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As an agriculturally based country, many rivers pumping stations are implemented in Myanmar. Currently, these pumping stations are operated with utility supply or diesel engines. For reliable energy supply and energy cost saving, the solar powered river pumping stations are now carried out in Myanmar. Most of these pumping stations are located at the dry zones especially at Magway, Mandalay and Sagaing Divisions. The main problem with solar powered river pumping station is the harmonic induced due to DC/DC boost converter and three phase inverters. Harmonics are the important problem in solar river water pumping system as they can shorten the life span of pumping motors and vibrations. Thus, harmonic filters become the main function of these system. In this research, the harmonic mitigation for Kanni river pumping system is executed using active and hybrid harmonic filter and their performances are compared. In this work, solar river water pumping system is designed firstly, and then modelled and simulated using MATLAB/Simulink. Harmonic contents and mitigation performances of each filter are analysed using Fast Fourier Transform (FFT) tool.

The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source three phase inverter and Boost converter is controlled by proportional-integral (PI) controller. Based on the BLDC drive, the load utilized from the solar generating module. Experimental results analyzed every module of the proposed grid system, which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics (PV) power is generated and the QPSO with Duty cycle switching state is determined. The Boost converter module is boost stage based on generation and load is obtained. Single Ended Primary Inductor Converter (SEPIC) and Zeta converter model is compared with the proposed logic; the proposed boost converter achieves the results. Three phase inverter control, PI, and BLDC motor drive results. Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures. Overall design model is done by using MATLAB/Simulink 2020a. [ABSTRACT FROM AUTHOR]

Solar energy can function as a supplementary power supply for other renewable energy sources. On average, Vellore region experiences approximately six hours of daily sunshine throughout the year. Solar photovoltaic (PV) modules are necessary to monitor and fulfill the energy requirements of a given day. An artificial neural network (ANN) based maximum power point tracking (MPPT) controller is utilised to regulate the solar photovoltaic (PV) array and enhance its output. The utilisation of this controller can enhance the efficiency of the module even in severe circumstances, where reduced current and torque ripples will be observed on the opposite end. The motorised vehicle has the capability to function at its highest torque level in different load scenarios as a result. The proposed method is expected to provide advantages in various electric vehicle (EV) applications that require consistent velocity and optimal torque to satisfy the load conditions. The study employs a solar battery that is linked to an SVPWM inverter and subsequently a DC-DC boost converter to supply power to the load. An Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) control system is proposed for a solar battery powered Electric Vehicle (EV) and the system's performance is evaluated by collecting and analysing data under adjustable load conditions to obtain constant parameters such as speed and torque. The MATLAB® Simulink® model was utilised for this purpose. [ABSTRACT FROM AUTHOR]

In order to improve the rapidity and immunity of microgrid inverter response, an inverter control structure with augmented state feedback plus dynamic feedforward is designed. The control structure is based on the augmented state feedback, robust mutual mass decomposition and Youla parameterisation theory, which can get the augmented state feedback control parameters and feedforward control structure, and the specific expression of feedforward controller is obtained by model matching theory, after which the Current loop compensation structure is added by combining the inverter and controller structures. The load switching and three-phase unbalance experiments are designed by Matlab/Simulink. The results show that without changing the structural parameters of the original system, the new controller can quickly stabilise the voltage fluctuation within 20 ms, change the fluctuation from 15 V to 2 V, and reduce the unbalance degree from 4% to less than 1%, effectively improving the response speed and anti-interference performance of the whole system, The speed and robustness of the inverter are improved.

The synchronization between the grid and inverter is crucial for power sharing. By reconnecting the inverter to the electrical grid, it becomes possible to provide power in grid-off mode. Inverter-interfaced distributed generators (DGs) rely on control methods to drive the power devices in the inverter. A three-phase inverter produces output in terms of voltage, frequency, and phase, which can be matched with the electrical output using control methods. These control methods determine the pulse width modulation (PWM) pulses for driving the inverter. Simulations of the proposed systems with a grid-connected inverter are expressed through a MATLAB SIMULINK Model. Various algorithms generate different PWM pulses for the inverter. The differences between these algorithms are summarized in the results. Finally, the simulation results are analyzed across the load, total harmonic distortion (THD), error in grid voltage, and inverter voltage.

