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The purpose of the research is to address the underutilization of electric machine-based propulsion in transportation despite its numerous advantages over conventional internal combustion engines (ICE), such as reduced emissions, lower fuel costs, and improved control and operation. To achieve this goal, the study reviews state-of-the-art energy sources, storage devices, power converters, and control strategies used in electric vehicles (EVs). It particularly focuses on the implementation of the five-level charging scheme for Lithium-ion (Li-ion) batteries, which are considered a promising solution for electric vehicle power storage. The important results of this work include the advantages of a five-level charging scheme for a 1Ah, 3.7V Li-ion battery compared with conventional charging methods, i.e., superior efficiency (97.16%), lower temperature rise (1.5 degrees Celsius), faster charging times (around 40-43 minutes), and extended battery lifespan. The significance of these results lies in their potential to address key drawbacks hindering the widespread adoption of plug-in hybrid electric vehicles (PH EVs) by offering a practical solution for faster, more efficient, and safer battery charging. By isolating the battery during charging and optimizing the charging process, the proposed system not only enhances the performance of electric vehicles but also contributes to prolonging the battery life, thus promoting sustainability in transportation. Additionally, the experimental validation using MATLAB Simulink underscores the practical feasibility of the proposed charging system, providing a valuable contribution to the field of electric vehicle technology.

Introduction. The renewable integrated microgrid has considered several distributed energy sources namely photovoltaic power plant, thermal generators, wind power plant and combined heat and power source. Economic dispatch problem is a complex operation due to large dimension of power systems. The objective function becomes non linear due to the inclusion of many constraints. Hourly demand of a commercial area is taken into consideration for performing economic dispatch and five combinations are considered to find the best optimal solution to meet the demand. The novelty of the proposed work consists of a Sparrow Search Algorithm is used to solve economic load dispatch problem to get the better convergence and accuracy in power generation with minimum cost. Purpose. Economic dispatch is performed for the renewable integrated microgrid, in order to determine the optimal output of all the distributed energy sources present in the microgrid to meet the load demand at minimum possible cost. Methods. Sparrow Search Algorithm is compared with other algorithms like Particle Swarm Optimization, Genetic Algorithm and has been proved to be more efficient than Particle Swarm Optimization, Genetic Algorithm and Conventional Lagrange method. Results. The five combinations are generation without solar power supply system and Combined Heat and Power source, generation without solar and wind power supply systems, generation including all the distributed energy sources, generation without wind power supply system and Combined Heat and Power source, generation without thermal generators. Practical value. The proposed optimization algorithm has been very supportive to determine the optimal power generation with minimal fuel to meet the large demand in commercial area.

In a hybrid renewable system, a conventional boost converter produces more losses at the time of the energy conversion process due to this, the performance of the hybrid system is reduced total harmonic distortion is increased, and the hybrid microgrid outcome is reduced. The main objective of the work enhancing the low DC voltage produced by the PV panel, a high gain Boost converter is utilized. The objectives of the work were achieved by a High Gain Modified Z-source Boost converter along with Modified Particle Swarm Optimized- Proportional Integral (MPSO-PI) controller employed in the energy conversion stage at Grid. It reduced power conversion stages and decreases the losses compared to existing Hybrid Grid-connected systems. A new 13-bus system is developed in this work for regulating the output voltage in distribution networks. The significance of our work lies in the design of an efficient microgrid system for grid-tied applications. High Gain Modified Z-source Boost converter along with Modified Particle Swarm Optimized- Proportional Integral (MPSO-PI) controller is employed to boost the voltage obtained from the PV system. A battery converter along with a bi-directional battery is connected to the DC link, to store energy generated by Hybrid Renewable Energy System (HRES) in excess amounts. The obtained DC link voltage is transferred to Three Phase VSI for the conversion of DC to AC voltage. Effective harmonic reduction is attained with the aid of an LC filter coupled to Three Phase grid, and the PI controller connected to Voltage Source Inverter(VSI) supports achieving effective grid synchronization. The proposed work was tested with 13 bus system through MATLAB Simulink.

Purpose. This article proposes a new control strategy for KY (DC-DC voltage step up) converter. The proposed hybrid energy system fed KY converter is utilized along with adaptive neuro fuzzy interface system controller. Renewable energy sources have recently acquired immense significance as a result of rising demand for electricity, rapid fossil fuel exhaustion and the threat of global warming. However, due to their inherent intermittency, these sources offer low system reliability. So, a hybrid energy system that encompasses wind/photovoltaic/battery is implemented in order to obtain a stable and reliable microgrid. Both solar and wind energy is easily accessible with huge untapped potential and together they account for more than 60 % of yearly net new electricity generation capacity additions around the world. Novelty. A KY converter is adopted here for enhancing the output of the photovoltaic system and its operation is controlled with the help of a cascaded an adaptive neuro fuzzy interface system controller. Originality. Increase of the overall system stability and reliability using hybrid energy system fed KY converter is utilized along with adaptive neuro fuzzy interface system controller. Practical value. A proportional integral controller is used in the doubly fed induction generator based wind energy conversion system for controlling the operation of the pulse width modulation rectifier in order to deliver a controlled DC output voltage. A battery energy storage system, which uses a battery converter to be connected to the DC link, stores the excess power generated from the renewable energy sources. Based on the battery’s state of charge, its charging and discharging operation is controlled using a proportional integral controller. The controlled DC link voltage is fed to the three phase voltage source inverter for effective DC to AC voltage conversion. The inverter is connected to the three phase grid via an LC filter for effective harmonics mitigation. A proportional integral controller is used for achieving effective grid voltage synchronization. Results. The proposed model is simulated using MATLAB/Simulink, and from the obtained outcomes, it is noted that the cascaded adaptive neuro fuzzy interface system controller assisted KY converter is capable of maintaining the stable operation of the microgrid with an excellent efficiency of 93 %.

