PI, Fuzzy Based Controllers for FACTS Devices in Grid Connected PV System

Now-a-days Renewable Energy Sources became an alternative to meet the increasing load demand because they are environmental friendly and also available abundant in nature. Among the Renewable Energy Sources, the Photo Voltaic (PV) System is gaining more attention due abundant availability of solar energy. The Maximum Power Point Tracking Technique is used to extract maximum power from the Photo Voltaic (PV) Array. When there is a need to transfer bulk amount of power from PV Array to Power Grid, the power quality issues, especially the real and reactive power flow problems, are a major concern. In this paper a novel control technique was proposed to control the power flow and to deal with power quality issues that arise when PV Array is integrated with power grid. It consists of a PI controller and Fuzzy Logic Controller (FLC) fed Flexible AC Transmission System device, namely STATCOM, for effective control of real and reactive power flow in grid connected photovoltaic system. The proposed system was simulated by using MATLAB-SIMULINK Tool Box and the results are compared.   &nbsp

TIME CONDITION SYSTEMS

The current thesis considers the issue of state estimation of condition systems, a form of petri net with signal inputs and outputs. In previous research the problem of unobservability due to progress confusion was identified, in the presence of which state estimation is not possible. Here we introduce the notion of Time Condition Systems , a class of condition systems that uses timing information from condition models to overcome state estimation problem caused by progress confusion. To make use of the timing information in the plant model, a procedure called Exploded Time Plant is synthesized. This procedure makes the plant model an observable model. It is proved that this procedure does not alter the structural and temporal behavior of the plant model and the plant maintains its integrity. The time plant(s) and the corresponding Exploded time plant(s) are subsequently used to develop observer(s) and controller(s) for Time condition models

A Review on Fuzzy-GA based Controller for Power Flow Control in Grid Connected PV System

Now-a-days Renewable Energy Sources became an alternative to meet the increasing load demand because they are environmental friendly and also available abundant in nature. Among the Renewable Energy Sources, the Photo Voltaic (PV) System is gaining more attention due abundant availability of solar energy. The Maximum Power Point Tracking Technique is used to extract maximum power from the Photo Voltaic (PV) Array. When there is a need to transfer bulk amount of power from PV Array to Power Grid, the power quality issues, especially the real and reactive power flow problems, are a major concern. In this paper a novel control technique was proposed to control the power flow and to deal with power quality issues that arise when PV Array is integrated with power grid. It consists of a Fuzzy-GA based Cascaded Controller fed Flexible AC Transmission System device, namely Unified Power Flow Controller, for effective control of real and reactive power flow in grid connected photovoltaic system. The output of the Fuzzy Logic Controller is a control vector which is fine tuned by using Genetic Algorithm approach

SEPIC Converter based-Drive for Unipolar BLDC Motor

Front-end single-ended primary inductance converter (SEPIC) and a switch in series with each phase is proposed for driving a permanent magnet brushless dc (BLDC) motor with unipolar currents. All the switches are ground-referenced, which simplifies their gate drives. The available input voltage can be boosted for better current regulation, which is an advantage for low voltage applications. The SEPIC converter is designed to operate in the discontinuous conduction mode for operation with an ac supply. In this operation mode, the line current follows the line voltage waveform to a certain extent. The reduction in low-order harmonics and improved power factor is achieved without the use of any voltage or current sensors. The simplicity and reduced parts count of the proposed topology make it an attractive low-cost choice for many variable speed drive applications. The proposed topology is simulated and verified by using MATLAB/SIMULINK.DOI:http://dx.doi.org/10.11591/ijece.v2i2.30

Supported quantum clusters of silver as enhanced catalysts for reduction

Quantum clusters (QCs) of silver such as Ag7(H2MSA)7, Ag8(H2MSA)8 (H2MSA, mercaptosuccinic acid) were synthesized by the interfacial etching of Ag nanoparticle precursors and were loaded on metal oxide supports to prepare active catalysts. The supported clusters were characterized using high resolution transmission electron microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, and laser desorption ionization mass spectrometry. We used the conversion of nitro group to amino group as a model reaction to study the catalytic reduction activity of the QCs. Various aromatic nitro compounds, namely, 3-nitrophenol (3-np), 4-nitrophenol (4-np), 3-nitroaniline (3-na), and 4-nitroaniline (4-na) were used as substrates. Products were confirmed using UV-visible spectroscopy and electrospray ionization mass spectrometry. The supported QCs remained active and were reused several times after separation. The rate constant suggested that the reaction followed pseudo-first-order kinetics. The turn-over frequency was 1.87 s-1 per cluster for the reduction of 4-np at 35°C. Among the substrates investigated, the kinetics followed the order, SiO2 > TiO2 > Fe2O3 > Al2O3

