, incremental delay switching angle modulation scheme, random delay switching angle modulation scheme and sine referencing-based switching angle modulation scheme. The preliminary study on the tenet of suggested topology is done theoretically, then the performance is analyzed in MATLAB2019a software and finally, experimentally corroborated on a proof-of-concept (POC) prototype with the aid of ModelSim6.3f hardware description language simulation environment, Xilinx 14.5 project navigator tool and XC3S500E field-programmable-gate-array processor. The tested results for the inductive load demonstrate the output voltage synthesizing and the total harmonic distortion curtailment savvies of the proposed MLI and the switching strategies.

Due to the intermittent and hazardous nature of lightning impulse, researchers rely on artificial impulse generators to study it. The Tesla coil is a commonly used device to generate artificial lightning. This paper presents a parametric analysis of the primary side coil of the Tesla transformer. The analysis employs seven key electrical properties: skin depth, current density, voltage distribution, Ohmic loss, electric field strength, charge density, and energy content. These parameters are used to evaluate the response of various coil types to high voltage impulses. The Ansys high-frequency electromagnetic solver is used to perform a comparative analysis of essential parameters. The results can aid lightning researchers and Tesla coil designers in determining the optimal designs for Tesla primary coils in the future. The analyzed data is validated using Tesla coil hardware, which is used as an artificial lightning producer to test the feasibility of a lightning energy harvester.

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain parameters of PID controller for the proposed closed-loop active magnetic bearing (AMB) system. Performance indices or, objective functions on which these optimization techniques are executed are integral absolute error (IAE), integral square error (ISE), integral time multiplied absolute error (ITAE), and integral time multiplied square error (ITSE). The significance of an optimization technique and objective function can obtain only by implementing it. As a result, several comparisons are made based on statistical performance, time domain, frequency response behavior, and algorithm execution time. Finally, the applicability of optimization strategies in addition to the performance indices is determined with the aid of the comparative analysis. That could assist in choosing a suitable optimization technique along with a performance index for a high-speed application of an active magnetic bearing system.

Partial shading (PS) phenomena significantly degrade the power output from the photovoltaic (PV) array. Due to the PS effect, there is a mismatch in current between the PV modules of a series-connected PV string. As a result, in-shaded module power dissipates, resulting in increased module temperature and the creation of local hotspots. To avoid the hotspot effect, bypass diodes are connected anti-parallel to the PV modules. But the activation of bypass diodes creates multiple peaks in I-V and P-V characteristics. The effect of PS can be reduced by using a suitable array configuration and the performance of the PV array gets improved. Among all the existing PV array configurations, the total cross-tied (TCT) configuration performs better under partial shading conditions (PSCs). But the disadvantage of TCT is that it has an enormous number of tie connections, creating complexity in an array configuration and, therefore, more cable losses. The main objective of this paper is to propose a novel array configuration named benzene (BZ) configuration, which eliminates the demerits of the TCT array configuration. Benzene configuration has improved performance with fewer tie connections compared to conventional tie-connected configurations such as TCT, bridge link (BL), and honeycomb (HC). The performance of the tie-connected array configurations is analyzed under different PSCs by considering the various performance parameters such as global maximum power (GMP), the voltage at maximum power (Vmp), current at maximum power (Imp), mismatch loss (ML), shading loss (SL), fill factor (FF) and performance ratio. It is observed that the proposed benzene array configuration gives better output performance, even having lower mismatch losses with a reduced amount of tie connections. Further, the effect of the bypass diode on a partially shaded PV string is investigated through MATLAB Simulation and experimental analysis.

