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The Unified Power Quality Conditioner (UPQC) is a promising solution for mitigating multiple Power Quality(PQ) issues in distribution systems, including harmonics, poor power factor, voltage sag/swell and voltage imbalance. The conventional Sliding Mode Controller (SMC) in UPQCs suffers from wide switching frequency variations, chattering problems, and inherent active and reactive power coupling. This study proposes a nonlinear control method, Sliding Mode-based Direct Power Control (SMC-DPC), for the simultaneous regulation of the shunt and series compensators in a UPQC. By optimizing voltage vector selection based on real-time power errors, the proposed method effectively mitigates chattering, and reduces switching frequency variations, and ensures precise tracking of instantaneous active and reactive powers even in the presence of coupling effects. The proposed approach simplifies the system design and improves steady state and dynamic power tracking. The simulation results in MATLAB Simulink® on a 20 kVA system demonstrate that the proposed method achieves a source current THD of 1.52%, compared to 2.31% for conventional SMC and 5.11% for linear controller. Furthermore, the method is robust to grid parameter variations and demonstrates satisfactory performance in both strong and weak grids. In weak grids, the proposed method reduces the line losses by 13.71% and 14.54% compared to SMC and linear controller respectively. The reported results comply with international standards such as IEEE-519 and IEC 61000-3-12, confirming effectiveness of SMC-DPC for enhancing PQ in distribution system.

Abstract Revamping the power grid into a smart grid and modernizing it with advanced metering infrastructure are essential steps in addressing ongoing energy challenges. Smart meters play a pivotal role in power grid modernization by providing real-time energy-related data which fuels the control activities of modern grid. While the advantages of smart meters are evident, their deployment necessitates a comprehensive redesign of the grid architecture, involving smart end devices for monitoring and communication networks for efficient data exchange. Yet, achieving cost-effective and widespread adoption of these technologies poses a challenge, particularly in developing and underdeveloped nations due to high capital costs, technological constraints and uneconomical deployment strategies. Moreover, the prevailing research often advocates a complete transition to new smart meters to achieve 'smartness,' neglecting the potential of existing metering infrastructure upgrades. To address these concerns, this study proposes and simulates the design of a low-cost Smart Network Meter. Notably, this meter upgrades the existing meter infrastructure while validating a cost-effective deployment strategy. Furthermore, a consumer opinion survey was also conducted to compelling evidence supporting the adoption of the proposed low-cost smart metering solution.

Due to their inherent ability and environmentally friendly nature, renewable energy sources are the only real option for producing pollution-free energy in the modern era. Solar energy is one of the best possibilities in this family for supplying civilization with the power and energy it needs. Researchers can efficiently boost a PV panel’s efficiency by using the maximum power point tracking (MPPT) approach to extract the most power from the panel and send it to the load. The authors of this study examined and surveyed the sequential advancement of solar PV cell research from one decade to the next, and they elaborated on the upcoming trends and behaviours. Many maximum power point tracking algorithms (MPPTs) that are employed in photovoltaic systems (PVSs) that function under both uniform and partial shade situations are structurally summarized in this work. Well-written descriptions of the features of photovoltaic modules are followed by a variety of effective control strategies, including both AI-based and traditional controllers. In addition, appropriate knowledge of the various controllers is essential when the PV system is exposed to partial shade, keeping in mind the different control systems’ classifications in this situation. A thorough analysis of several soft computing-based techniques is also included, as well as many classical controller-based PV systems. First, well-developed traditional MPPT methods are used, followed by artificial intelligence-based MPPT approaches. Later, a thorough comparison of the various MPPT-controlling approaches is established. For PV systems operating under partial shade conditions (PSCs), the advantages and disadvantages of the various MPPT techniques are outlined, contrasted, and assessed. Future research directions for MPPT are also being investigated. A collection of several datasets pertaining to various control processes that were gleaned from various research articles has also been presented. Researchers working on PV-based MPPT and those working in the sectors of renewable energy production and environmentally sustainable development would be very interested in the findings of this review study.

