PSIM Software Package Research Articles

Online Control of Smart Inverter for Photovoltaic Power Generation Systems in a Smart Grid

The main purpose of this study is to engage in research on a grid-connected photovoltaic (PV) power generation system smart inverter. The research content includes a smart maximum power point tracking (MPPT) controller and an inverter with power regulation. First, use the PSIM software package to establish the simulation environment of the grid-connected photovoltaic power generation system and use the Sanyo HIP-186BA19 photovoltaic module to form a 744 W system for simulation. In order to enable the photovoltaic module array (PVMA) to output the maximum power under different solar insolation and ambient temperature, the architecture is based on the extension theory-based smart MPPT method to improve the dynamic response and steady-state performance of photovoltaic power generation systems compared to perturb and observed (P&O) MPPT. When the sunshine is 1,000 W/m2, the photovoltaic power generation system adopts the extension theory-based maximum power tracking method. The time required to track the maximum power point is only 0.32 s, and the steady-state ripple is only 4.127 W. However, using the traditional P&O method requires 0.741 s to track the maximum power point, and the steady-state ripple reaches 18.131 W. Thus, the dynamic response speed of the maximum power tracking method proposed is 50% faster than that of the P&O method. The steady-state performance is also better compared to the P&O method. At the same time, a simple proportional-integral (PI) controller is used to regulate the DC-link voltage, output voltage, and current of the inverter to make the voltage of the grid-connected point stable at an effective value of 220 V. Then, the voltage-power control technology is added to the photovoltaic grid-connected inverter, and a simple proportional-integral controller is used to regulate the output of the smart inverter reactive power to improve the power quality of grid voltage. Finally, simulation and experimental results are used to verify the effectiveness of the regulation performance of the developed smart inverter.

Comparative Analysis of Chopper-Inverter Performances for Wind Conversion System Connected to Grid

PurposeThe purpose of this paper is to propose an efficient current control technique based on model predictive control (MPC) for grid-connected wind conversion system. This nonlinear strategy is applied for the chopper circuit and grid-tied inverter and compared with other two conventional schemes; a traditional proportional-integral (PI) and sliding mode controller (SMC) using the same switching frequency.Design/methodology/approachFirstly, the MPC scheme uses the mathematical model to predict future behaviors of the controlled converter outputs for possible switching states. After that, the optimal voltage vector is selected by minimizing a cost function, which is defined as a sum of the absolute values of the controlled current errors. Then, the corresponding switching signals are applied to the converter switches in the next sampling period to track correctly the reference current. Thus, the MPC scheme ensures a minimal error between the predicted and reference trajectories of the considered variables.FindingsThe MPC-based algorithm presents several benefits in terms of high accuracy control, reduced DC-link voltage ripples during steady-state operation, faster transient response, lower overshoots and disturbance rejection and acceptable total harmonic distortion.Originality/valueThe authors introduce several simulation case studies, using PSIM software package, which prove the reliability and effectiveness of the proposed MPC scheme. Therefore, the MPC performances, during dynamic and steady-state condition, are compared with those obtained by a PI regulator and SMC to highlight the improvements, specifically the transfer of smooth power to the grid.

Improving the delivered power quality from WECS to the grid based on PMSG control model

Renewable energy has become one of the most energy resources nowadays, especially, wind energy. It is important to implement more analysis and develop new control algorithms due to the rapid changes in the wind generators size and the power electronics development in wind energy applications. This paper proposes a grid-connected wind energy conversion system (WECS) control scheme using permanent magnet synchronous generator (PMSG). The model works to improve the delivered power quality and maximize its value. The system contained one controller on the grid side converter (GSC) and two simulation packages used to simulate this model, which were PSIM software package for simulating power circuit and power electronics converters, and MATLAB software package for simulating the controller on Simulink. It employed a meta-heuristic technique to fulfil this target effectively. Mine-blast algorithm (MBA) and harmony search optimization technique (HSO) were applied to the proposed method to get the best controller coefficient to ensure maximum power to the grid and minimize the overshoot and the steady state error for the different control signals. The comparison between the results of the MBA and the HSO showed that the MBA gave better results with the proposed system.

