Signal Processing and Renewable Energy
Volume:4 Issue: 2, Spring 2020

This paper reviews various algorithms for the implementation of MPPT in a PV module integrated with a DC-DC converter and current mode control strategies for power converters. Also, a novel multi-loop integrated MPPT and current mode control for the Single Ended Primary Inductance Converter (SEPIC) derived from the incremental conductance MPPT technique is proposed. A simulation model is developed using MATLAB/Simulink dynamic system simulation software to verify the operation of the control system developed in the paper. This ensures the efficient operation of the PV power plant by rapid and accurate tracking the maximum power point (MPP) of the PV array. Moreover, the system is seen to offer robust voltage regulation and improved dynamic response in the face of changing environmental variables.

Epilepsy is a brain disorder which stems from the abnormal activity of neurons and recording of seizures has primary interest in the evaluation ‎of epileptic patients.  A seizure is the phenomenon of rhythmicity discharge from either a ‎local area or the whole brain and the individual behavior usually ‎lasts from seconds to minutes. In this work, empirical wavelet transform (EWT) is applied to ‎decompose signals into Electroencephalography (EEG) rhythms. ‎EEG signals are separated into the delta, theta, alpha, beta and gamma ‎rhythms using EWT.‎ The proposed method has been evaluated by the benchmark dataset which is freely downloadable from the Bonn University website. Ellipse area (A) and shortest distance to 45 and 135-degree lines are computed from the 2D projection of reconstructed phase space (RPS) of rhythms as features. After that, the genetic algorithm is used as feature selection. Finally, selected features are fed to the K-nearest neighbor (KNN) classifier for the detection of the seizure (S) and seizure-free (SF) EEG signals. Our proposed method archived 98.33% accuracy in the classification of S and SF EEG signals with a tenfold cross-validation strategy that is higher than previous techniques.

Power electronic converters have been considered by many researchers and their control and robustness under various operating conditions has a great importance. The proposed type-2 fuzzy controller employs expert experience to control the power electronic converters, considering to their non-linear and time variant structure. Using type-2 fuzzy controller enhances the stability and robustness of system. This paper's attempt is to compare general and interval type-2 fuzzy controllers in terms of dealing with non-linear uncertain plants. It is shown that general type-2 fuzzy controller leads to more accuracy in comparison with interval type-2 and type-1 fuzzy controllers in regulating the output voltage, as it is shown in simulation part. To compare the performance of the controlling methods, the Euclidean norm of regulating error is calculated.

One of the common problems of power quality is the occurrence of voltage sags due to different types of balanced and unbalanced short-circuit faults in electrical distribution systems. Dynamic Voltage Restorer (DVR) is the most effective equipment used for voltage recovery in power distribution systems and it injects voltage in series with line voltage for voltage recovery. In this paper, the structure and general components of this equipment are presented. In addition, by applying a control scheme based on Synchronous Reference Frame Theory (SRFT) in its control system, the effective role of this equipment in compensating and maintaining the voltage of a power distribution system under the occurrence of balanced three-phase short-circuit fault and unbalanced single-phase to ground short-circuit fault is investigated and analyzed using Simulink/Matlab software.

In this paper, the reactive resources placement including capacitor bank in radial distribution network is studied. The placement purpose is to reduce the cost of power loss, the cost of capacitor purchase and installation. The location and size of the capacitors in the distribution network are determined using the intelligent ant lion optimizer (ALO) method, which is inspired by the hunting behavior of the ant lions. Based on the power loss sensitivity factor (LSF), candidate buses are selected for capacitor installation using the ALO. The proposed method is implemented ona 33-bus radial distribution networks. In this study, the effect of loading changes on the placement problem and distribution network characteristics including power losses, minimum voltage, voltage profile and net savings are evaluated. The results show that after optimal capacitor placement the characteristics of the distribution network includes active and reactive power loss are significantly reduced and also the network voltage profile is improved compared to former capacitor placement. The performance of the proposed method is compared to particle swarm optimization (PSO), teaching-learning based optimization (TLBO) and previous studies, which showed the superiority of the proposed method in achieving lower cost and greater net saving.

This paper presents the optimal and intelligent design of photovoltaic-wind-hydrogen system with the aim of minimizing the overall cost of the system and considering the reliability constraints based on annual radiation and wind speed data in Bushehr city. The hydrogen storage system includes an electrolyzer, a hydrogen storage tank and a fuel cell. Overall costs of hybrid systems include initial investment costs, maintenance and operation and replacement of components, and reliability constraint indicate deficit load demand probability (DLDP). In this study, the decision variables were optimized system capacity including number of solar panels, wind turbine, electrolyzer power capacity, mass of hydrogen storage tank, fuel cell capacity and power transfered with inverter by Grey Wolf Optimization (GWO) algorithm that has high convergence speed and accuracy. System design is presented in different scenarios of hybrid system combinations. To verify the proposed method, the results are compared with the results of Particle Swarm Optimization (PSO) algorithm. The simulation results show that the GWO method performs better in design of optimization with lower overall cost and better DLDP than the PSO in different combinations. The results show that photovoltaic -hydrogen storage due to the low wind speed potential in Bushehr city is the optimal combination based on cost and reliability for load supply based on renewable resources hybrid systems. In addition, the results show that the use of higher efficiency inverters reduces energy production costs and improves load reliability. In addition, the results indicate that the outage of renewable units in the design problem has a significant effect on system cost and reliability.