The performance of the solar photovoltaic system is affected by the unpredictable phenomenon of partial shading. This causes the mismatch losses that suppress the power generation of healthy PV modules in it. The objective of the proposed work in this paper is to bring out the maximum power from each PV module in the PV array by reducing the mismatch losses. A new array configuration method is proposed in this paper, which follows the screw pattern in the row formation. Each PV row is created with distinct PV modules from the rows of the conventional array configuration. This proposed work allows the PV system to operate with minimum mismatch losses by even shade dispersion over the PV array. The proper mathematical expression with all necessary constraints was derived for the array formation of the proposed work. The output analysis is been validated in the simulation of the $9\times 9$ PV array in MATLAB/Simulink Ⓡ. The mismatch loss generation and output power enhancement are measured and compared with the various conventional array configuration methods under six kinds of partial shading patterns. The proposed array configuration is 40% more efficient than the conventional series-parallel array configuration and also performs better than the total cross-tied and sudoku puzzle pattern methods. The shade dispersion rate of the proposed array configuration has highly reduced the mismatch losses in the PV system and hence, it improves the power output.

Power conversion efficiency is the most important factor to be considered in PV systems because it is affected by various environmental conditions. The effect of partial shading is the most influenced factor in the reduction of power output. Various research schemes like Maximum Power Point Tracking (MPPT), array configuration scheme, reconfiguration, etc., work on the PV system to reduce the impact of partial shading. This paper presents a new kind of array configuration scheme that forms the PV array based on the moves of the Knight coin in the chess game. This arrangement creates the squared PV array of rows with distinct PV modules which is capable of evenly dispersing the shading in the partially shaded PV array. Also, this scheme is applicable for the non-squared PV arrays to create PV rows with the PV modules from a distinct location or from the same row with optimized distance to disperse the maximum level of shading. The proposed method has been discussed with the proper mathematical formulation with all necessary constraints and also it been validated with the hardware arrangements and MATLAB/Simulink® model.

Multiport converters play a significant role in portable electronic and electric vehicle (EV) applications. In literature, different configurations of single-input multi-output (SIMO) converters are presented. Most of the SIMO converters generate the outputs with operating constraints on the duty ratio and charging of inductors. The cross-regulation problem is still a challenge in SIMO converters design. A SIMO topology is proposed in this study to overcome the limitations mentioned earlier. It can generate three different output voltages without constraint on the duty cycle and inductor currents (like $i_{L1} > i_{L2} > i_{L3} $ or $i_{L1} < i_{L2} < i_{L3}$ ). Cross regulation problems do not exist in the proposed topology, so the load voltage $V_{01}$ ( $V_{02}$ ) ( $V_{03}$ ) is not affected by the variation of output current $i_{03}$ ( $i_{02}$ ) ( $i_{01}$ ). The loads are isolated from each other during control. In the laboratory, a 200 W prototype circuit is developed; simulation and experimental results are validated.

This paper proposes a closed-loop and implements some metaheuristic optimization approaches to regulate an unstable active magnetic bearing (AMB) system. First of all, a hardware model of an AMB is fabricated in the laboratory. Mathematical analysis is carried out and a linearized open-loop transfer function is obtained for an equilibrium point of operation, using the parameters of the hardware model. Then, a closed loop is proposed for this AMB system, which comprises a PID controller, power amplifier, and position sensor. Further, three different metaheuristic nature-inspired hunting-based optimization algorithms i.e., Ant lion optimization (ALO), Grey wolf optimization (GWO), and Whale optimization algorithm (WOA) are implemented individually to calculate the gain parameters of the PID controller. Separately, the performance of these optimization algorithms is evaluated and observed on four different performance indices: integral of absolute error (IAE), integral of squared error (ISE), and an integral of time multiplied absolute error (ITAE) and integral of time multiplied squared error (ITSE). For a stable, efficient, and reliable bearing operation, it is vital to perform an analysis of the performance of optimization techniques with different objective functions for the proposed system. Therefore, few comparisons are conducted, first based on data obtained from statistical analysis. The second is based on data obtained from transient state performance and phase margin. Third on the scale of algorithm execution time. Finally, with the assistance of observed data effectiveness of each optimization technique to control the proposed AMB system is concluded which can serve as theoretical and experimental foundations for the continued use of AMB in high-speed applications.