Fault Diagnosis and Tolerant Control of Three-Level Neutral-Point Clamped Inverters in Motor Drives

This paper presents an extension theory-based assessment method to perform fault diagnosis for inverters in motor driving systems. First, a three-level neutral-point clamped (NPC) inverter is created using the PSIM software package to simulate faults for any power transistor in the NPC-type inverter. Fast Fourier transformation is used to transform the line current signals in the time domain into a spectrum in the frequency domain for analysis of the corresponding spectrum of features of the inverter for faults with different power transistors. Then, the relationships between fault types and specific spectra are established as characteristics for the extension assessment method, which is then used to create a smart fault diagnosis system for inverters. Fault-tolerant control (FTC) is used here when the rated output of a faulty inverter is decreased in order to maintain balanced output in three phases by changing the framework of the transistor connection. This is performed to reinforce the reliability of the inverter. Finally, by the simulation and experimental results, the feasibility of the proposed smart fault diagnosis system is confirmed. The proposed fault diagnosis method is advantageous due to its minimal use of data and lack of a learning process, which thereby reduces the fault diagnosis time and makes the method easily used in practice. The proposed fault-tolerant control strategy allows both online and smooth switching in the wiring structure of the inverter.

Analysis and electronic implementation of an absolute memristor autonomous Van der Pol-Duffing circuit

In this paper, a memristor-based chaotic circuit is built by replacing the nonlinear resistor of a unified Van der Pol-Duffing circuit by an ideal and active flux-controlled memristor with an absolute value nonlinearity. The equilibrium points of the mathematical model describing the proposed absolute memristor Van der Pol-Duffing circuit are determined and their stabilities are analyzed thank to the Routh-Hurwitz criteria. The numerical simulations reveal that the proposed absolute memristor circuit exhibits reverse period-doubling to chaos, bistable one-scroll chaotic attractors, double-scroll chaotic attractor, bistable periodic attractors and antimonotonicity phenomenon. Moreover the proposed absolute memristor circuit is implemented in PSIM software package. The results found using the PSIM software package have a good qualitative agreement with those found during the numerical simulations.

An Intelligent Fault Diagnosis Method Based on Extension Theory for DC–AC Converters

In this paper, an extension evaluation method was proposed to diagnose the fault of a DC–AC converter in a motor drive system. First, the PSIM software package was used to construct a three-level neutral point clamped (NPC) DC–AC converter for simulating the occurrence of the fault of any power transistor in the NPC DC–AC converter. Simultaneously, the fast Fourier transform was adopted to transcribe the waveform of phase voltage in time domain into the spectrum in frequency domain, looking for the corresponding characteristic spectrum during the fault of the power transistor in a DC–AC converter. Then, we establish the relationship between the fault type and the specific spectrum as the characteristics of the extension evaluation method, building up a fault diagnosis system for a DC–AC converter. Finally, the simulation results are made to demonstrate the feasibility of the proposed intelligent fault diagnosis system.

A Low Cost Single-Switch Bridgeless Boost PFC Converter

This paper proposes the single-switch bridgeless boost power factor correction (PFC) converter to achieve high efficiency in low cost. The proposed converter utilizes only one active switching device for PFC operation as well as expecting higher efficiency than typical boost PFC converters. On the other hand, the implementation cost is less than traditional bridgeless boost PFC converters, in where two active switching deivces are necessary. The operational principle, the modeling, and the control scheme of the proposed converter are discussed in detail. In order to verify the operation of the proposed converter, a 500W switching model is built in PSIM software package. The simulation results show that the proposed converter perfectly achieves PFC operation with only a single active switch. DOI: http://dx.doi.org/10.11591/ijpeds.v4i2.5558

A hybrid real coded genetic algorithm – Pattern search approach for selective harmonic elimination of PWM AC/AC voltage controller

Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package. Finally, these results are verified by means of an experimental prototype.

