Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Not a member yet
776 research outputs found
Sort by
Evaluation of Power Management Strategy for Renewable Microgrid System
Get PDFThis paper presents the evaluation and control of renewable energy sources based micro-grid system having solar photovoltaic, wind turbine generator, fuel cell and diesel engine generator. A battery storage system has also been installed to provide unintrupted power supply and to store excess power. The proposed micro-grid system is simulated on Matlab/Simulink software and the performance has been analysied with two cases considering different environmental conditions to check the optimal performance of the system. In the first case, the solar photovoltaic, fuel cell, diesel engine generator and battery storage system has been considered and in the second case, the solar photovoltaic source is replaced by the wind turbines. For both the cases, simulation has been done for 300 seconds to findout the optimal fulfilment of the demand. The time domain analysis has been done by varying the solar irradiance and wind speed in respective cases to check the system performance. This work shows the efficient control of various distributed energy resources in the micro-grid system and meeting the load demand efficiently
The Assessment of Light Environment with the First Generation Leds
Get PDFThe article describes experimental studies on the effectiveness of lighting installations (LI) with light-emitting diodes (LEDs). It is established that LED-based lighting does not cause a negative impact on the organ of vision and the human body as a whole. The changes in the functional parameters of the organ of sight, which occur during the visual performance has the corresponding limits of physiological fluctuations and are reversible. The integral indicators of the efficiency of LED-based lighting were estimated. The practical significance of the results was shown
Bat Algorithm for Solving Dynamic Economic Emission Dispatch Problem
No full textThis paper proposes a new meta-heuristic search algorithm, called Bat Algorithm (BA). Bat algorithm is an optimization technique motivated by the echolocation behavior of natural bats in finding their foods. The proposed algorithm is presented to solve the dynamic economic emission dispatch (DEED) problem. As emission minimization is conflicting with minimum cost of generation, the DEED problem becomes a multi-objective optimization problem with conflicting objectives. The proposed algorithm is validated on 5-unit generation system for a 24 h time interval. The results proved the efficiency of the proposed method when compared with the other optimization algorithms reported in the literature
Comparative Study of Type-1 and Type-2 Fuzzy System in Decision Support System
Get PDFThis study compares the Type-1 Fuzzy and Interval Type-2 Fuzzy in Decision Support System (DSS). Particular case studied in this paper deals with supplier selection for development of new product. DSS is developed to recommend a decision to provide assessment criteria on the supplier. All the type of membership functions and rules between these systems are equally applied. It is shown that in Type-2 Fuzzy can manage the level of uncertainty in decision making. In general, both systems have a surface resemblance. The result shows that type-2 Fuzzy based decision making with a level of uncertainty is able to provide alternative decisions
Big Data in Smart-Cities: Current Research and Challenges
Get PDFSmart-cities are an emerging paradigm containing heterogeneous network infrastructure, ubiquitous sensing devices, big-data processing and intelligent control systems. Their primary aim is to improve the quality of life of the citizens by providing intelligent services in a wide variety of aspects like transportation, healthcare, entertainment, environment, and energy. In order to provide such services, the role of big-data and its analysis is extremely important as it enables to obtain valuable insights into the large data generated by the smart-cities. In this article, we investigate the state-of-art research efforts directed towards big-data analytics in a smart-city context. Specifically, first we present a big-data centric taxonomy for the smart-cities to bring forth a generic overview of the importance of big-data paradigm in a smart-city environment. This is followed by the presentation of a top-level snapshot of the commonly used big-data analytical platforms. Due to the heterogeneity of data being collected by the smart-cities, often with conflicting processing requirements, suitable analytical techniques depending upon the data type are also suggested. In addition to this, a generic four-tier big-data framework comprising of the sensing hub, storage hub, processing hub and application hub is also proposed that can be applied in any smart-city context. This is complemented by providing the common big-data applications in a smart-city and presentation of ten selected case studies of smart-cities across the globe. Finally, the open challenges are highlighted in order to give future research directions
Fast Denoising Filter for MRI using Parallel Approach
