Showing papers in "Journal of The Institution of Engineers : Series B in 2018"
TL;DR: An overview of the research progress in Particle Swarm Optimization during 1995-2017 is presented, which includes improvements, modifications and applications of this technique.
Abstract: This paper presents an overview of the research progress in Particle Swarm Optimization (PSO) during 1995–2017. Fifty two papers have been reviewed. They have been categorized into nine categories based on various aspects. This technique has attracted many researchers because of its simplicity which led to many improvements and modifications of the basic PSO. Some researchers carried out the hybridization of PSO with other evolutionary techniques. This paper discusses the progress of PSO, its improvements, modifications and applications.
178 citations
TL;DR: An intelligent and an optimal model for prophecy of stock market price using hybridization of Adaline Neural Network (ANN) and modified Particle Swarm Optimization (PSO) and the result indicates that proposed scheme has an edge over all the juxtaposed schemes in terms of mean absolute percentage error.
Abstract: The foremost challenge for investors is to select stock price by analyzing financial data which is a menial task as of distort associated and massive pattern. Thereby, selecting stock poses one of the greatest difficulties for investors. Nowadays, prediction of financial market like stock market, exchange rate and share value are very challenging field of research. The prediction and scrutinization of stock price is also a potential area of research due to its vital significance in decision making by financial investors. This paper presents an intelligent and an optimal model for prophecy of stock market price using hybridization of Adaline Neural Network (ANN) and modified Particle Swarm Optimization (PSO). The connoted model hybrid of Adaline and PSO uses fluctuations of stock market as a factor and employs PSO to optimize and update weights of Adaline representation to depict open price of Bombay stock exchange. The prediction performance of the proposed model is compared with different representations like interval measurements, CMS-PSO and Bayesian-ANN. The result indicates that proposed scheme has an edge over all the juxtaposed schemes in terms of mean absolute percentage error.
21 citations
TL;DR: An Adaptive Social Acceleration Constant based Particle Swarm Optimization (ASACPSO) has been developed which uses the best value of social acceleration constant (Csg) and was found to converge faster and give more accurate results compared to BPSO for IEEE 5, 14 and 30 bus systems.
Abstract: In this paper, an Adaptive Social Acceleration Constant based Particle Swarm Optimization (ASACPSO) has been developed which uses the best value of social acceleration constant (Csg). Three formulations of Csg have been used to search for the best value of Csg. These three formulations led to the development of three algorithms–ALDPSO, AELDPSO-I and AELDPSO-II which were implemented for Economic Load Dispatch of IEEE 5 bus, 14 bus and 30 bus systems. The best value of Csg was selected based on the minimum number of Kounts i.e. number of function evaluations required to minimize the function. This value of Csg was directly used in basic PSO algorithm which led to the development of ASACPSO algorithm. ASACPSO was found to converge faster and give more accurate results compared to BPSO for IEEE 5, 14 and 30 bus systems.
16 citations
TL;DR: A meta heuristic optimization method called modified Culture Algorithm for reconfiguration of distribution network considering power loss, which is inspired by culture and culture is collection of different traits, social motivated behavior and individual’s experiences of several generations.
Abstract: This paper proposes a meta heuristic optimization method called modified Culture Algorithm (CA) for reconfiguration of distribution network considering power loss. Modified CA is inspired by culture and culture is collection of different traits, social motivated behavior and individual’s experiences of several generations. These social motivated behavior and individual’s experiences are collected, merged and generalized in the belief space. This belief space is communicated with future generation, which forces the optimization problem towards the global optimal solutions. In the proposed methodology decimal based coding technique has been used to represent chromosomes. To get feasible chromosomes all the time, it is subjected to some graph theory based rules. Direct topological approach has been used for precise calculation of power losses. The proposed methodology has been tested on 16-bus and 33-bus distribution test cases. The obtained result has been compared with some previous paper results and it shows that the proposed method is better than the methods used in previous papers.
15 citations
TL;DR: The Power Balance Theory (PBT) with perturb and observe based maximum power point tracking algorithm is proposed for the mitigation of power quality problems in a solar PV grid tied system.
