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This paper proposes modeling and control system design for PV based Quasi-Z-Source Inverter (QZSI) for grid connected applications. The control system is designed based on the dynamical characteristics of the converter and introduces two cascaded controllers. Firstly, output current controller designed in the stationary frame. The second is DC-link voltage controller. Also, Modified Direct Incremental...
This paper explains the talented impact of utilizing the Adaptive Neuro Fuzzy Inference System (ANFIS) technique on enhancing the performance of the generator Loss-of-Excitation (LOE) protection. In this context, investigations are conducted on a two-hydro generator power station model under a complete Loss of Excitation (LOE) conditions and a partial Loss of Excitation (LOE) conditions. The positive...
This paper presents an adaptive state of charge estimator for rechargeable batteries using the artificial neural network technique. That technique is based on that the charging current for any battery, in un-controlled current charging circuit, changes according to the battery state of charge (SOC). This proposed estimator will use the charging current, battery voltage samples and the time of each...
This Paper presents a model of Wind Energy Conversion System (WECS) using Permanent Magnet Synchronous Generator (PMSG). This system is a grid connected system and contains two power converters and capacitor bank. This system is controlled by PI control for controlling the Voltage Source Inverter (VSI). Particle Swarm Optimization (PSO) code is used to calculate the parameters of the controller to...
The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm (GA) and Adaptive Neuro-Fuzzy Inference System (ANFIS). DC motor could be represented by a nonlinear model when nonlinearities such as magnetic saturation are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in...
The Active Power Filter (APF) is an advanced solution to power quality problems in which all problems related to the classical solution passive L-C filter has been solved. The main purpose of this paper is to focus upon the comparison between three types of controllers which are Genetic Algorithm (GA) tuned Proportional Integral (PI) controller, GA tuned PI like fuzzy controller and optimization of...
This paper proposes a new technique to model the stator winding of the induction motor in order to simulate its thermal behavior. The modified model is used to validate a remote and sensorless stator winding temperature estimation technique for induction motors. The stator winding resistance/temperature is estimated from dc injection via soft starter by changing the gate drive signals of the thyristors...
The advanced application of Artificial Neural Network was introduced recently in Protection of Transmission lines in Electric Power Systems. In this proposed research, the application of ANFIS and ANN for Distance Relay Protection for short and long Transmission line, under different loading conditions, in Electrical Power systems will be introduced and discussed. Considering different loading conditions,...
Accurate load forecasting is very important for electric utilities in planning for new plants. Also it is very significant for the routine of maintaining, scheduling daily, electrical generation, and loads. The main mission for a forecaster is to study the behaviour of the collected historical data (which is called data mining), and determining the different patterns of the time series. In this study,...
This paper presents an adaptive state of charge estimator for rechargeable batteries using the Adaptive Neuro Fuzzy Inference System (ANFIS). That technique is based on that the charging current for any battery, in un-controlled current charging circuit, changes according to the battery state of charge (SOC). This proposed estimator will use the charging current, battery voltage samples and the time...
This paper presents a new approach for detection and classification of high impedance faults in distribution system using Adaptive Neuro Fuzzy Inference System (ANFIS). The proposed scheme was trained by data from simulation of a distribution system under different faults conditions and tested for different system conditions. Details of the design procedure and the results of performance using the...
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