AbstractThis paper aims to provide a model that combines reconfiguration with Unit Commitment (UC) and analytically examine Storage Capacity Increment Effects (SCIEs) in Micro-Grid (MG) operation. The case study includes batteries as the storage system and a conventional 10-bus MG with Wind Turbine (WT) and Micro-Turbines (MTs) as energy sources. The load demand and energy estimation of the Wind Unit (WU) with respect to wind speed changes are considered uncertain parameters. Additionally, a newly introduced algorithm and an objective function based on MG’s day-ahead benefit are employed to tackle the problem. According to Monte Carlo Simulation (MCS), a few scenarios are created for modeling uncertainties, and the MG’s optimal operation is examined under these situations. This study is based on two cases: the first examines the MG’s scheme with just one battery, and the second investigate SCIEs. This paper seeks to maximize MG’s benefit and optimize power exchange with increasing storage capacity. The statistical analysis results show that the proposed strategy can offer more cost-effectiveness, reliability, and power quality, though challenges remain.

AbstractLow energy inertia, a high penetration level of renewable energy sources, and a large ratio of power deviations in a small power transmission system have put microgrid frequency at risk of instability. Based on the close coupling between microgrid frequency and system security requirements, providing sufficient ancillary services from cost-effective and environmentally friendly resources is a major challenge in an efficient energy management system. In this article, a fuzzy approach and a new optimization technique on the PI controller are used to solve the problem of frequency stability in the AC micro-grid in the island mode by optimising the PI-fuzzy controller parameters. The suggested modified new self-organizing hierarchical PSO with jumping time-varying acceleration coefficients (MNHPSO-JTVAC) based controller’s results show that the control system has been investigated under three scenarios: load variations, RES uncertainty, white noise, and frequency correction. In terms of frequency responsiveness, the results are good when compared to traditional algorithms: The suggested design has been able to optimise the control system parameters by the proposed MNHPSO-JTVAC algorithm to solve microgrid frequency deviations caused by source uncertainty, load changes, and white noise, respectively, 0.008473, 0.01334, and 23.71, compared to classical PI control—PI, fuzzy And PI-fuzzy-GOA shows that in practical systems, this method can be considered very desirable and attractive.

In general, multilevel inverters (MLIs) are regarded as advanced power conversion systems required for medium-voltage and high-power applications. The purpose of this article is to provide an overview of recently investigated MLI topologies classified into various categories based on the transformer requirement such as the transformer less (TL-MLI) and transformer-based (T-MLI) with single and multi-source topologies of symmetric, asymmetric, hybrid and single DC sources for renewable energy applications. For the previous few decades, multiple new variants of each group have been developed. The design and functioning of each topology, as well as each group, are examined in this study. T-MLI topologies of H-bridge, three-leg inverter-based, and other T-MLI configurations are discussed from a configuration standpoint. Each topology’s state-of-the-art of both MLI configurations and problems are treated separately. Furthermore, the disadvantages and benefits of each topology have been thoroughly addressed. Finally, a comparison of existing topologies is conducted to determine the optimal topology based on several performance characteristics and the cost evaluation has been presented. This article provides a comprehensive overview of recently developed multilevel inverters and provides a solution for developing the MLIs for future research on renewable energy applications.

Abstract In this research work, an adaptive TS‐fuzzy based RBF neural network (ATSFRBFNN) algorithm based maximum power point tracker (MPPT) is employed for grid integrated photovoltaic (PV) system. The novel learning algorithm provides accurate and rapid PV power tracking under fluctuating solar insolation. However, an improved damping circulating current limiting inverter controller is employed to generate gating signal of voltage source inverter and to deliver reduced harmonic constant, less power loss, mitigation of power quality issues regulation of Dc‐link voltage utilization for grid integrated PV system under steady, and transient weather conditions. The experimental results justify the improved system performance under varying operating conditions. The behaviour of novel hybrid PV MPPT structure is compared with TS‐fuzzy, RBFNN, and GA‐RBF for higher tracking efficacy, least tracking deviation, accurate responses, and zero steady‐state power oscillation around MPP region.

