Applied Mechanics and Materials Vol. 573

Abstract: This paper deals with the design of filters for power quality enhancement in microgrid. The voltage source inverters (VSI) fed from microgrid requires filter across them to detect the unbalance and harmonics in the system. The performances of various filters are compared and the improved negative sequence filter is found out to be the best solution. The stability of these filters are also studied and simulations are carried out to validate the results.

Abstract: This paper presents an artificial immune system algorithm to the short-term hydrothermal scheduling and unit commitment problem. This technique is applied to maximize the profit of Generating Companies (GENCO) which consider the softer demand constraint. A novel method is proposed for solving Hydrothermal Scheduling (HTS) using Artificial Immune System (AIS) in a competitive electricity market. The proposed algorithm is tested on four-hydro and three-thermal system for 12 hours. It is observed from the numerical results that the proposed algorithm provides better profit as compared to the conventional method and hence can be adopted by GENCO. Keywords: Hydrothermal Scheduling (HTS), Artificial Immune System (AIS)

Abstract: Development of better wind and thermal coordination dispatch is necessary to determine the optimal dispatch scheme that can integrate wind power reliably and efficiently. In this paper hybrid Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) approach is utilized to coordinate the wind and thermal generation dispatch and to minimize the total production cost considering wind power generation and valve effect of thermal units. Numerical studies have been performed for three different test systems, i.e., six, thirteen and forty generating unit systems. The simulation results demonstrate the effectiveness of the proposed approach and shows the effect of wind power generation in reducing the total fuel.

Abstract: The Unified Power Quality Conditioner plays an important role in the constrained delivery of electrical power from a source to an isolated pool of load or from a source to the grid. This article is presented new control approaches for both series and shunt inverter. The proposed control algorithm for series and shunt converters based on FLC and synchronous reference frame theory respectively. The proposed approach eliminates the total harmonic distortions (THD) efficiently, and mitigates sag and swell present in the linear and nonlinear loads.

Abstract: In this paper, wavelet transform based approach is proposed for islanding detection in a distribution system. The negative sequence voltage and negative sequence current obtained due to disturbances are measured at the point of common coupling (PCC) and given to the wavelet processing module to extract features like standard deviation and energy content. The negative sequence voltage and current components are decomposed under various levels to filter out lower frequency components. From the obtained features suitable threshold value is fixed for classifying the islanding and non-islanding events.

Abstract: Utilizing the renewable energy at consumer side is not required additional transmission capacity. Solar power plant connected with wind generator can support real and reactive power to the unbalance three phase loads. The unbalance load always requires more reactive power compare to balanced load. The reactive power support demand of the unbalanced load is supplied by any conventional FACTS devices. These conventional devices add additional cost and require maintenance also. In this proposed system Voltage Source Inverter (VSI) based solar power plant acts like a STATCOM and reduces the additional cost requirement. The unbalanced three phase load have different reactive power requirement for individual phase. The PWM based FACTS devices supplies only balanced reactive power support irrespective of their requirement. It leads to poor compensation and requires large size of FACTS devices. In this paper the Individual Phase Current sensing method is used and the performance of the system is analyzed for PI controller. The MATLAB simulation verification is presented. Keywords : Solar power plant, Wind power plant, FACTS devices, IPCS, PI, Fuzzy logic.

Abstract: To allow utilities to fulfill self-imposed and regulative performance targets the demand for new optimized tools and techniques to Estimate the performance of modern Transformers has increased. The modern power transformers has subjected to different types of faults, which affect the continuity of power supply which in turn causes serious economic losses. To avoid the interruption of power supply, various fault diagnosis approaches are adopted to detect faults in the power transformer and has to eliminate the impacts of the faults at the initial stage. Among the fault diagnosis methods, the hybrid technique of Particle Swarm Optimization (PSO) with Support Vector Machine (SVM) learning algorithm is simple conceptually derived and its implementation process is faster with better scaling properties for complex problems with non linearity and load variations but performance factor related to accuracy has a declined value in case of correlations implicit . In order to obtain better fault diagnosis to improve the service of the power transformer, SVM is optimized with Improved PSO technique to achieve high interpretation accuracy for Dissolved Gas Analysis (DGA) of power transformer through the extracting positive features from both the techniques. Primary SVM is applied to establish classification features for faults in the transformer through DGA. The features are applied as input data to Autonomous optimized Technique for faults analysis. The proposed methodology obtains the DGA data set from diagnostic gas in oil of 500 KV main transformers of Pingguo Substation in South China Electric Power Company. The simulations are carried out in MATLAB software with an Intel core 3 processor with speed of 3 GHZ and 4 GB RAM PC. The result obtained by Autonomous optimized Technique (IPSO-SVM) is compared against PSO-SVM to estimate the performance of the classifiers in terms of execution time and quality of classification for precision. The test results indicate that the Autonomous optimization of IPSO-SVM approach has significantly improved the classification accuracy and computational time for power transformer fault classification. Keywords: Transformer Fault Analysis, Improved Particle Swarm Optimization, Hybrid Optimization, Dissolved Gas Analysis, Support Vector Machine

Abstract: Renewable energy sources provide the additional/satisfy the power to the consumer through power electronics interfaces and integrated with the grid. In grid integration power quality is one of the important parameter that need to be paying more attention. This proposed work focuses on power quality issues in a grid connected renewable energy system. Power quality issues will arises due to many factors here with the by introducing a fault condition in a grid connected renewable energy system the measurements were made at the point of common coupling and the mitigation is done with the help of a dynamic voltage restorer. The dynamic voltage restorer is a device which offers series compensation activated by neural network based controller. The sag improvement and the total harmonic assessment were made at the point of common coupling. Keywords: Neural network, Point of common coupling, Renewable energy source, Power quality, Dynamic voltage restorer ,electric grid.

Abstract: Power flow control is important in power systems and recently becomes more urgent because of the deregulation. This paper presents a novel configuration of unified power flow controller and performance of UPFC intended for installation on transmission line. When no UPFC is installed, any interruption in the line due to fault reduces the active power flow through the line. Installing the UPFC makes it possible to control an amount of active power flow through the line. Simulations were carried out using Matlab to validate the performance of UPFC. Keywords: FACTS Devices, UPFC, Transient stability, Matlab, Fault simulation.

Abstract: This paper proposes a technique for the identification of defects of three-phase squirrel cage induction motors. Simulations were performed using ANSYS finite element software package to obtain the flux density waveform in the air gap. Broken rotor bar fault was simulated by breaking rotor bars to see how the flux density is affected. In this paper, a new approach for the identification of broken rotor bar based on the calculation of high-frequency losses in induction motors is presented. The approach presented in this paper requires little time for loss calculation and fault identification.