Partial shading is the most unexpected scenario encountered by the arrays that degrade the performance causing power reduction, non-convex characteristics curves, losses, hotspot, module damage, and system failure. The adoption of various reconfiguration techniques has recently provided relief to the PV array to reduce power losses during partial shading. However, these techniques exhibit vulnerabilities such as reliable operation, ease of implementation and, higher cost and complexity due to the requirement of abundant manpower, labour, complex algorithms, dynamic operation, switches and sensors that cause additional power losses. Hence, this paper presents a low cost and less complex reconfiguration technique for PV arrays to effectively increase the power generation during partial shading scenarios. The proposed reconfiguration does not require any manpower, labour, algorithms or additional devices to reduce the losses in arrays during shading. The efficacy of the technique is tested using two array sizes under various shading scenarios using MATLAB modelling and real-time field experiments. Also, for better analysis, the performance of the proposed technique is compared with conventional configurations and Sudoku reconfiguration. The investigation proclaimed that the proposed reconfiguration technique has an average power enhancement of 20% higher than any other conventional configurations.

The growing Indian economy calls for the urgent need to review the ways and means to conserve energy consumed by the industrial sector. As a part of fulfilling the objective, the Government of India has made it mandatory to conduct periodic energy audits in the bulk industrial sector to be followed up with a practical implementation of energy conservation (ECON) measures as suggested by the energy audit team. This paper presents the energy audit conducted in a medium-size textile mill in western Tamil Nadu of India. The energy audit has been conducted, and an exhaustive study of the energy consumption pattern of the mill has been carried out using tools like power quality analyzer, thermal leak detectors, air leakage detectors, and luminance meter. The qualitative data measured has been studied, and suitable site-specific and problem-specific methods, suggestions, and recommendations have been examined to yield substantial energy savings. The implementation of energy efficiency technologies and energy saving (ES) methods like effective use of the existing machinery, installing application-specific machinery, reduction/ avoiding energy wastage was also carried out. The conducted energy audit on the chosen textile leads to the reduction of energy consumption by almost 21 % per day. It saved company utility energy by nearly 13.59 %. This paper examines the recommendations and the subsequent energy efficiency implementations about specifically (i) energy demand management, (ii) equipment healthiness, and (iii) identification of energy wasted. The energy-saving outcome is elaborated with cost-effective planning and execution.

The intelligent optimization techniques have been introduced by carefully observing the behavior of various hunters like a whale, grey wolf, Aquila, and lizards for estimating global optimum solutions in fair time by forming appropriate mathematical models. However, hunting-based algorithms suffer from slow and pre-requisite convergence and get caught up in local minimum. Aquila optimizer (AO) is one of the recently developed hunting-based methods that encounter a similar type of shortcoming in a few situations. This research introduces the concept of chaotic mapping to the standard AO in order to increase the convergence speed. Also to maintain the balance of exploration performed by AO with its exploitation capability, a single stage evolutionary algorithm is also integrated with it. The performance of standard AO and modified AO are tested for well-defined unimodal and multimodal Benchmark functions. The proposed framework produces one population by standard AO and a new population by single stage genetic algorithm based evolutionary concept in which binary tournament selection, roulette wheel selection, shuffle crossing over and displacement mutation occur to generate a new population. The chaotic mapping criteria are then applied to obtain various variants of the standard AO technique. The general results obtained from the proposed novel chaotic mapping-based advanced AO with single stage evolutionary algorithm shows that it outperforms the standard AO. This advanced technique is thus applied to real-world design engineering problems to study its significance from an industrial point of view.

Mobile ad-hoc network is an assortment of distinct attribute-based mobile devices that are autonomous and are cooperative in establishing communication. These nodes exploit wireless links for communication that causes injection of the adversaries in the network. Therefore, detection and mitigation of adversaries and anomalies in the network are mandatory to retain its performance. To strengthen this concept, in this article, a novel secure neighbor selection technique using recurrent reward-based learning is introduced. This proposed technique inherits the benefits of conventional routing and intelligent machine learning paradigm for classifying the states of the nodes based on their communication behavior. Thorough learning of the behavior of the nodes unanimously at all the hop-levels of communication enables establishing secure and consistent routing and transmission paths to the destination. The performance of the proposed technique is estimated using the metrics throughput, packet delivery ratio, and delay and detection ratio. Experimental analysis proves the consistency of the proposed technique by improving throughput, packet delivery ratio, and detection ratio under less delay.