Abstract: In this paper, power quality features such as harmonics mitigation, power factor correction with active power filtering are addressed in a single-stage, single-phase solar photovoltaic (PV) grid tied system. The Power Balance Theory (PBT) with perturb and observe based maximum power point tracking algorithm is proposed for the mitigation of power quality problems in a solar PV grid tied system. The solar PV array is interfaced to a single phase AC grid through a Voltage Source Converter (VSC), which provides active power flow from a solar PV array to the grid as well as to the load and it performs harmonics mitigation using PBT based control. The solar PV array power varies with sunlight and due to this, the solar PV grid tied VSC works only 8–10 h per day. At night, when PV power is zero, the VSC works as an active power filter for power quality improvement, and the load active power is delivered by the grid to the load connected at the point of common coupling. This increases the effective utilization of a VSC. The system is modelled and simulated using MATLAB and simulated responses of the system at nonlinear loads and varying environmental conditions are also validated experimentally on a prototype developed in the laboratory.
14 citations
TL;DR: A hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations is presented.
Abstract: Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.
14 citations
Caps1
TL;DR: The Modified Shuffled Frog Leaping optimization Algorithm (MSFLA) has been used to optimize the DG capacity and has been found more efficient than the other two algorithms for real power loss minimization problem.
Abstract: This paper investigates the Distributed Generation (DG) capacity optimization at location based on the incremental voltage sensitivity criteria for sub-transmission network. The Modified Shuffled Frog Leaping optimization Algorithm (MSFLA) has been used to optimize the DG capacity. Induction generator model of DG (wind based generating units) has been considered for study. Standard test system IEEE-30 bus has been considered for the above study. The obtained results are also validated by shuffled frog leaping algorithm and modified version of bare bones particle swarm optimization (BBExp). The performance of MSFLA has been found more efficient than the other two algorithms for real power loss minimization problem.
11 citations
TL;DR: A vector oriented control technique with a two-loop control scheme has been developed for operating a stand-alone three- Phase SEIG for supplying DC loads through a three-phase Pulse Width Modulated (PWM) rectifier and a close agreement between the simulated and experimental results has been confirmed.
Abstract: A vector oriented control technique with a two-loop control scheme has been developed for operating a stand-alone three-phase SEIG for supplying DC loads through a three-phase Pulse Width Modulated (PWM) rectifier. The proposed controller maintains constant load voltage with reduced harmonics at the PWM rectifier input terminals. In addition, it controls the real and reactive power flow between the SEIG and converter system. The proposed control scheme has been implemented employing dSPACE 1103 real-time controller. The successful working of the proposed control strategy has been verified for different operating conditions, by modelling the system in MATLAB/Simulink toolbox and the results are presented. A prototype system consisting of an SEIG, PWM rectifier and associated control circuits, has been built in the laboratory environment and a close agreement between the simulated and experimental results has been confirmed.
10 citations
TL;DR: The motive of research published in this paper is to propose a methodology to solve Optimal reactive power dispatch problem using two phase hybrid combination of Genetic algorithm and Particle Swarm Optimization algorithms.
Abstract: The transmission losses are more dependent upon the voltages at various load conditions. The motive of research published in this paper is to propose a methodology to solve Optimal reactive power dispatch problem using two phase hybrid combination of Genetic algorithm and Particle Swarm Optimization algorithms. Optimal reactive power dispatch tackles network loss reduction, increased power transfer capability along with the voltage control at various buses by satisfying limitations on the dependent and independent control variables. Among all Flexible AC Transmission Systems Devices, unified power flow controller abbreviated as UPFC has been chosen for the analysis to control the power system because it was found to be the most efficient in empowering transmission network using reactive power injection. Therefore, most desirable placement and competency of UPFC has been worked out in the proposed research. Two-voltage source model of UPFC has been utilized for the analysis purpose. The UPFC control parameters are chosen to be the additional control parameters for the optimal reactive power dispatch calculations. The results are obtained by applying GA and PSO separately and finally, using the combination of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The simulation is carried out on standard IEEE-30 bus test system using MATLAB. The results obtained using GA, PSO and HGAPSO were compared, and it was found that HGAPSO results prove to be operative for the proposed optimal reactive power dispatch algorithm.
9 citations
TL;DR: It was confirmed that C-FLANN trained through HS gives better prediction result than being trained through DE or RBFNN or MLP and can be used for predicting water flow in different rivers.
Abstract: In the present study, with a view to speculate the water flow of two rivers in eastern India namely river Daya and river Bhargavi, the focus was on developing Cascaded Functional Link Artificial Neural Network (C-FLANN) model. Parameters of C-FLANN architecture were updated using Harmony Search (HS) and Differential Evolution (DE). As the numbers of samples are very low, there is a risk of over fitting. To avoid this Map reduce based ANOVA technique is used to select important features. These features were used and provided to the architecture which is used to predict the water flow in both the rivers, one day, one week and two weeks ahead. The results of both the techniques were compared with Radial Basis Functional Neural Network (RBFNN) and Multilayer Perceptron (MLP), two widely used artificial neural network for prediction. From the result it was confirmed that C-FLANN trained through HS gives better prediction result than being trained through DE or RBFNN or MLP and can be used for predicting water flow in different rivers.
