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This paper proposes a method for selecting the parameters of the main components of an autonomous photovoltaic (PV) stations to ensure the most efficient conversion and use of solar energy. The main energy characteristics are analyzed and the mathematical models of the components of an autonomous PV system are developed to study the modes of tracking the maximum power point (MPP). The necessary conditions for matching the parameters of the PV and the DC–DC buck converter are evaluated to track the MPP. This paper aims to create an original method and algorithm for calculating and selecting parameters of the main elements of a PV stations. The optimal value of the sampling time of the MPP controller is obtained for different schemes of the PV system . A practical example is considered for selecting the parameters of a DC–DC buck converter and a digital MPP of an autonomous PV station. The simulation of dynamic modes of an autonomous photovoltaic (PV) station is performed in the MATLAB/SIMULINK software package. The simulation results of dynamic operations of the PV system show that the voltage converter and the MPP controller with the selected parameters according to the proposed method provide reliable and effective tracking of the MPP in all different connections of the PV.

The integration of a Z-source network with a 5-Level three-phase inverter based cascaded to provide voltage step-up function is proposed in this paper. The system is controlling by an improved space vector modulation (SVM) the implantation of algorithm and innovative virtual automated solutions can be considered, very fast and very simple. The main objective of the proposed system is to achieve an output voltage twice the applied input voltage, and to eliminate the largest amount of excess harmonic. This proposed model is characterized by the ease of boosting the output voltage twice the input voltage, depending on the characteristics of the Z-source network without the need for a DC-DC rectifier. Furthermore, the proposed algorithm for this system is characterized by improving the output voltage and eliminating a large number of harmonics while greatly simplifying the calculations compared to its conventional SVM. This makes the proposed system and its algorithm an interesting alternative to classical systems and algorithms. The simulation was processed using MATLAB/Simulink. The results obtained prove and verify the effectiveness of the proposed system. From the results, of the output current total harmonic distortion (THD), it was reduced to 1.05% which is very low compared to the other algorithms in the literature.

This research introduces the simulation of photovoltaic (PV) array to track the peak point (MPPT) using fuzzy logic control. Therefore, real time simulation is performed in MATLAB/Simulink based on a PV model, boost converter and fuzzy logic-based tracker. A comparative study is carried out against perturb and observe (P&O) controller. The fuzzy logic technique based tracker can successfully track the maximum power point very fast and has precise control when compared to the P&O algorithm. The overall we conclude that the MPPT using the fuzzy logic technique takes a fast response and can improve the performance of the PV system.

Grid-connected photovoltaic (PV) systems play an important role in reducing emissions resulting from conventional fossil-fuel-based power plants. However, in order to effectively integrated PV systems into the power system, many challenges regarding these renewable resources such as extracting maximum power under various conditions should be solved. This paper suggests an enhanced maximum power point tracking (MPPT) by the fuzzy logic controller (FLC) and a modified bat algorithm (MBA) to fine-tune the parameters of the controller. The FLC is greatly affected by rule base and membership functions (MFs). The fine-tuning of such parameters cannot be appropriate when accurate information regarding the system is not available. To overcome the above-mentioned challenges, the MBA algorithm is utilized to optimize the scaling factors of MFs. Simulation results confirm that the suggested MBA-FLC method can effectively cope with the global maxima under different weather circumstances with high efficiency, faster tracking and stable output.

Power loss is a bottleneck in every power system and it has been in focus of majority of the researchers and industry. This paper proposes a new method for determining the power loss in wind-solar power system based on deep learning. The main idea of the proposed scheme is to freeze the feature extraction layer of the deep Boltzmann network and deploy deep learning training model as the source model. The sample data with closer distribution with the data under consideration is selected by defining the maximum mean discrepancy contribution coefficient. The power loss calculation model is developed by configuring the deep neural network through the sample data. The deep learning model is deployed to simulate the non-linear mapping relationship between the load data, power supply data, bus voltage data and the grid loss rate during power grid operation. The proposed algorithm is applied to an actual power grid to evaluate its effectiveness. Simulation results show that the proposed algorithm effectively improved the system performance in terms of accuracy, fault tolerance, nonlinear fitting and timeliness as compared with existing schemes.