No full textReal time medical image processing is necessary in the domain of remote medical care, diagnostics and surgery. To provide fast MRI diagnostics especially for neuro imaging, the research work proposes CUDA GPU based fast denoising filter with a parallel approach. Bilateral filter is the most suitable candidate for denoising, as it has unique ability to retain contours of soft tissue structures of the brain. The work proposes improvised memory optimization techniques for the GPU implementation to achieve superior performance in terms of speed up when compared with existing work. For a 64Megapixel brain MR image, shared memory approach gives speed up of 256.5 while texture memory usage with tiling approach stands the next in speedup with 42.16 over its CPU counterpart. The results indicate that in spite of increase in image size, the execution time of the filter does not increase beyond 500msec keeping the performance real time
Synthesis of (Polymer blend-MgO) Nanocomposites and Studying Electrical Properties for Piezoelectric Application
Get PDFNanocomposites prepared by casting method with different percentages of nano magnesium oxide (0, 1.5, 3, 4.5 and 6) wt%.The structural and electrical properties of (PAA-CMC-MgO) nanocomposites were studied.The experimental results of Scanning electron microscopy shows the surface morphology of the (PAA-CMC-MgO) nanocomposites where many aggregates or chunks randomly distributed on the top surface, homogeneous and coherent.The D.C electrical conductivity for (PAA-CMC-MgO) nanocomposites increased with increasing of temperature and magnesium oxid nanoparticles concentration, while activation energy decreases with increasing of the magnesium oxid nanoparticles concentration.The A.C electrical properties show that the dielectric constant and dielectric loss of the nanocomposites decrease with increasing the frequency of applied electrical field and they increase with the increase of the concentration of the magnesium oxide nanoparticles. The A.C electrical conductivity increases with increasing the concentration of magnesium oxide nanoparticles and also increases with the increase frequency, as well as almost constant at high frequency.The results of sensor application showed that the electrical resistance of (PAA-CMC-MgO) nanocomposite decreases with increases in pressure
Performance Analysis of Adaptive Fuzzy Sliding Mode for Nonlinear Control of the Doubly Fed Induction Motor
Get PDFIn this article, we propose a contribution to the control of a doubly fed induction motor by sliding mode with adaptive fuzzy logic. The technique of vector-control by classical field oriented applied to the doubly fed induction motor (DFIM) with mechanical sensors made it possible to have performances comparable with that of the direct current motor. However, it very sensitive to the parametric variations of the machine. The regulation speed by a classical regulator (PI) presents disadvantages: Poor robustness against parametric uncertainties of modeling and no the considering of the disturbances and little degree of freedom for the regulation. Because this effect, several robust controls were proposed in the technical literature to ensure the decoupling of the currents of the DFIM in a reference (d, q) leading to calculate simplified correctors. Among them, the variable structure control by sliding mode. It uses algorithms of regulations which ensure the robustness of the behavior of the process compared to the parametric variations and disturbances. Also, the impact of regulators based on artificial intelligence techniques such as adaptive fuzzy sliding mode controller are studied. In terms of results obtained, good dynamic performance and robustness with respect to load disturbances and parametric variation has been observed
Graphene-based Microbial Fuel Cell Studies with Starch in sub-Himalayan Soils
Get PDFMicrobial fuel cells with graphene based cathode and anode is the study of interest. Present work shows the capacity of sub-himalayan soil of Dehradun region of Uttarakhand, India holds potential to cater to power production from soil and organic waste matter. This can be speculated to power less energy intensive devices at the smallest level. Peak voltage of 0.69 V and current density datas are reported.Renewable energy utilization with such samples represents a sustainable usage. The soil bacterias are capable to metabolize the metal substances in the soil through symbiosis. Electric bacteria create conductive pili called nanowires enabling them to transfer electron and this can be utilized effectively.Direct electron transfer mechanisms have been investigated for this work. The biofilm developed by soil bacterias represent the central idea in making value from waste matter
A Pattern Classification Based approach for Blur Classification
Get PDFBlur type identification is one of the most crucial step of image restoration. In case of blind restoration of such images, it is generally assumed that the blur type is known prior to restoration of such images. However, it is not practical in real applications. So, blur type identification is extremely desirable before application of blind restoration technique to restore a blurred image. An approach to categorize blur in three classes namely motion, defocus, and combined blur is presented in this paper. Curvelet transform based energy features are utilized as features of blur patterns and a neural network is designed for classification. The simulation results show preciseness of proposed approach