This study proposes a duty cycle-based direct search method that capitalizes on a bioinspired optimization algorithm known as the salp swarm algorithm (SSA). The goal is to improve the tracking capability of the maximum power point (MPP) controller for optimum power extraction from a photovoltaic system under dynamic environmental conditions. The performance of the proposed SSA is tested under a transition between uniform irradiances and a transition between partial shading (PS) conditions with a focus on convergence speed, fast and accurate tracking, reduce high initial exploration oscillation, and low steady-state oscillation at MPP. Simulation results demonstrate the superiority of the proposed SSA algorithm in terms of tracking performance. The performance of the SSA method is better than the conventional (hill-climbing) and among other popular metaheuristic methods. Further validation of the SSA performance is conducted via experimental studies involving a DC-DC buck-boost converter driven by TMS320F28335 DSP on the Texas Instruments Experimenter Kit platform. Hardware results show that the proposed SSA method aligns with the simulation in terms of fast-tracking, convergence speed, and satisfactory accuracy under PS and dynamic conditions. The proposed SSA method tracks maximum power with high efficiency through its superficial structures and concepts, as well as its easy implementation. Moreover, the SSA maintains a steady-state oscillation at a minimum level to improve the overall energy yield. It thus compensates for the shortcomings of other existing methods.

This proposed work demonstrates the illustration of dynamic performance intensification of a Permanent Magnet Synchronous Motor (PMSM) employed by a PWM controlled inverter which synchronizes with the rotor movement intimation. PMSM are widely hired in electric vehicles since it possesses better dynamic response, improved torque-speed property, and reduced noise, energy-efficient and power factor in comparison with traditional motors. In the present work, it is observed that by few modifications of the position control strategy as good as sinusoidal stator currents response generates less torque ripples. The mathematical model for PMSM is derived from park’s transformation. Further, a maiden attempt is taken to introduce the performance indicator ’sensor angle’ to estimate the rotor position in this strategy. From the established model, the various dynamic behavior of the drive system is determined analytically without and under various load disturbances. Additionally, a particle swarm optimization (PSO) technique is adopted to optimize the performance of the proposed dynamic strategy. An efficient speed control strategy by the variation of DC bus voltage is achieved which is equivalent to the armature voltage control of the conventional dc machine. Further, efficient and simple control circuitry of the voltage source inverter (VSI) is obtained in this strategy. To verify the efficacy of the proposed algorithm, necessary tests are carried out in a real-time setup. Therefore, an improved control strategy obtained from the simulation and an experimental approach meets the dynamic behavior employed in light weight electric vehicles.

Low power distribution systems have severe power quality issues due to the non-linearity of several residential and industrial loads. The main power quality issue is the harmonics leading to the overheating of the transformers in the distribution systems. By employing passive filters, active filters, and custom power devices, the harmonics in the source current can be reduced. To overcome the drawbacks of conventional tuned filters and active power filters the modified shunt active power filter was introduced with the fuzzy logic controller. In this paper, an effective way of reducing the total harmonic distortion using three-phase three-wire shunt active filter is carried out and this has been investigated through three control methods namely synchronous reference frame theory, real and reactive power theory, and indirect reference current theory. The recognized control methods are implemented with the fuzzy controller to improve the performance of the induction motor drive. The hardware setup was implemented for the proposed fuzzy-based control technique to achieve better performance in terms of reduced total harmonic distortion and DC link voltage and improved speed performance of induction motor drive when compared to other control methods. Further power factor correction and better reactive power compensation are achieved by implementing hardware.