In this article the research results of application of back-to-back HVDC system in the Tomsk electric power system are presented. Historically, power transmission between the South to the North parts of the Tomsk electric power system is realized via the long double-circuit 220 kV overhead transmission line. However, due to electrical load increasing and growing complexity of the grid, as well as the length (about 800 km) and low transfer capacity of this transit, it cannot be used as a reliable link for parallel operation of these parts, as a consequence, there is an operational section at this transit. To solve this task, the back-to-back HVDC system is proposed to provide an asynchronous link for parallel operation of these parts. Therefore, appropriate studies and calculations were performed, in particular the optimal location and sizing of back-to-back HVDC system were defined. Extra researches of back-to-back HVDC’s impact on emergency scenarios of Tomsk electric power system power are conducted. It is shown, that its installation decreases the level of short-circuit current and oscillations in electric power system, and as a result increases the stability of load operation, especially motor load.

One of the important tasks for increasing the efficiency of photovoltaic (PV) system is the development and improvement of the maximum power point tracking algorithms (MPPT). These MPPT algorithms lead to the ability to catch efficiently the global maximum power point of the partially shaded PV array. One of these trackers is the particle swarm optimization (PSO) algorithm which is one of the Soft computing techniques. The conventional PSO based trackers have many advantages such as the simplicity of hardware implementation and independence from the installed system. The actual problem of the practical application of PSO is the determination of its parameters to ensure high effectiveness of extracting the global MPP. Analysis of scientific papers devoted to the PSO algorithm has shown that there is currently no methodology for the optimal parameters' selection of PSO algorithm based maximum power trackers for the PV system. This paper aims to create a convenient and reasonable method for choosing the optimal parameters of the PSO algorithm, taking into account the topology and parameters of the DC-DC converter and the configuration of solar panels. A new method for selecting the parameters of a buck converter connected to a battery has been presented. The optimal value of the sampling time for the digital MPP controllers, providing their maximum performance; has been determined based on a new methodology. Matlab/Simulink software package is used as the main research tool. The prominent outcomes identify that the modified PSO and its designed parameters best meet the requirements of the MPPT controller for the PV system.

Recent hybrid simulators (or co-simulators) of the electric power system are focused on scientific and research features to propose and develop novel and more accurate simulators. The present paper demonstrates one more hybrid modelling approach based on application and combination of three modeling approaches all together: physical, analog and digital. The primary focus of the proposed approach is to develop the simulation tool ensuring such vital characteristics as three-phase simulation and modeling of a single spectrum of processes in electric power system, without separation of the electromagnetic and electromechanical transient stages. Moreover, unlimited scalability of the electric power system model and real-time simulation to ensure the opportunity of data exchange with external devices have been considered. The description of the development of the hybrid model of back-to-back HVDC link based on the proposed approach is discussed and analyzed. To confirm properties of the mentioned hybrid simulation approach and hybrid model of back-to-back HVDC link, the simulation results of the interconnection of non-synchronously operating parts of the electric power system; power flow regulation; dynamic response to external fault and damping of power oscillation in electric power system are presented and examined. Moreover, to confirm the adequacy of the obtained results, the comparison with a detailed voltage source converter HVDC model (Simulink Matlab) and Eurostag software are introduced.

