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Volume 11

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Dynamic modeling of grid-connected photovoltaic system using artificial neural network and genetic algorithm

Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. The aim of this study is to simulate and control of a grid-connected PV source using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum power point (MPP), ANN and GA are used. Data are optimized by GA and then these optimized data are applied in the neural network training. The simulation results are presented by using Matlab/Simulink and show that the ANN—GA controller can meet the need of the load easilyand have less fluctuations around the maximum power point (MPP), also it can increase convergence speed to achieve the MPP. Moreover, to control both line voltage and current, a grid side P-Q controller has been applied.

Comparative Performance of Supercapacitor and Fuel cell based UPQC

In this paper analysis comparative result of a supercapacitor based unified power quality conditioner comparing with a fuel cell based unified power quality conditioner. This work describes the unified power quality conditioner principles and power restoration for balanced or unbalanced voltage sag or swells in a distribution system. This method proposes a typical configuration of unified power quality conditioner that consists of a DC/DC converter supplied by a supercapacitor at the DC link. This analysis used for comparing how the THD will be improved and after injecting current and voltage to UPQC source current and source voltage are sinusoidal. This paper explains the comparative results of UPQC showing performance Wise THD of upercapacitor and fuel cell, the harmonic distortion is reduced in fuel cell as compared
to supercapacitor. The comparative studies analyse in both the cases fuel cell is better than supercapacitor in power quality parameters as THD and power factor etc. The result analysis shows the THD of supercapacitor and fuel cell, the harmonic distortion is quite reduced in fuel cell as compared to supercapacitor. The operation of the proposed system is modeled and simulated in MATLAB environment using Simulink and Simpower System toolboxes.

Robust Generation Control Strategy Based on Grey Wolf Optimizer

This paper presents an application of Grey Wolf Optimizer (GWO) technique to estimate the parameters of the Proportional Integral Controller (PI) for Automatic Generation Control of two area power system. In this work two thermal units with non reheat turbines are considered. The detailed eigenvalue analysis is carried out for exhibiting the philosophy of damping requirement in the complex networks. The parameters namely proportional integral gain, speed regulation, frequency sensitivity coefficient are considered as the modifiable parameters. These parameters are estimated through optimization process with the aim to minimize the Area Control Error
(ACE). The comparison between two objective functions namely Integral Square Error (ISE) and Integral Time Absolute Error (ITAE) is presented. Sensitivity analysis advocates the effectiveness of the proposed approach. To draw a fair comparison between the proposed method and the conventional methods (GSA, PSO and GA) convergence characteristics of the optimization techniques are compared and presented. It is observed that the proposed design satisfactorily handle different contingencies and operating conditions.

Comparison of Hybrid DifferentialEvolution Algorithm with GeneticAlgorithm Based Power System SecurityAnalysis Using FACTS

This paper presents a novel stochastic hybrid differential evolutionary algorithm technique to find the optimal location of Flexible Alternating Current Transmission System (FACTS) devices with minimum cost of installation and to improve power system security and is compared with Genetic Algorithm (GA). Differential Evolution (DE) algorithm technique is a simple evolutionary search algorithm and shows better performance but greedy in space searching. Particle Swarm Optimization (PSO) converges quickly and but stuck in local optima.A novel heuristic method based on Genetic algorithm also used to find optimal location of FACTS devices to enhance the power system security and no absolute assurance of global optimum. In this paper hybrid differential evolutionary algorithm (DEPSO) is introduced to eliminate the problems of DE and PSO and solve the power system security problem with
greater accuracy and compared with Genetic Algorithm. The proposed algorithm minimizes the security index, loss and the installation cost of FACTS devices in the transmission network. Security index indicates the overload level of the transmission lines. Three types of FACTS devices, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC) are considered and the proposed algorithm is verified by standard IEEE 14 bus network.

An improved simple Fuel Cell model for Energy Management in residential buildings

This paper deals with a fuel cell (FC) model to be integrated into the energy management algorithm for a stand-alone residential photovoltaic (PV) power system. The FC system is added to guarantee continuous power supply taking account of the photovoltaic intermittent nature. FC models are generally relatively complex especially when they should be introduced in a complete hybrid system model. This paper investigates a simple FC model derived from the FC electrical circuit model. Analytic expression of each element of this simple circuit is established. Experimental tests are conducted to identify the model parameters. FC model is simulated using PSIM software and validated with corresponding experimental polarization curves. To verify FC model effectiveness for energy management algorithm, simulations are carried out with specific load shape and a hybrid system (FC and PV systems with storage batteries). Several scenarios are performed under various meteorological conditions and in case of non-availability generation.