An Innovative Solution to Make Sure High School Students Stay in School

Project No Drop attempts to make sure that students stop dropping out of high school. Currently, within Illinois, high schools such as East Aurora High School have a dropout rate six times higher than the national average. Project No Drop’s mission is to make sure that all students are able to get the same opportunities in the future through continued education. There are many factors that contribute to a students decision to drop out, which includes low motivation, disillusion, and apathy towards schoolwork and school completion because a student doesn’t feel or show significant academic progress in school. Through identifying their needs, we will build sustainable support for the students in need and connect them with opportunities so that they can succeed. We will first identify students that are potentially dropping out, motivate them to address their needs, and help students improve their academics. Through tutoring, summer programs, academic counseling, peer support system, internships, and possibly research opportunities, Project No Drop aims to alleviate the dropout crisis in East Aurora

Crowd sourced modeling approach of human behavior modeling

Generating models from large data setsand determining which subsets of data to mine is becoming increasingly automated. However choosing what data to collect in the first place requires human intuition or experience, usually supplied by a domain expert. This paper describes a new approach to machine science which demonstrates for the first time that non-domain experts can collectively formulate features, and provide values for those features such that they are predictive of some behavioral outcome of interest. This was accomplished by building a web platform in which human groups interact to both respond to questions likely to help predict a behavioral outcome and pose new questions to their peers. This results in a dynamically-growing online survey, but the result of this cooperative behavior also leads to models that can predict user’s outcomes based on their responses to the user-generated survey questions

Perspective Chapter: Epigenetic Therapy - The Future Treatment for Cancer

Scientists have made a remarkable breakthrough by uncovering DNA and its role in living organisms. Epigenetics examines the phenotypic divergences due to DNA methylation and its effects at certain genetic spots. Epigenetic and genetic problems combine to cause cancer and its growth, as seen by frequent mutations in genes that manage the epigenome. Recently, new therapies targeting epigenetic alterations have been proposed. Drugs with longer shelf life and better absorption are also being manufactured and tested. On this aspect, CRISPR technology has been used to create various strategies for epigenetic engineering and is a practical approach to understanding and manipulating biological processes. Furthermore, studies on the advantages of probiotics have advanced previous interventional studies to recognize the molecular mechanisms involved. Numerous probiotic genomes include epigenetic components that influence gene expression for fundamental functions. Consequently, we suggest investigations incorporating genomic and meta-epigenomic information to better understand the mode of action of probiotics and their related microbiomes in epigenetic therapy. Here, we review established epigenetic discoveries, combined with the rapid advancement of immunotherapies, to create new possibilities for cancer treatment

SRF is required for maintenance of astrocytes in non-reactive state in the mammalian brain

Astrocytes play several critical roles in the normal functioning of the mammalian brain, including ion homeostasis, synapse formation, and synaptic plasticity. Following injury and infection or in the setting of neurodegeneration, astrocytes become hypertrophic and reactive, a process termed astrogliosis. Although acute reactive gliosis is beneficial in limiting further tissue damage, chronic gliosis becomes detrimental for neuronal recovery and regeneration. Several extracellular factors have been identified that generate reactive astrocytes; however, very little is known about the cell-autonomous transcriptional mechanisms that regulate the maintenance of astrocytes in the normal non-reactive state. Here, we show that conditional deletion of the stimulus-dependent transcription factor, serum response factor (SRF) in astrocytes

SRF-deficient astrocytes provide neuroprotection in mouse models of excitotoxicity and neurodegeneration

Reactive astrogliosis is a common pathological hallmark of CNS injury, infection, and neurodegeneration, where reactive astrocytes can be protective or detrimental to normal brain functions. Currently, the mechanisms regulating neuroprotective astrocytes and the extent of neuroprotection are poorly understood. Here, we report that conditional deletion of serum response factor (SRF) in adult astrocytes causes reactive-like hypertrophic astrocytes throughout the mouse brain. Thes