The paper gives a review of the investigation, which is being imported under different shading scenarios on the solar photovoltaic (PV) array arrangements. Under non-uniform irradiations, the authors pursue voluminous interpretation to scrutinize the mismatch power losses (PL) in PV array systems. In addition to power, the partial shading also reveals non-linearity along with multiple maximum power points (MPP) on performance curves i.e. power-voltage (P-V) and current-voltage (I-V). The inspection of the optimal layout of PV modules during the study helps us to extract maximum power and reduce the number of power peaks, when arranged in an array under partial shading conditions (PSCs). In the vicinity of PV array configurations such as series-parallel (SP), honey-comb (HC), bridge-link (BL), total cross-tied (TCT), and hybrid series-parallel-Total cross-tied (SP-TCT), bridge link-honey comb (BL-HC), and bridge link-total cross-tied (BL-TCT) are considered to investigate the performance under shadowing conditions. Moreover, Latin square (LS) puzzle is introduced to reconfigure the PV array and extensive comprehensive comparison with conventional is presented and entitled as “LS-TCT” configuration. The MATLAB/Simulink environment helps in modelling all the considered PV array configurations. The recommended LS-TCT configuration is turned out to be superior (for MATLAB/Simulink study) among all configurations during PSCs in terms of location of global maximum power point (GMPP), minimized PL and improved fill factor (FF). To show the superiority of proposed Shape-do-Ku (SPDK) puzzle based configuration, an experimental comparison is shown with conventional TCT and LS-TCT, Su-do-Ku (SDK) puzzle based configurations under new shading pattern-4. In addition, presented experimental study is validated the results obtained during MATLAB/Simulink study.

The growing interest with the developments of renewable sources owing to less environmental pollution creates challenges for the grid operators. Virtual Power Plant (VPP) is a novel concept that will integrate the small distributed energy resources and will act as a single conventional power plant in the electricity market. As a core energy management system in VPP, the energy should be dispatched optimally for achieving the maximum profit. Therefore, smart energy management is developed in this article of VPP with Programmable Logic Controller (PLC) and Internet of Things (IoT) in a unified market environment that integrates the DA and RT market. The cost characteristics for the interruptible load, battery storage system are modelled individually. The PLC and IoT based automation is proposed for optimal dispatch strategy of VPP. The proposed scheme can efficiently handle the energy demand for the VPP domain. Four different scenarios are considered with different loading conditions for validation of the concept of smart energy management. The profitability for each scenario is shown with the experimental results.

Partial shading is an unavoidable factor that reduces the performance of solar PV systems. The PV system receives uneven irradiation due to partial shading which causes the mismatch loss. The partial shading distracts the irradiation from the PV modules that makes the healthy modules as idle or low performing modules. The mismatch loss can be mitigated by uniformly distributing the partial shading over the PV array. In this work, L-shaped propagated array configuration method with a new dynamic reconfiguration algorithm have proposed for enhancing the energy conversion under the partial shading conditions. A new kind of array configuration is implemented in a $4\times 4$ PV array for the better shade dispersion. Further, a dynamic reconfiguration algorithm is employed to disperse the effect of partial shading. The combination of new array configuration and reconfiguration method is simulated in MATLAB/Simulink® and implemented in hardware. The outputs are measured under all possible shading patterns and validated with the outputs of convention methods for observing the enhanced energy conversion rate of the proposed system.

This paper presents an in-depth analysis and investigation on the performance of static photovoltaic (PV) array configurations subjected to various partial shading conditions (PSCs). Under PSCs, the electrical characteristics of the PV modules are critically monitored and reasons for their behavioral changes are highlighted. By doing so, this study aims to improve the efficiency of PV systems by minimizing mismatch losses and determining the optimum array configuration which is characterized by the highest maximum power and lowest relative losses under PSCs. Besides, this study complements and carries forward the previous studies through the detailed analysis of each configuration subjected to various practically probable PSCs. Three different PV array sizes ( $5\times4$ , $5\times5$ , and $3\times10$ ) are used to analyze the results and performance under considered shading scenarios. MATLAB/Simulink platform is used to model and simulate the PV array using the single diode (5-parameters) model. In-depth analysis of current flow across cross-ties and bypass diodes activation shows that the diagonal shading pattern leads to lower power loss (PL). Besides, the Total Cross-Tied (TCT) configuration demonstrates superior performance under most of the PSCs compared to other configurations. These results provide valuable information about the performance of PV array which may lead to better estimation and prediction of global maximum power (GMP) generation of a PV system.