Abstract Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role throughout the operation of the conventional power system. The precise modelling and complex analyses of STLF have become more significant in advanced microgrid (MG) applications. Several models are proposed for STLF and tested successfully in the literature. The selection of a forecasting method is mostly based on data availability and its objectives. This article presents a survey of the latest analytical and approximation techniques reported in the literature to model STLF in an MG environment. This article mainly focusses on the review on important methods applied to forecast renewable energy availability, energy demand, and price and load demand. Different models, their main objectives, methodology, error percentage, and so forth, are critically reviewed and analysed. For quick reference, we have highlighted the important points in the form tables. The researchers can quickly identify and frame their research problem related to the LF area by reading this review paper.

Today, the desire to use renewable energy as a source of clean and available energy in the grid has increased. Due to the unpredictable behavior of renewable resources, it is necessary to use energy storage resources in the microgrid structure. The power generation source and the storage source in microgrids should be selected in such a way that it has the ability to respond to the maximum demand in the state connected to the grid and operate independently. In this article, the optimal capacity and economic performance of a microgrid based on photovoltaic and battery system have been investigated. In this way, first, using the iterative optimization method, the optimal microgrid capacity has been obtained. Then, the dynamic planning method has been used for optimal microgrid energy management. The simulation results show the accuracy and efficiency of the proposed solutions. The proposed controller, while automatically and dynamically adapting to the solar cell output changes, is capable of responding to external requests, such as price signals or satisfying power system constraints or operator requests. In addition, the results indicate that by using the proposed energy management system, the microgrid system can regain stability during one to two cycles, during the occurrence of PV system radiation changes as well as ESS charge changes. And also, according to the ESS charge changes, the voltage changes should be within the defined permissible range between 0.95 and 1.05 pu, which is the result of the unique efficiency of the proposed energy management system.

Abstract The paper presents the performance analysis‐based reliability estimation of a self‐excited induction generator (SEIG) using the Monte‐Carlo simulation (MCS) method with data obtained from a self‐excited induction motor operating as a generator. The global acceptance of a SEIG depends on its capability to improve the system's poor voltage regulation and frequency regulation. In the grid‐connected induction generator, the magnetizing current is drawn from the grid, making the grid weak. In contrast, in the SEIG stand‐alone operation, an external capacitor arrangement is implemented to render the reactive power support. This capacitor arrangement is connected across the stator terminals during the stand‐alone configuration of SEIG. The capacitor serves two purposes, which include voltage build‐up and power factor improvement. Therefore, the paper deals with obtaining the minimum capacitor value required for SEIG excitation in isolated mode applications, including stand‐alone wind power generation. The SEIG performance characteristics have been evaluated for different SEIG parameters. The simulation and experimental results are then compared and found satisfactory. Then, SEIG reliability is estimated considering the MCS method utilizing SEIG excitation's failure and success rates during experimental work in the laboratory. Finally, the SEIG reliability evaluation is performed considering different wind speeds.

Abstract The paper represents a comprehensive review of the wind farm layout and reliability assessment of the wind farm integrated electrical power system. The authors have done a review on the proliferation of renewable energy which raises the uncertainties in the electrical power system. The uncertainties including wind speed and wake effect are important to deal with when an isolated microgrid is considered. The scenario becomes vigilant when the wind farms are integrated with the main grid. Due to uncertainties, the study of reliability evaluation of a wind integrated power system would become significant to analyse the electrical power system behaviour effectively. So, the paper discusses the layout optimisation methods of wind turbines considering the uncertainty parameters, mainly the wake effect. In this regard, the different wake models and optimisation methods based on a single‐objective and multi‐objective functions are reviewed in detail with the proper comparisons. The paper serves as a better illustration of the competency of these optimisation methods on the optimal wind turbine location on a wind farm. Furthermore, the paper extends the view on the reliability and cost assessment, and reliability improvement techniques of the wind integrated power system. This article provides comprehensive information, yields an attractive and subsequent tool for research requirements for the researchers to design the wind farm layout, and assessed the reliability of a wind integrated power system.