Solar energy can function as a supplementary power supply for other renewable energy sources. On average, Vellore region experiences approximately six hours of daily sunshine throughout the year. Solar photovoltaic (PV) modules are necessary to monitor and fulfill the energy requirements of a given day. An artificial neural network (ANN) based maximum power point tracking (MPPT) controller is utilised to regulate the solar photovoltaic (PV) array and enhance its output. The utilisation of this controller can enhance the efficiency of the module even in severe circumstances, where reduced current and torque ripples will be observed on the opposite end. The motorised vehicle has the capability to function at its highest torque level in different load scenarios as a result. The proposed method is expected to provide advantages in various electric vehicle (EV) applications that require consistent velocity and optimal torque to satisfy the load conditions. The study employs a solar battery that is linked to an SVPWM inverter and subsequently a DC-DC boost converter to supply power to the load. An Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) control system is proposed for a solar battery powered Electric Vehicle (EV) and the system’s performance is evaluated by collecting and analysing data under adjustable load conditions to obtain constant parameters such as speed and torque. The MATLAB® Simulink® model was utilised for this purpose.

The selection, sizing, and management of energy storage system for an electric vehicle (EV) are critical while considering later's large-scale deployment. The complementary nature of battery and ultracapacitor (UC) makes the combination a suitable hybrid energy storage system (HESS) for EV since the peak to average power demand ratio is very high especially for an urban drive commonly characterized by frequent acceleration and deceleration. A suitably sized UC combined with the battery pack provides necessary high power density as well as high energy density. The HESS makes the EV more effective with improved dynamic response, higher kilometers per charge, and longer battery life. This paper presents a fuzzy logic control based power management strategy to employ UC to relieve the battery of peak discharge currents as well as rapid charging currents. The power conditioning unit limits the battery current as well as its rate of change by maintaining the UC state of charge in the desired limits. The paper presents some of the key simulation and experimental results for a prototype EV system tested for various modes of operations. [ABSTRACT FROM AUTHOR]

This article presents control techniques for the critical conduction mode(CRM) based high-frequency soft-switching three-phase inverter under unbalanced grid conditions. The soft-switching technique with silicon carbide (SiC) power devices allows the inverter to operate at hundreds of kHz with high efficiency and high power density. To extend the soft-switching technique to more practical cases, behaviors of the inverter under unbalanced grid conditions, specifically voltage sag, are investigated. During the voltage sag, the ac voltage at the grid becomes unbalanced. This requires unbalanced ac current reference to avoid output active power oscillation. With the unbalanced grid voltage and the ac current reference, the inverter loses the soft-switching capability. Continuous conduction mode (CCM) operation occurs where discontinuous conduction mode (DCM) operation is intended leading to large turn-on loss. To eliminate the CCM issue, two improved modulation techniques are proposed by using off-time extension in the CRM phase and by skipping pulses in the DCM phase. This article discusses how the CCM operation arises and details the proposed control methods. The performance of the proposed control is validated experimentally under a variety of grid imbalance cases with an SiC-based three-phase inverter prototype. [ABSTRACT FROM AUTHOR]

This paper deals with a comparison of inverter types and develops a system to provide pure sine wave ac voltage. The ac voltage is utilized to drive the compressor ac split. The assembled inverter problem is a square waveform, power losses, torque, efficiency, and a lag behind in terms of performance reliability. The push-pull amplifiers technic is proposed to produce sine wave output from dc input. The output result shows that an experimental pure sin wave obtains a frequency of 50.05 Hz, V max 13.49 Volt, V min -14.49 volt, and duty cycle 50.1%. the assembled inverter has a frequency is 37.87 Hz, V max 11.88 Volt, V min 13.09 volt, and a duty cycle is 50 %. A modified 3-phase inverter attains frequency 50.05 Hz, V max 15.71 Volt, V min -16.11 Volt, and the duty cycle is 50.5 %. The frequency, v max, v min, and duty cycle are bigger than an assembled inverter, then the modified 3-phase inverter has small harmonic distortion. The comparison of inverter types gives information for home appliances.

This paper simulates a Three-Phase Inverter (TPI) for proton exchange membrane fuel cells with fewer switches. It can also serve as a source for the production of stable electrical energy. Unlike the traditional 6-key 3-phase inverter, this paper proposes a 3-phase inverter with fewer switches. For real-time implementation, this can reduce the amount of computation. Fewer switches with lower switching losses, easy understanding control algorithm, and smaller in interface circuitry. [ABSTRACT FROM AUTHOR]