Partial shading causes mismatch losses in the solar PV system. In the PV array, the power output from the healthy PV modules is gone in vain due to the mismatch losses. The PV array construction with the high resistivity to the mismatch loss generation is the progressing research work in the research field. In this work, a new kind of array configuration scheme is framed for the PV system for overcoming the effect of partial shading. The proposed array configuration has a high resistivity to the mismatch loss generation over the other conventional array configuration methods. The array configuration is framed in a pattern that is similar to the spiral step pattern. Each row of the PV array is constructed with the PV modules from each row of the conventional Total Cross Tied configuration with the optimized distance. This row construction allows the system to uniformly disperses the partial shading over the PV array. The simulation analysis is carried out by applying various shading patterns in MATLAB/SimulinkⓇ. The performance of the proposed array configuration is also analyzed in the experimental setup and the results were presented.

The Photovoltaic (PV) cell converts a portion of incident irradiation of visible wavelength into electricity and the remaining into heat, thereby decreasing the electrical efficiency. Hence, it is necessary to transfer the heat generated in the module by a cooling medium, thereby maintaining the operating temperature within the operating limit. This study discusses the feasibility of cooling the monocrystalline and polycrystalline modules by using rehashed edible oil (coconut oil, sesame oil, and peanut oil) with an integrated oil tank attached to the backside of the module. This study has used the environmentally friendly rehashed edible oil as a coolant, which can be used as an alternate to the toxic mineral oil. Hence, this study can prevent the consumption of reused edible oil along with the food, which causes harmful effects on human health. The rehashed edible oil flows from the storage tank through the backside of the module and is collected in another storage tank, which can be reused. Also, the performance of the monocrystalline and polycrystalline modules under different rehashed edible oil shows a significant reduction in module temperature and improvement in the efficiency of the module. The performance of the peanut oil is found to be superior in improving the performance by 14.0 % and 16.8 % on monocrystalline and polycrystalline modules respectively.

Partial shading is the commonly encountered scenario of building roof-top based PV arrays that mainly occur due to the shadow of the neighbouring buildings and clouds resulting in unexpected losses and deteriorated system performance. The arrays are connected in various configurations to enhance the system performance during shading. In this paper, various conventional and hybrid interconnection configurations based on series-parallel (SP), bridge-linked (BL), and total cross tied (TCT) topologies of the roof-top PV arrays are examined under various partial shading scenarios caused by the neighbouring building and clouds. The investigation is done for a $9\times 9$ roof-top array in MATLAB/Simulink environment considering various comparison parameters. It has been found that during 1.23%, 7.40%, 11.11%, 17.75%, 18.51%%, 22.22%, and 24.69% of total array shading, SP generated the maximum power whereas, during 30.86%, 61.72% shading, TCT has the generated only a slightly higher power as compared to SP. Hence, the study concludes that the configurations have a puny effect on the power generation of the arrays during uneven shading patterns caused by buildings and clouds.

Providing security to the Supervisory Control and Data Acquisition (SCADA) systems is one of the demanding and crucial tasks in recent days, due to the different types of attacks on the network. For this purpose, there are different types of attack detection and classification methodologies have been developed in the conventional works. But it limits with the issues like high complexity in design, misclassification results, increased error rate, and reduced detection efficiency. In order to solve these issues, this paper aims to develop an advanced machine learning models for improving the SCADA security. This work comprises the stages of preprocessing, clustering, feature selection, and classification. At first, the Markov Chain Clustering (MCC) model is implemented to cluster the network data by normalizing the feature values. Then, the Rapid Probabilistic Correlated Optimization (RPCO) mechanism is employed to select the optimal features by computing the matching score and likelihood of particles. Finally, the Block Correlated Neural Network (BCNN) technique is employed to classify the predicted label, where the relevancy score is computed by using the kernel function with the feature points. During experimentation, there are different performance indicators have been used to validate the results of proposed attack detection mechanisms. Also, the obtained results are compared with the RPCO-BCNN mechanism for proving the superiority of the proposed attack detection system.