Abstract The operation of Dynamic Voltage Restorer has been studied for the mitigation of supply voltage disturbances like sag, swell, distortions, and unbalances. A Dynamic Voltage Restorer with three single‐phase Voltage Source Converters has been implemented for this purpose. Dynamic Voltage Restorer's compensation capability has been evaluated while introducing the above‐said voltage related disturbances in the supply by different means. A control algorithm named Variable Fractional Power‐Least Mean Square has been proposed for generating the load reference voltage for Dynamic Voltage Restorer. Variable Fractional Power‐Least Mean Square extracts the fundamental active and reactive component out of non‐ideal supply voltage and is thus, used in generating reference load voltage. This algorithm is more robust with respect to disturbance due to variable step size and is computationally less expensive. In addition, an optimization‐based approach has been proposed to estimate the approximate values of PI control gains. For this reason, a population‐based optimization method known as Sine Cosine Optimization has been used. The added feature of the optimization method is the reduction of computational time as compared to conventional PI controller tuning. A model of Dynamic Voltage Restorer using Variable Fractional Power‐Least Mean Square control algorithm with Sine Cosine Optimization tuned PI gains has been built in MATLAB Simulink as well as a reduced scale experimental prototype and their results have been presented with discussion.

Deep learning (DL) is an exciting field of interest for many researchers and business. Due to a massive leap in DL based research, many domains like Business, science and government sectors make use of DL for various applications. This work puts forward the importance of DL and its application in a few critical electrical segments. Initially, an introduction to Artificial Intelligence (AI) and Machine Learning (ML) is presented. Then the need for DL and the popular architectures, algorithms and frameworks used are presented. A summary of different techniques used in DL is outlined, and finally, a review on the application of deep learning techniques in some popular electrical applications is presented. Five critical electrical applications, namely identification of bearing faults, hot spots on the surface of PV panels, insulator faults, an inspection of power lines and Electric vehicles have been considered for review in this work. The primary aim of this work is to present chronologically, a survey of different areas in which it applies DL along with their architectures, frameworks and techniques to provide a deeper understanding of DL for widespread use in real-time applications.

For renewable sources application like smart grids, microgrids, etc. high voltage gain converter becomes a fundamental unit. In this article, a new hybrid circuit of zeta and boost converter based on active-quad-switched-inductor (AQSL) is proposed. The discontinuous input current in classical zeta circuit determines the less consumption of input source. However, the proposed hybrid zeta-boost converter provides a higher voltage gain with continuous input and output currents. It achieves higher voltage gain devoid of the high-frequency transformer, and multiple stages of diode and capacitor circuit. The mode of operation, boundary region, and non-ideal model of the proposed converter are presented. Design consideration and a comparison study with recent circuits are provided. The design circuitry of the proposed converter investigated and the functionality of the suggested circuit is validated.

The concept of energy management in smart homes has received increasing attention in recent years, particularly on issues such as creating a balance between user privacy and reducing energy costs. Accordingly, this article proposes a user-oriented multi-objective approach, which minimizes energy costs and maximizes consumer privacy. In addition, a home energy management system is suggested for smart homes to optimize the energy consumption pattern of appliances. On the other hand, considering challenges in energy management of smart homes, the concept of demand-side management (DSM) is introduced. The objective of the proposed method is to reduce energy consumption to lower consumers’ electricity bills. Also, it improves user comfort (UC) in average waiting time conditions. In this research, a smart home equipped with an energy management system and smart home appliances that can inject electric power into the upstream network is considered the main system. This framework leads to a multi-objective optimization problem in which the two objectives mentioned above are considered two separate dimensions. To solve the problem, an ITS-BF Algorithm is used, which employs a random search to schedule home appliances and batteries based on the application of flexible devices in smart homes. The case studies show that the proposed method can considerably respect and satisfy users’ privacy and reduce the energy cost to an acceptable level. Finally, the numerical results obtained from the simulation have been analyzed to evaluate the proposed method’s efficiency. The simulation results show that an ITS-BF algorithm performs better than the existing methods in reducing costs and waiting time.

his short communication focuses on exploiting the inherent advantages of discrete wavelet transformation (DWT) as a diagnostic tool for post-processing and for identifying the faults that occur in the standard high-voltage direct-current (HVDC) transmission network. In particular, a set of investigations are developed and examined for single-line-to-ground fault on the generation and on the load side converter, and DC-link fault. For this purpose, a standard 12-pulse line-commutated converter (LCC)-HVDC transmission network along with the DWT algorithm is numerically modeled in the MATLAB/PLECS simulation software. Furthermore, in this paper, a set of designed faulty conditions are predicted using the output of DWT and the results of numerical simulation are presented. Results are in good agreement with expectations to prove that DWT is an effective tool for fault diagnostics.