Grid connected inverter controllers require the magnitude and phase of the point of common coupling voltage for the generation of unit vectors from a phase locked loop. However, weak grid conditions or grid voltage sensor failures might substantially increase control difficulty in the inverter due to unknown grid impedance which causes instability in the phase locked loop. In this paper, an internal model based grid voltage estimation architecture has been presented. The proposed control architecture relies on the current measurements along with nominal values of filter parameters for the point of common coupling voltage estimation and unit vector generation. Detailed stiffness and robustness analyses are presented to show that the proposed control and estimation architecture is nearly insensitive to parameter variations. In comparison to conventional current control with both voltage and current sensors, the proposed current control scheme provides better transient response during both ideal and non-ideal grid voltage conditions. Experimental results on a reduced scale laboratory prototype validate the efficacy of the proposed architecture. [ABSTRACT FROM AUTHOR]

In this article, real-time monitoring, control and operation of the power generation of Şenyurt (Erzurum/Turkey) Solar Power Plant (SPP) with a three-phase central inverter topology is discussed. In the study, firstly, the power generation model of Şenyurt SPP with direct grid feed and central inverter topology was examined. Secondly, the data obtained by means of solar radiation sensor, Photovoltaic (PV) panel temperature sensor, outdoor temperature sensor and wind speed sensor, which are vital for monitoring and controlling the power generation of SPP, were evaluated. Real-time data obtained from these sensors were obtained with the help of a remote monitoring interface compatible with the Central Control and Data Acquisition (SCADA) system in the SPP. With the data of the sensors, the graphs obtained regarding the change of one-day active power generation of the SPP are interpreted. Thus, the operational inspection of the SPP for uninterrupted active power generation was carried out. Finally, practical field applications such as cleaning the snow accumulated on the PV panel surface, detection of hot zone faults in PV panels, measurement of current-voltage (I-V) characteristics of PV panel arrays, which are necessary for efficient power generation in the solar power plant, are also included. [ABSTRACT FROM AUTHOR]

The paper primarily focuses on water pump irrigation by operating the three phase induction motor, using photovoltaic supply. In many far away regions, mainly in villages, the main hindrance in agricultural production is the sole dependence on electricity. Up till now, solar application employed for DC motors throughout the world because of its simplicity and torque controlling techniques. In addition to it, regular maintenance of brushes and commutator is mandatory. Also it is not possible to replace all, already installed three phase induction motors with DC motors. A three phase induction motor with the help of inverter performs robustly. The primary goal of this paper is to study a DC-DC converter and DC-three phase inverter, to integrate three phase induction motor. The exploratory results satisfied the targets as it was effectively managed as a water pump with optimal efficiency and cost, using three phase induction motor. [ABSTRACT FROM AUTHOR]

Now a day's, Photo Voltaic (PV) power generation rapidly increasing. This power generation highly depending on the temperature and irradiation. When this power interface with grid through the voltage source inverter with PI controller. Its gains should be updated due to the parametric changes for the better performance. In This Work Fuzzy Controller updates the gains of the proportional integral (PI)s Controller under variable parametric conditions. the gaines of the PI Controller are updated based on the error current and change in error current through the fuzzy controller. The error current in direct and quadrature frame are the Inputs to the PI controller. The PI Controller generates the reference voltage to the pulse width modulation technique. Here reference voltage is compared with the carrier signal to generate the pulses to the 3-Ph Inverter connected to the grid. This controller has given well dynamic response with less steady state error and also given The less THD of the grid current compared to the PI and Fuzzy controller. It Is implemented and verified in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

A two-stage stand-alone scheme consisting of a transformer coupled dual input converter (TCDIC) followed by a conventional three phase full-bridge inverter used for motor driving applications in the area of farming aiming for rural deployment is proposed in this paper. Here battery is used as the energy storage element. This paper is proposed to address the issues involved with the existing system. Solar photovoltaic (PV)- based standalone systems have evolved as a promising solution to the issue of electrification in areas where the grid is not available. The major challenges that are faced by the existing system are : 1) to extract the maximum PV power from the array; 2) to protect the battery from overcharging and over discharging; 3) to covert dc to ac in order to fed the motor. These objectives were satisfied by employing a minimum of three converter stages. This will leads to reduction in reliability and efficiency of the system. The dedicated converter cannot be utilized properly if the PV power remains unavailable for more than half a day. The use of additional converters will increase the component count. The TCDIC can be used to realize maximum power point tracking and proper battery charge control can be maintained. A suitable control strategy for the proposed TCDIC is devised .Simple and efficient control structure is developed for proper operating mode selection and smooth transition between different possible modes. A three phase inverter feeds the motor which is connected at the load terminal. This paper is focused towards the motor driving application. The operation of the existing scheme is verified by using Mat lab simulation studies. [ABSTRACT FROM AUTHOR]