The integration of a Z-source network with a 5-Level three-phase inverter based cascaded to provide voltage step-up function is proposed in this paper. The system is controlling by an improved space vector modulation (SVM) the implantation of algorithm and innovative virtual automated solutions can be considered, very fast and very simple. The main objective of the proposed system is to achieve an output voltage twice the applied input voltage, and to eliminate the largest amount of excess harmonic. This proposed model is characterized by the ease of boosting the output voltage twice the input voltage, depending on the characteristics of the Z-source network without the need for a DC-DC rectifier. Furthermore, the proposed algorithm for this system is characterized by improving the output voltage and eliminating a large number of harmonics while greatly simplifying the calculations compared to its conventional SVM. This makes the proposed system and its algorithm an interesting alternative to classical systems and algorithms. The simulation was processed using MATLAB/Simulink. The results obtained prove and verify the effectiveness of the proposed system. From the results, of the output current total harmonic distortion (THD), it was reduced to 1.05% which is very low compared to the other algorithms in the literature.

A maximum power point tracking (MPPT) is a method to extract the optimal operating point of the photovoltaic power generation system. Under partial shading conditions (PSC), the power voltage characteristics exhibit more than one local peaks and one global peak. This paper presents a cuckoo search (CS) algorithm to catch the global maximum power point of PV under PSC. The main contributions of this work are to minimize the tracking time and increase the tracking efficiency of the PV modules. Furthermore, this work aims to study the behavior performance of two MPPT techniques which have been designed for extracting the GMPP under the PSC. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. In addition, a step up (boost) DC–DC converter is designed and interfaced with resistive load in the proposed model. The prominent outcomes show that the CS has the best performance compared to the Perturb and observe (P&O) techniques. In addition, for all test cases, the tracking efficiency of the CS is higher than 99.97% within 150–180 ms.

This paper presents an improved particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking (GMPP) of photovoltaic (PV) array under partially shaded conditions (PSC). Under PSC, the power–voltage characteristics have a more complex shape with several local peaks and one global peak. Most of the conventional techniques that are applied in the maximum power-tracking control unit of PV stations do not provide reliable tracking of the GMPP under PSC, which leads to decrease the reliability and the performance of the PV power plant. The performances of the proposed PSO algorithm and the conventional perturb and observe algorithms are evaluated using simulations in MATLAB/Simulink. Eight different partial shading patterns have been selected to prove the robustness of the proposed algorithm. A (step-up) DC–DC boost converter is interfaced with the proposed model. The results indicate that the modified PSO algorithm can very fast track the GMPP within 150–280 ms for different shading conditions furthermore the quality of the tracked power is very high as compared with the previous studies in the literature. Also, the average tracking efficiency of the proposed PSO algorithm is higher than 99.8%, which provides good prospects to apply this algorithm in the control search unit for the GMPP in PV stations.

In real inverters' operations, it is essential to insert delay time in the pulses provided to the inverter switches to protect the DC link against the short circuits. From this situation, the dead time phenomenon is introduced that causes undesirable performance and distortion of the output signal. Previously, researchers have proposed various schemes for compensating or eliminating dead-time. In this paper, a new dead-time elimination (DTE) scheme is proposed with a guarantee algorithm to eliminate dead-time and overcome the issues produced at the zero-currents-crossing point (ZCC). This method does not require additional hardware or filters to determine the polarity of the output current, and its principle is very simple to implement. The developed DTE method completely removes the dead-time issues on the magnitude and phase of the output voltage, and avoid the problems which can be induced around the ZCC. The results confirm the effectiveness and safety of this method.