This paper presents the characteristic behavior of direct vector control of two induction motors with sensorless speed feedback having the same rating parameters, paralleled combination, and supplied from a single current-controlled pulse-width-modulated voltage-source inverter drive. Natural observer design technique is known for its simple construction, which estimates the speed and rotor fluxes. Load torque is estimated by load torque adaptation and the average rotor flux was maintained constant by rotor flux feedback control. The technique’s convergence rate is very fast and is robust to noise and parameter uncertainty. The gain matrix is absent in the natural observer. The rotor speed is estimated from the load torque, stator current, and rotor flux. Under symmetrical load conditions, the difference in speed between two induction motors is reduced by considering the motor parameters as average and difference. Rotor flux is maintained constant by the rotor flux control scheme with feedback, and the estimation of rotor angle is carried out by the direct vector control technique. Both balanced and unbalanced load conditions are investigated for the proposed AC motor drive system. Experimental results presented in this paper show good agreement with the theoretical formulations.

In the current era, the desire for high boost DC-to-DC converter development has increased. Notably, there has been voltage gain improvement without adding extra power switches, and a large number of passive components have advanced. Magnetically coupled isolated converters are suggested for the higher voltage gain. These converters use large size inductors, and thus the non-isolated traditional boost, Cuk and Sepic converters are modified to increase their gain by adding an extra switch, inductors and capacitors. These converters increase circuit complexity and become bulky. In this paper, we present a hybrid high voltage gain non-isolated single switch converter for photovoltaic applications. The proposed converter connects the standard conventional Cuk and boost converter in parallel for providing continuous current mode operation with the help of a single power switch, which gives less voltage stress on controlled switch and diodes. The proposed hybrid topology uses a single switch with a lower component-count and provides a higher voltage gain than non-isolated traditional converters. The converter circuit mode of operation, operating performance, mathematical derivations and steady-state exploration and circuit parameters design procedures are deliberated in detail. The proposed hybrid converter circuit components, voltage gain and performance, were compared with other topologies in the literature. The MATLAB/Simulink simulation study and microcontroller-based experimental laboratory prototype of 150 W were implemented. The simulation study and experimentation results were confirmed to be a satisfactory agreement with the theoretical analysis. This topology produced non-inverting output in continuous input current mode using a single switch with high voltage gain (≈5.116 gain) with a maximum efficiency of 92.2% under full load.

Blockchain technology is increasingly used worldwide to enhance the performance and profit of any environment through its defining characteristics, such as security, auditability, immutability, and inconspicuousness. Owing to these characteristics, the blockchain can be used in various non-financial operations of some domains, such as the Internet of Things (IoT) and distributed computing. However, implementing blockchain technology in IoT is not always a feasible solution because blockchain deployment is costly, it has limited extensibility and provides irregular bandwidth and latency. In this regard, a simple size extensible (SSE) blockchain has been proposed to provide an optimal solution for IoT environments by satisfying the needs of the IoT environment as well as ensuring end-to-end security. The implementation of the proposed blockchain develops an overlay network to obtain a distributed environment where the blockchain is handled by the resources present therein. Two novel algorithms were introduced into the proposed system to minimize the irregularity and latency on one hand, and to maximize the throughput of the system on the other. The shared-time depending agreement algorithm (STD) minimizes the irregularity in the extraction operation and latency. The other, the shared throughput administration algorithm (STA) justifies the overall collection of the transmission load in the network and maintains the performance of the blockchain. The proposed system was applied to smart home IoT appliances to test the performance of the proposed system. The experimental results show that the proposed blockchain system minimizes nearly 70% of the data irregularity, latency, and furthermore, 30% of the blockchain extensibility is maximized as compared to the existing systems.