9 citations
TL;DR: In this paper hybrid models using neural networks are presented and novel training strategies for the neural network have been investigated for wind speed prediction.
Abstract: Large wind farms are being installed globally to meet power shortage and produce green power. The power output of the wind farm is dependent on the wind speed at any instant. In scheduling the generation and demand a few hours ahead, generators and distribution companies are required to project their schedules a priori to enable load dispatch centres to operate the grids reliably. A generation schedule is not easy with renewable sources especially wind due to the erratic nature of the wind speed. Hence it is vital to develop accurate models for wind speed prediction. In this paper hybrid models using neural networks are presented. Different pre-processing techniques for statistical input data of wind speed have been tried including wavelet decomposition. Novel training strategies for the neural network have been investigated. A generalised user friendly Graphical User Interface (GUI) tool has been developed for wind speed prediction wherein the user feeds historical data and the output of the GUI gives the predicted wind speed. The user has options to choose from different filtering techniques, training strategies and training algorithms for ANN. For the site location under consideration the mean percentage error obtained for the wind speed prediction was around 6%.
TL;DR: The level of accuracy of the method is slightly improved up to 84% accuracy, which is a positive signal for the whole process of disambiguation as it opens scope for further modification of the existing method for better result.
Abstract: An attempt is made in this paper to report how a supervised methodology has been adopted for the task of word sense disambiguation in Bangla with necessary modifications. At the initial stage, the Naive Bayes probabilistic model that has been adopted as a baseline method for sense classification, yields moderate result with 81% accuracy when applied on a database of 19 (nineteen) most frequently used Bangla ambiguous words. On experimental basis, the baseline method is modified with two extensions: (a) inclusion of lemmatization process into of the system, and (b) bootstrapping of the operational process. As a result, the level of accuracy of the method is slightly improved up to 84% accuracy, which is a positive signal for the whole process of disambiguation as it opens scope for further modification of the existing method for better result. The data sets that have been used for this experiment include the Bangla POS tagged corpus obtained from the Indian Languages Corpora Initiative, and the Bangla WordNet, an online sense inventory developed at the Indian Statistical Institute, Kolkata. The paper also reports about the challenges and pitfalls of the work that have been closely observed and addressed to achieve expected level of accuracy.
TL;DR: The test results prove that the private key is chosen optimally not repetitive or tiny and the computations in public key will not reach infinity.
Abstract: Elliptic Curve Cryptography (ECC) uses two keys private key and public key and is considered as a public key cryptographic algorithm that is used for both authentication of a person and confidentiality of data. Either one of the keys is used in encryption and other in decryption depending on usage. Private key is used in encryption by the user and public key is used to identify user in the case of authentication. Similarly, the sender encrypts with the private key and the public key is used to decrypt the message in case of confidentiality. Choosing the private key is always an issue in all public key Cryptographic Algorithms such as RSA, ECC. If tiny values are chosen in random the security of the complete algorithm becomes an issue. Since the Public key is computed based on the Private Key, if they are not chosen optimally they generate infinity values. The proposed Modified Elliptic Curve Cryptography uses selection in either of the choices; the first option is by using Particle Swarm Optimization and the second option is by using Cuckoo Search Algorithm for randomly choosing the values. The proposed algorithms are developed and tested using sample database and both are found to be secured and reliable. The test results prove that the private key is chosen optimally not repetitive or tiny and the computations in public key will not reach infinity.
TL;DR: This paper presents the design and implementation of a pipeline Analog-to-Digital Converter (ADC) for superheterodyne receiver application and uses the concepts of time interleaving and double sampling to enhance the sampling speed and to reduce the number of amplifiers used in the ADC.
Abstract: This paper presents the design and implementation of a pipeline Analog-to-Digital Converter (ADC) for superheterodyne receiver application. Several enhancement techniques have been applied in implementing the ADC, in order to relax the target specifications of its building blocks. The concepts of time interleaving and double sampling have been used simultaneously to enhance the sampling speed and to reduce the number of amplifiers used in the ADC. Removal of a front end sample-and-hold amplifier is possible by employing dynamic comparators with switched capacitor based comparison of input signal and reference voltage. Each module of the ADC comprises two 2.5-bit stages followed by two 1.5-bit stages and a 3-bit flash stage. Four such pipeline ADC modules are time interleaved using two pairs of non-overlapping clock signals. These two pairs of clock signals are in phase quadrature with each other. Hence the term quadrature parallel pipeline ADC has been used. These configurations ensure that the entire ADC contains only eight operational-trans-conductance amplifiers. The ADC is implemented in a 0.18-μm CMOS process and supply voltage of 1.8 V. The proto-type is tested at sampling frequencies of 50 and 75 MSPS producing an Effective Number of Bits (ENOB) of 6.86- and 6.11-bits respectively. At peak sampling speed, the core ADC consumes only 65 mW of power.