Solar Photovoltaic array may often be subjected to partial shading, which may lead to uneven row current and creates local maximum power point on the power-voltage characteristics. One of the effective approaches to dilute the concentration of partial shading is the array reconfiguration technique. This study proposes a ken-ken puzzle-based reconfiguration technique for $4\times 4$ total-cross-tied configuration to rearrange the position of modules within the array and to improve the maximum power under partial shading conditions. Further, the performance of the ken-ken puzzle arrangement is compared with the total-cross-tied configuration and existing reconfiguration techniques namely odd-even, Latin Square, and Sudoku reported in the literature. The performance of all these configurations is evaluated in terms of fill factor, mismatch loss, power loss, execution ratio, and performance enhancement ratio. The proposed ken-ken puzzle-based reconfiguration technique mitigates the occurrence of local maximum power point and eliminates the need for a complex algorithm to track the global maximum power point. The simulation result shows that the KK puzzle-based reconfiguration technique has obtained an improved PE of 10.85 % compared to TCT configuration, followed by LS, Sudoku, and OE. Also, the experimental result shows the effectiveness of the ken-ken in diluting the effects of partial shading when the rows of the photovoltaic array are shaded. The ken-ken puzzle-based reconfiguration technique reduces the complexity, maintenance and increases reliability, scalability of the PV array.

One of the most challenging and interesting field in power electronics is the ability to mitigate the Electromagnetic Interference (EMI). A natural source of EMI includes the atmospheric discharge/charge phenomena and extra-terrestrial radiation. Man-made source of EMI are line radiation, auto ignition, radio frequency interference and power lines. Suppression of EMI and enhancing the Electro Magnetic Compatibility (EMC) has become essential in high frequency power electronic converters. This review article is a one stop solution for new researchers and practitioners to understand about the effects of EMI and its suppression techniques in detail.

Massive infiltration of photovoltaic (PV) systems into electric supply networks creates numerous challenges in the present era, as the PV systems become an alternative to non-renewable energy resources. Partial shading, nevertheless, is an essential problem which affects the productivity and life of PV plants. PV reconfiguration is known as a powerful technique to resolve this effect. It is achieved by rearranging the PV modules according to their temperature and levels of shade. Therefore, in this paper, we have utilized three simple population-based optimization algorithms that are known as the flow regime algorithm (FRA), the social mimic optimization algorithm (SMO), and the Rao optimization algorithm to dynamically restructure the PV array. The effectiveness of the proposed algorithms is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the results obtained are compared with a regular total-cross-tied (TCT) connection and recently published techniques such as the competence square (CS) and genetic algorithm (GA). Furthermore, to demonstrate the suitability of proposed approaches in real-time implementation, real-time irradiation data of a particular location are considered and fed into the proposed algorithms for effective shade dispersion. After successful shade dispersion, the total energy generated using the three proposed algorithms is calculated and compared with the TCT reconfigured system for one year. The presented energy calculations and revenue generation confirm that the power produced by the proposed FRA technique is 13% higher than that generated by the TCT configuration. Furthermore, the presented PV characteristics show a reduced number of multiple peaks in the system. Thus, the proposed FRA technique can be endorsed as a technique that is superior to other existing methods.