Reliability and survivability of electric power systems (EPS) depend on transient stability assessment (TSA). One of the most effective way to TSA is time-domain simulation. However, large-scale EPS mathematical model contains a stiff nonlinear system of high-order differential equations. Such system cannot be solved analytically. At the same time, numerical methods are imperfectly applied for such system due to limitation conditions. To make it appropriate, the EPS mathematical model is simplified and additional limitations are used. These simplifications and limitations reduce reliability of simulation results. Consequently, their validation is needed. The most reliable approach to provide it is to compare the simulation results with the field data. However, in practice, there are not enough data for such validation. This paper proposes an alternative approach for validation - the application of a reference model instead of field data. A hardware-software system HRTSim was used as a reference model. This power system simulator has all the necessary properties and capabilities to obtain reliable information required for comprehensive validation of transient stability calculations in EPSs. Main disturbances leading to instability in EPSs are investigated to conduct the validation (processes in cases of faults, single-phase auto-reclosing operation and power system interconnection). Fragments of corresponding experimental studies illustrate the efficiency of the proposed approach. Obtained results confirmed the possibility of the developed approach to identify the causes of numerical calculation errors and to determine disturbances calculated with the significant error. In addition, experimental studies have revealed that numerical calculations error depends on disturbances intensity.

Frequency control represents a critically significant issue for the enhancement of the dynamic performance of isolated micro grids. The micro grid system studied here was a wind−diesel system. A new and robust optimization technique called the mine blast algorithm (MBA) was designed for tuning the PID (proportional−integral−differential) gains of the blade pitch controller of the wind turbine side and the gains of the superconducting magnetic energy storage (SMES) controller. SMES was implemented to release and absorb active power quickly in order to achieve a balance between generation and load power, and thereby control system frequency. The minimization of frequency and output wind power deviations were considered as objective functions for the PID controller of the wind turbine, and the diesel frequency and power deviations were used as objective functions for optimizing the SMES controller gains. Different case studies were considered by applying disturbances in input wind, load power, and wind gust, and sensitivity analysis was conducted by applying harsh conditions with varying fluid coupling parameter of the wind−diesel hybrid system. The proposed MBA−SMES was compared with MBA (tuned PID pitch controller) and classical PI control systems in the Matlab environment. Simulation results showed that the MBA−SMES scheme damped the oscillations in the system output responses and improved the system performance by reducing the overshoot by 75% and 36% from classical and MBA-based systems, respectively, reduced the settling time by 45% compared to other systems, and set the final steady-state error of the frequency deviation to zero compared to other systems. The proposed scheme was extremely robust to disturbances and parameter variations.

A control of a three-phase four-leg autonomous voltage inverter (VSI) based on scalar PR-controllers with as part of an autonomous power supply system (APS) is presented. The proposed method independently controls each phase load voltage in the coordinate system ABC. The control system of the VSI consists of an outer control loop for controlling the load voltages and an inner control loop for controlling the output current of the VSI. To analyze the stability of the system and design the PR regulators, the root locus and the Bode diagram are used. The control signals applied for the VSI switches are provided by Scalar PWM. Studies of operating modes of APS are carried out using MATLAB/SIMULINK. The proposed method shows good tracking of the reference output voltage in the static and dynamic modes of APS.

In this study, introduces a cuckoo search (CS) algorism for determining the global maximum power point (GMPP) of photovoltaic (PV). The traditional methods are failed to track the global maximum power point under partially shaded conditions (PSC), which decrease the reliability of the power system and increase the system losses. The research results of the CS algorithm and perturb and observe (P&O) algorithm are investigated for different cases of operations of PV panels under PSC. The proposed CS model can track the GMPP very accurate with high efficiency in less time under severe weather conditions as well as in PSC.

A control of a three-phase four-leg autonomous voltage inverter (VSI) based on PID-controllers with Scalar PWM as part of an autonomous power supply system (APS) is presented. The control system of the VSI consists of an outer control loop for controlling the load voltages and an inner control loop for controlling the output current of the VSI with a feedback load current loop. To analyze the stability of the system and design the PID regulators, the root locus and the Bode diagram are used. Studies of operating modes of APS are carried out using MATLAB/SIMULINK. The proposed method shows good tracking of the reference output voltage in the static and dynamic modes of APS.