In recent times, multilevel inverters are used as a high priority in many sizeable industrial drive applications. However, the reliability and performance of multilevel inverters are affected by the failure of power electronic switches. In this paper, the failure of power electronic switches of multilevel inverters is identified with the help of a high-performance diagnostic system during the open switch and low condition. Experimental and simulation analysis was carried out on five levels cascaded h-bridge multilevel inverter, and its output voltage waveforms were synthesized at different switch fault cases and different modulation index parameter values. Salient frequency-domain features of the output voltage signal were extracted using a Fast Fourier Transform decomposition technique. The real-time work of the proposed fault diagnostic system was implemented through the LabVIEW software. The Offline Artificial neural network was trained using the MATLAB software, and the overall system parameters were transferred to the LabVIEW real-time system. With the proposed method, it is possible to identify the individual faulty switch of multilevel inverters successfully.

Cloud computing has made the software development process fast and flexible but on the other hand it has contributed to increasing security attacks. Employees who manage the data in cloud companies may face insider attack, affecting their reputation. They have the advantage of accessing the user data by interacting with the authentication mechanism. The primary aim of this research paper is to provide a novel secure authentication mechanism by using Blockchain technology for cloud databases. Blockchain makes it difficult to change user login credentials details in the user authentication process by an insider. The insider is not able to access the user authentication data due to the distributed ledger-based authentication scheme. Activity of insider can be traced and cannot be changed. Both insider and outsider user’s are authenticated using individual IDs and signatures. Furthermore, the user access control on the cloud database is also authenticated. The algorithm and theorem of the proposed mechanism have been given to demonstrate the applicability and correctness.The proposed mechanism is tested on the Scyther formal system tool against denial of service, impersonation, offline guessing, and no replay attacks. Scyther results show that the proposed methodology is secure cum robust.

Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system.

Wind Energy Conversion System (WECS) plays an inevitable role across the world. WECS consist of many components and equipment’s such as turbines, hub assembly, yaw mechanism, electrical machines; power electronics based power conditioning units, protection devices, rotor, blades, main shaft, gear-box, mainframe, transmission systems and etc. These machinery and devices technologies have been developed on gradually and steadily. The electrical machine used to convert mechanical rotational energy into electrical energy is the core of any WECS. Many electrical machines (generator) has been used in WECS, among the generators the Permanent Magnet Synchronous Generators (PMSGs) have gained special focus, been connected with wind farms to become the most desirable due to its enhanced efficiency in power conversion from wind energy turbine. This article provides a review of literatures and highlights the updates, progresses, and revolutionary trends observed in WECS-based PMSGs. The study also compares the geared and direct-driven conversion systems. Further, the classifications of electrical machines that are utilized in WECS are also discussed. The literature review covers the analysis of design aspects by taking various topologies of PMSGs into consideration. In the final sections, the PMSGs are reviewed and compared for further investigations. This review article predominantly emphasizes the conceptual framework that shed insights on the research challenges present in conducting the proposed works such as analysis, suitability, design, and control of PMSGs for WECS.

Various statistics indicate that many of the parts of India, especially rural and island areas have either partial or no access to electricity. The main reason for this scenario is the immense expanse of which the power producing stations and the distribution hubs are located from these rural and distant areas. This emphasizes the significance of subsidiarity of power generation by means of renewable energy resources. Although in current energy production scenario electricity supply is principally by AC current, a large variety of the everyday utility devices like cell phone chargers, computers, laptop chargers etc. all work internally with DC power. The count of intermediate energy transfer steps are significantly abridged by providing DC power to mentioned devices. The paper also states other works that prove the increase in overall system efficiency and thereby cost reduction. With an abundance of solar power at disposal and major modification in the area of power electronic conversion devices, this article suggests a DC grid that can be used for a household in a distant or rural area to power the aforementioned, utilizing Solar PV. A system was designed for a household which is not connected to the main grid and was successfully simulated for several loads totaling to 250 W with the help of an isolated flyback converter at the front end and suitable power electronic conversion devices at each load points. Maximum abstraction of operational energy from renewable sources at a residential and commercial level is intended with the suggested direct current systems.