A Maximum Power Point Tracker with Automatic Step Size Tuning Scheme for Photovoltaic Systems

The purpose of this paper is to study on a novel maximum power point tracking (MPPT) method for photovoltaic (PV) systems. First, the simulation environment for PV systems is constructed by using PSIM software package. A 516 W PV system established with Kyocera KC40T photovoltaic modules is used as an example to finish the simulation of the proposed MPPT method. When using incremental conductance (INC) MPPT method, it usually should consider the tradeoff between the dynamic response and the steady-state oscillation, whereas the proposed modified incremental conductance method based on extension theory can automatically adjust the step size to track the maximum power point (MPP) of PV array and effectively improve the dynamic response and steady-state performance of the PV systems, simultaneously. Some simulation and experimental results are made to verify that the proposed extension maximum power point tracking method can provide a good dynamic response and steady-state performance for a photovoltaic power generation system.

A novel neural network with simple learning algorithm for islanding phenomenon detection of photovoltaic systems

This study aimed to propose an intelligent islanding phenomenon detection method for a photovoltaic power generation system. First, a PSIM software package was employed to establish a simulation environment of a grid-connected photovoltaic (PV) power generation system. A 516W PV array system formed by Kyocera KC40T photovoltaic modules was used to complete the simulation of the islanding phenomenon detection method. The proposed islanding phenomenon detection technology was based on an extension neural network (ENN), which combined the extension distance of extension theory, as well as the learning, recalling, generalization and parallel computing characteristics of a neural network (NN). The proposed extension neural network was used to distinguish whether the trouble signals at the grid power end were power quality interference or actual islanding operations, in order that the islanding phenomenon detection system could cut off the load correctly and promptly when a real islanding operation occurs. Finally, the feasibility of the proposed intelligent islanding detection technology was verified through simulation results.

PWM methods for two-phase inverters

This article focuses on simple space-vector PWM (SPWM) methods for two-leg, three-leg, and four-leg inverters that can be applied to three phase induction motor drives (TPIM). First, a carrier-based PWM method for a two-leg inverter was proposed on the basis of the conventional SPWM method. Second, a carrier-based PWM method for a four leg inverter that used a double triangular carrier wave was proposed. Third, a carrier-based PWM method for a three-leg inverter was proposed as a replacement for a conventional SVPWM method. Digital calculations using the PSIM software package are performed to investigate the effectiveness of the proposed PWM method

Modeling and fault diagnosis of a photovoltaic system

In this paper, a circuit-based simulation model of a photovoltaic (PV) panel by PSIM software package is developed, firstly. Then, a 3 kW PV arrays established by using the proposed PSIM model with series and parallel connection is not only employed to carry out the fault analysis, but also to represent its I– V and P– V characteristics at variable surface temperatures and isolations under normal operation. Finally, a novel extension diagnosis method based on the extended correlation function and the matter-element model was proposed to identify the faulting types of a 3 kW PV system. The simulated results indicate that the proposed fault diagnosis method can detect the malfunction types correctly and promptly.

A Hybrid Genetic Algorithm for Selective Harmonic Elimination PWM AC/AC Converter Control

This paper presents an optimal solution for eliminating pre-specified orders of harmonics from the output waveform of AC/AC converter. The main challenge of solving the associated nonlinear equations, which are transcendental in nature and therefore have multiple solutions, is the convergence and therefore an initial point selected considerably close to the exact solution is required. The paper discusses an efficient hybrid real coded genetic algorithm (HRCGA) that reduces significantly the computational burden resulting in a fast convergence. An objective function describing a measure of effectiveness of eliminating selected orders of harmonics, while controlling the fundamental is derived and a comparison of different operating points is reported. It is observed that the modulation index can reach unity value. The theoretical findings are verified through simulation results using the PSIM software package.