Purpose. This article proposes a new control monitoring grid connected hybrid system. The proposed system, improvement of power quality is achieved with internet of things power monitoring approach in solar photovoltaic grid system network. The novelty of the proposed work consists in presenting solar power monitoring and power control based internet of things algorithm, to generate DC voltage and maintain the constant voltage for grid connected hybrid system. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for measuring the fault and as maximum power point tracking assures controlled output and supports the extraction of complete power from the photovoltaic panel. The objective of the work is to monitor and control the grid statistics for reliable and efficient delivery of power to a hybrid power generation system. Internet of things is regarded as a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. The proposed control technique strategy is validated using MATLAB/Simulink software and real time implementation to analysis the working performances. Results. The results obtained show that the power quality issue, the proposed system to overcome through monitoring of fault solar panel and improving of power quality. The obtained output from the hybrid system is fed to the grid through a 3ϕ voltage source inverter is more reliable and maintained power quality. The power obtained from the entire hybrid setup is measured by the sensor present in the internet of things-based module. In addition to that, the photovoltaic voltage is improved by a boost converter and optimum reliability is obtained with the adoption of the perturb & observe approach. The challenges in the integration of internet of things – smart grid must be overcome for the network to function efficiently. Originality. Compensation of power quality issues, grid stability and harmonic reduction in distribution network by using photovoltaic based internet of things approach is utilized along with sensor controller. Practical value. The work concerns a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. In this paper, internet of things sensors are installed in various stages of the smart grid in a hybrid photovoltaic –wind system. It tracks and manages network statistics for safe and efficient power delivery. The study is validated by the simulation results based on MATLAB/Simulink software and real time implementation.

Purpose. This article proposes a new control strategy for static synchronous compensator in utility grid system. The proposed photovoltaic fed static synchronous compensator is utilized along with recurrent neural network based reference voltage generation is presented in grid system network. The novelty of the proposed work consists in presenting a Landsman converter enhanced photovoltaic fed static synchronous compensator with recurrent neural network algorithm, to generate voltage and maintain the voltage-gain ratio. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for utilization of adaptive neuro-fuzzy inference system as maximum power point tracking assures controlled output and supports the extraction of complete power from the photovoltaic panel. Grid is interconnected with solar power, voltage phase angle mismatch, harmonic and voltage instability may occur in the distribution grid. The proposed control technique strategy is validated using MATLAB/Simulink software and hardware model to analysis the working performances. Results. The results obtained show that the power quality issue, the proposed system to overcome through elimination of harmonics, reference current generation is necessary, which is accomplished by recurrent neural network. By recurrent neural network, the reference signal is generated more accurately and accordingly the pulses are generated for controlling the inverter. Originality. Compensation of power quality issues, grid stability and harmonic reduction in distribution network by using photovoltaic fed static synchronous compensator is utilized along with recurrent neural network controller. Practical value. The work concerns the comparative study and the application of static synchronous compensator with recurrent neural network controller to achieve a good performance control system of the distribution network system. This article presents a comparative study between the conventional static synchronous compensator, static synchronous compensator with recurrent neural network and hardware implementation with different load. The strategy based on the use of a static synchronous compensator with recurrent neural network algorithm for the control of the continuous voltage stability and harmonic for the distribution network-linear as well as non-linear loads in efficient manner. The study is validated by the simulation results based on MATLAB/Simulink software and hardware model.

Purpose. This article proposes a new control strategy for Dynamic Voltage Restorer (DVR) in utility grid for distribution system. The proposed DVR using PI tuned fuzzy logic scheme is based on replacement of conventional DVR and voltage sag compensation in distribution system network. The novelty of the proposed work consists in presenting an enhanced PI tuned fuzzy logic algorithm to control efficiently the dynamic voltage restorer when voltage sag is suddenly occurred. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for power quality problems. Our strategy is based on tuned fuzzy control of reactive powers and also closed loop for harmonic reduction in distribution system. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that DVR using PI tuned fuzzy logic have good performances (sag compensation, harmonic reduction) compared to conventional DVR. Originality. Compensation of voltage sag/ swell in distribution for reactive power and current harmonic reduction by using DVR based PI tuned fuzzy logic controller. Practical value. The work concerns the comparative study and the application of DVR based on PI tuned fuzzy techniques to achieve a good performance control system of the distribution system. This article presents a comparative study between the conventional DVR control and PI tuned fuzzy DVR control. The strategy based on the use of a PI tuned fuzzy controller algorithm for the control of the continuous voltage sag and harmonic for the distribution network-linear as well as non-linear loads in efficient manner. The study is validated by the simulation results based on MATLAB / Simulink software.