Voltage Unbalance in Low Voltage Networks with Single-phase and Three-phase Micro-Generation and Loads

The incorporation of clean energy sources in the power system is a topic of discussion almost everywhere. After the “Wind (farms) of change”, small, dispersed, urban photovoltaic (PV) generators are being installed in the roofs of the buildings,
connected to the local Low Voltage (LV) grid. A boost in this type of renewable micro generation is expected in the near future. Due to the domestic loads, LV grids are inherently unbalanced, its analysis requiring the use of three-phase load flow
methods. This same methodology is used in this paper to assess the problem of the concurrent unbalanced generation and load and to cope with the presence of both single and three-phase equipment in the same grid. A review of existent models for
three-phase equipment is performed. The issue of modelling three-phase loads (isolated star and delta connected) and singlephase PV generators and associated power electronics is given special attention. Finally, a case-study is presented, enabling to draw some conclusions regarding the impacts on the Medium Voltage (MV) grid and the behaviour of the system facing different climacteric conditions.

Improving Transmission Rate with Efficient Bandwidth by using Diversity Technique for MIMOOFDMA Resource Allocation

MIMO-OFDMA (Multiple Input Multiple Output-Orthogonal Frequency Division Multiple
Access) resource allocation is studied in this paper. The considered problem is to provide eachuser with more data rates in wireless communication system by using the suitable value of bandwidth. The objective of this research is to focus on how to improve the data rate by using efficient bandwidth in MIMO-OFDMA system. The different diversity techniques are also applied to observe which technique is the best for the achievement of maximum diversity order.The simulations show that the space time frequency (STF) diversity technique achieves the highest diversity order by achieves more than 50 percent improvement compared to the system without diversity method, and the value of suitable bandwidth is identified to improve the transmission rate of the system.

Abnormal gait detection using Hexagonal method on Model based Front view model

Gait abnormality recognition would be very useful in medical monitoring and surveillance system. In this research, analysis of front view human gait silhouette had been done to investigate the possibility of the method in recognizing abnormality on proposed model-based approach. The model based which utilised hexagonal theorem as feature extraction method is used to produce the vertical angles of both hip and knee for 70 image sequences as feature vectors for both legs for one complete cycle sequences. Consequently, a total of 280 features generated based on four parameters from the lower limb of human body for gait abnormality purpose. Further, the gait features extracted from different gait pattern namely as normal, drunken, dragging and tiptoed is classified as normal or abnormal using ANN and KNN. Improvement findings of classification result for before and after normalisation confirmed that the proposed method suited to be utilized as gait abnormality recognition based on human gait

Fuzzy Logic Controlled DC-DC Converter Based Dynamic Voltage Restorer

This paper presents fuzzy logic controlled dc-dc boost converter based Dynamic Voltage Restorer (DVR) to compensate severe voltage sag problems in an electrical system. DVR absorbs real power from battery to compensate voltage sags in the system. This condition causes reduction in voltage magnitude of dc-link capacitor. Additionally, DVR requires large dc capacitors to compensate long and severe voltage sags in the system. In this study, dc-dc boost converter is connected to DVR for keeping dc link voltage constant. For this propose, a control algorithm based on Fuzzy Logic (FL) control is developed for dc-dc boost converter. The main contribution of this study is that Fuzzy Logic (FL) is firstly used to generate reference signal for PWM signals of dc-dc converter applied in DVR. FL is a very flexible controller which keeps
the dc link voltage constant during voltage sag. The performance results of proposed study are verified with PSCAD/EMDTC.

Robust Optimal Control of Chaos in Permanent Magnet Synchronous Motor with Unknown Parameters

This paper focuses on the problem of chaos suppression in permanent magnet synchronous motors (PMSM) with uncertain parameters. Firstly, the chaotic characterizations are analyzed, including bifurcation diagram, chaotic attractor, Lyapunov exponents, and power spectrum. Then, by using robust optimal control approach, a simple linear feedback controller is designed to make the system states stable. And the control gains can be obtained from a linear matrix inequality (LMI), which can be resolved easily via the MATLAB LMI toolbox. Based on Lyapunov stability theory, the stability of the proposed scheme is verified. Finally, numerical
simulation results are given to demonstrate the effectiveness of the presented method.

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