DC to AC inverters are the well-known and improved in various kinds photovoltaic (PV) and gird tied systems. However, these inverters are require interfacing transformers to be synchronized with the grid-connected system. Therefore, the system is bulky and not economy. The transformerless inverter (TLI) topologies and its grid interface techniques are increasingly engrossed for the benefit of high efficiency, reliability, and low cost. The main concern in the TL inverters is common mode voltage (CMV), which causes the switching-frequency leakage current, grid interface concerns and exaggerates the EMI problems. The single-phase inverter two-level topologies are well developed with additional switches and components for eliminating the CMV. Multilevel inverters (MLIs) based grid connected transformerless inverter topology is being researched to avail additional benefits from MLI, even through that are trust topologies presented in the literature. With the above aim, this paper has proposed three -phase three-level T type NP-MLI (TNP-MLI) topology with transformerless PV grid connected proficiency. The CM leakage current should handle over mitigating CMV through removing unwanted switching events in the inverter pulse width modulation (PWM). This paper is proposes PV connected T type NP-MLI interface with three-phase grid connected system with the help of improved space vector modulation (SVM) technique to mitigate the CM leakage current to overcome the above said requests on the PV tied TL grid connected system. This proposed the SVM technique to mitigate the CM leakage current by selecting only mediums, and zero vectors with suitable current control method in order to maintain the inverter current and grid interface requirements. The proposed PV tied TNP-MLI offering higher efficiency, lower breakdown voltage on the devices, smaller THD of output voltage, good reliability, and long life span. The paper also investigated the CM leakage currents envisage and behavior for the three-phase MLI through the inverter switching function, which is not discussed before. The proposed SVM on TL-TNP-MLI offers the reliable PV grid interface with very low switching-frequency leakage current (200mA) for all the PV and inverter operation conditions. The feasibility and effectiveness of the TLI and its control strategy is confirmed through the MATLAB/Simulink simulation model directly as compared with 2kW roof top PV plant connected TL-TNP-MLI experimentation, showing good accordance with theoretical investigation. The simulation and experimental results are demonstrated and presented in the good stability of steady state and dynamics performances. The proposed inverter reduces the cost of grid interface transformer, harmonics filter, and CMV suppressions choke.

This paper presents a hybrid wavelet-fuzzy based multiresolution (MR) controller for robust speed control of induction motor. The discrete wavelet transform (DWT) is used to decompose the error between the actual speed and command speed of the induction motor drive in to different frequency components. A self-tuning fuzzy logic is used for online tuning of the controller parameters. The proposed controller has the ability of meeting the speed tracking requirements in the closed loop system. The complete indirect field oriented control scheme incorporating the proposed wavelet-fuzzy based MR controller is investigated theoretically and simulated under various dynamic operating conditions. Simulation results are compared with that of conventional PI controller and fuzzy based PI controller. The speed control scheme incorporating the proposed controller is implemented in real time using the digital processor (DSP) control board. Simulation and experimental results validates the effectiveness of the proposed controller over conventional controllers and proves to be more suitable for high performance applications.

This paper presents the topology of operating DC-DC buck converter in boost mode for extra-high-voltage applications. Traditional DC-DC boost converters are used in high-voltage applications, but they are not economical due to the limited output voltage, efficiency and they require two sensors with complex control algorithm. Moreover, due to the effect of parasitic elements the output voltage and power transfer efficiency of DC-DC converters are limited. These limitations are overcome by using the voltage lift technique, opens a good way to improve the performance characteristics of DC-DC converter. The technique is applied to DC-DC converter and a simplified control algorithm in this paper. The performance of the controller is studied for both line and load disturbances. These converters perform positive DC-DC voltage increasing conversion with high power density, high efficiency, low cost in simple structure, small ripples, and wide range of control. Simulation results along theoretical analysis are provided to verify its performance.