Large-scale solar photovoltaic (PV) plants play an essential role in providing the increasing demand for energy in recent time. Therefore, in the purpose of achieving the highest harvested power under the partial shading conditions as well as protecting the PV array from the hot-spot calamity, the PV reconfiguration strategy is established as an efficient procedure. This is performed by redistribution of PV modules according to their levels of shading. Motivated by this, the authors in this article have introduced a novel population-based algorithm that is known as marine predators algorithm (MPA) to restructure the PV array dynamically. Moreover, a novel objective function is introduced to enhance the algorithm performance rather than utilizing the regular weighted objective function in the literature. The effectiveness of the proposed algorithms based on the novel objective function is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the obtained results are compared with a regular total-cross-tied (TCT) connection, manta ray foraging optimization (MRFO), harris hawk optimizer (HHO) and particle swarm optimizer (PSO) based reconfiguration techniques. Furthermore, to demonstrate the suitability of the proposed methods, large scale PV arrays of $16\times16$ and $25\times25$ are considered and evaluated. The results reveal that MPA enhanced the PV array power by percentage of 28.6 %, 2.7 % and 5.7 % in cases of $9\times9$ , $16\times16$ and $25\times25$ PV arrays, respectively. The comprehensive comparisons endorse that MPA shows a successful shade dispersion; hence the number of multiple peaks in the PV characteristics has reduced, and high values of power have been harvested with least mean execution time in comparison with PSO, HHO and MRFO. Moreover, the Wilcoxon signed-rank test has been accomplished to confirm the reliability and applicability of the proposed approach for the PV large scale arrays as well.

The ever increasing trend of renewable energy sources (RES) into the power system has increased the uncertainty in the operation and control of power system. The vulnerability of RES towards the unforeseeable variation of meteorological conditions demands additional resources to support. In such instance, energy storage systems (ESS) are inevitable as they are one among the various resources to support RES penetration. However, ESS has limited ability to fulfil all the requirements of a certain application. So, hybridization of multiple ESS to form a composite ESS is a potential solution. While integrating these different ESS, their power sharing control plays a crucial role to exploit the complementary characteristics of each other. Therefore, this article attempts to bring the numerous control strategies proposed in the literature at one place. Various control techniques implemented for HESS are critically reviewed and the notable observations are tabulated for better insights. Furthermore, the control techniques are classified into broad categories and they are briefly discussed with their limitations. From the carried-out analysis, the challenges faced towards the implementation of HESS for standalone and grid connected microgrid systems are presented. Finally, the future directions are laid out for the researchers to carry out the research and implementation of HESS technologies. Overall, this article would serve as a thorough guide on various control techniques implemented for HESS including their features, limitations and real-time applications.

The increase in the penetration of renewable energy sources (RES) has reduced the effective inertia of the power system dominated by synchronous machines. The reduction in inertia has paved the way to the development of inertia emulation techniques, which complements the increased penetration of RES. The synchronverter technology is one among the virtual inertia emulation techniques which resembles close to the synchronous machine. The advancements in control and adaptations of synchronverter for various applications demand a comprehensive yet critical review. Thus, the main objective of this paper is to present a critical review of synchronverter technology which could increase the inertial response of RES. A critical analysis of modifications made to original synchronverter and the stability assessment techniques is presented. The effect of parameter variation on stability and dynamic performance is brought out as a decision matrix by analysing the movement of eigenvalues presented in various works. Towards the end, a synoptic overview is presented to depict the research trend and emphasize the domain which requires further attention. Furthermore, a brief discussion of the research gaps perceived during the phase of review is presented to leverage future research in the field.

A partial shading condition is an environmental phenomenon that causes multiple peaks in Photovoltaic (PV) characteristics. Introducing robust and reliable Maximum Power Point Tracking technique is essential in PV systems to extract the Global Maximum Power Point (GMPP) irrespective of the environmental conditions. Therefore in this manuscript, a novel optimization algorithm is implemented for MPPT. The developed technique named Chaotic Flower Pollination Algorithm (C-FPA) merges the chaos maps (Logistic, sine, and tent maps) to tune the basic algorithm parameters adaptively. The effectiveness of the introduced variants is proved using several patterns of partial shading condition. Moreover, these variants are certified for tracking the GMPP in case of dynamic and sudden variation in the irradiance conditions. Several statistical analysis is carried out to evaluate the performance of the proposed variants in comparison with the standard version of the Flower Pollination Algorithm (FPA). The significant outcome clarifies that combining the chaos maps with FPA improves the dependability and stability of the FPA and offers higher tracking efficiency with a reduction of tracking time by 50% when compared to FPA. Moreover, the proposed C-FPA provides a better dynamic response, especially with the tent chaos map.