Comparative study of the methods for controlling a stand-alone voltage source inverter with a fourth leg (4-leg VSI) based on scalar pulse width modulation (PWM) and Finite control set model predictive control (FCS-MPC) as part of an autonomous power supply system are presented. The main purpose is to control 4-Leg VSI to provide balanced load voltage with lower total harmonic distortion. The discrete-time model of the autonomous 4-Leg VSI with output LC filter is pointed out for predicting the output voltage at a varying load. The PID controller is employed to provide the control reference signal for the PWM. The performances of the two control methods in tracking the load voltage under steady state and transient conditions are analyzed.

Finite control set model predictive control (FCS-MPC) is considered as a new control technique in the power electronics fields which do not require modulation stage. The absence of modulation stage results in operating under variable switching frequency which can affect the harmonic distortion of the output signal, the switching losses, filters design and so on. On the other hand, the linear controllers control the power converters with constant switching frequency by using modulators. In this paper, the overall performance of FCS-MPC is assessed by performing a comparative study with a linear controller based on scalar pulse width modulation (PWM). The control systems are applied on an autonomous four-leg voltage source inverter (VSI) with LC filter as part of an autonomous power supply system. The main purpose of the two control techniques is to control four-leg VSI to provide balanced load voltage with lower total harmonic distortion. The steady state performance of the two control techniques is tested under balanced, unbalanced, linear and nonlinear load conditions. Moreover, the effect of the load variations on the switching frequency of the FCS-MPC is discussed. Finally, the performances of the two control methods in tracking the reference voltage under transient conditions are analysed.

This paper presents optimal parameters selection of particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking of photovoltaic array under partially shaded conditions. Under partial shading, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. The two proposed controllers include dynamic Particle Swarm Optimization, and constant particle swarm optimization. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. The results indicate that the dynamic particle swarm optimization algorithm can very fast track the GMPP within 128 ms for different shading conditions. In addition, the average tracking efficiency of the proposed algorithm is higher than 99.89%, which provides good prospects to apply this algorithm in the control search unit for the global maximum power point in stations.

A novel predictive control algorithm is proposed for predicting and regulating the load voltages of a four-leg inverter in an autonomous three-phase four-wire power supply system (APS). The control algorithm is developed to reduce the number of the mathematical operations required for the control system without affecting the control performance. The current information about the APS with its load voltages prediction is processed by using a discrete-time state space model. The simulation results show a good control performance in regulating the load voltages?, with fewer mathematical computations, under various load conditions?

The partial shading condition (PSC) often occur in large photovoltaic (PV) generation system (PGS), it causes system losses and many problems in reliability of power system. The power voltage ( p-v) curve under the PSC have more peaks local and global peak and this makes the track of maximum power is very difficult and the conventional algorithms can't track the global maximum power point in this case. In this paper, the maximum power point tracking (MPPT) under PSC are evaluated using the particle swarm optimization (PSO). The proposed model tracks the global maximum power point (GMPP) very fast and in very short time and don't exceed 30 iterations under minimum solar irradiation cases.

This paper presents a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) tracking of photovoltaic (PV) under partial shading conditions (PSC). The conventional methods are fail to track the GMPP under PSC, which decrease the reliability of the power system and increase the system losses. The performance of the CS algorithm is compared with perturb and observe (P&O) algorithm for different cases of operations of PV panels under PSC. The CS algorithm used in this work to control directly the duty cycle of the DC-DC converter without proportional integral derivative (PID) controller. The proposed CS model can track the GMPP very accurate with high efficiency in less time under different conditions as well as in PSC.

In the microgrid systems, three-phase inverter becomes the main power electronic interface for renewable distributed energy resources (DERs), especially for the islanded microgrids in which the power quality is easily affected by unbalanced and nonlinear loads, this is due to the fact that the voltage and frequency of the microgrid are not supported by the main power grid but determined only by the inverters. Therefore, the compensation of the load unbalances and harmonics in autonomous microgrid inverters are getting more attention in power quality research areas. The main purpose of this paper is to represent an overview of the control strategies of various inverters for unbalanced load compensation