TL;DR: This paper presents Heat Transfer Search (HTS) algorithm for the non-linear economic dispatch problem based on the law of thermodynamics and heat transfer and test results acquired have been fitted to that acquired from other stated evolutionary techniques.
Abstract: This paper presents Heat Transfer Search (HTS) algorithm for the non-linear economic dispatch problem. HTS algorithm is based on the law of thermodynamics and heat transfer. The proficiency of the suggested technique has been disclosed on three dissimilar complicated economic dispatch problems with valve point effect; prohibited operating zone; and multiple fuels with valve point effect. Test results acquired from the suggested technique for the economic dispatch problem have been fitted to that acquired from other stated evolutionary techniques. It has been observed that the suggested HTS carry out superior solutions.
TL;DR: The major finding is that Arrhythmia ECG poses lower values of D as compared to normal, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.
Abstract: Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on “Hurst Rescaled Range Analysis”. Although the concept of applying “non-linearity” for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method “Rescaled Range Analysis”. The quantitative parameter, “Fractal Dimension” (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.
TL;DR: In this paper, the detailed simulation studies for a grid connected solar photovoltaic system (SPV) have been presented The power electronics devices like DC-DC boost converter and grid interfacing inverter are most important components of proposed system.
Abstract: In this paper, the detailed simulation studies for a grid connected solar photovoltaic system (SPV) have been presented The power electronics devices like DC–DC boost converter and grid interfacing inverter are most important components of proposed system Here, the DC–DC boost converter is controlled to extract maximum power out of SPV under different irradiation levels, while the grid interfacing inverter is utilized to evacuate the active power and feed it into grid at synchronized voltage and frequency Moreover, the grid interfacing inverter is also controlled to sort out the issues related to power quality by compensating the reactive power and harmonics current component of nearby load at point of common coupling Besides, detailed modeling of various component utilized in proposed system is also presented Finally, extensive simulations have been performed under different irradiation levels with various kinds of load to validate the aforementioned claims The overall system design and simulation have been performed by using Sim Power System toolbox available in the library of MATLAB
TL;DR: This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.
Abstract: Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.
TL;DR: In this article, an adaptive packet combining scheme has been proposed to achieve better throughput, which adapts to the channel condition to carry out transmission using PC scheme, APC scheme and SR ARQ scheme.
Abstract: The two popular techniques of packet combining based error correction schemes are: Packet Combining (PC) scheme and Aggressive Packet Combining (APC) scheme. PC scheme and APC scheme have their own merits and demerits; PC scheme has better throughput than APC scheme, but suffers from higher packet error rate than APC scheme. The wireless channel state changes all the time. Because of this random and time varying nature of wireless channel, individual application of SR ARQ scheme, PC scheme and APC scheme can’t give desired levels of throughput. Better throughput can be achieved if appropriate transmission scheme is used based on the condition of channel. Based on this approach, adaptive packet combining scheme has been proposed to achieve better throughput. The proposed scheme adapts to the channel condition to carry out transmission using PC scheme, APC scheme and SR ARQ scheme to achieve better throughput. Experimentally, it was observed that the error correction capability and throughput of the proposed scheme was significantly better than that of SR ARQ scheme, PC scheme and APC scheme.
TL;DR: Proposed Impedance network based Switched Capacitor MLI performance in stand-alone and with grid integration is analyzed with MATLAB/SIMULINK and to validate the performance of proposed ISCMLI a proto model is developed.
Abstract: In this paper, a single phase impedance network based symmetrical Multi Level Inverter (MLI) integrated to grid is presented. The proposed topology requires a reduced number of controlled switches as compared to voltage source and impedance source MLI’s. The complexity, switching losses and size decreases due to reduced number of switch count. A simple Self-Voltage Balancing Circuit technique is used for maintaining equal voltage across all DC-link capacitors. Impedance network is used for boosting the voltage so as to meet the load/grid voltage. In order to synchronize the proposed inverter with grid two control loops are used. The first loop is voltage controller, which controls the output voltage of impedance network and the second loop is a current control loop, it injects the desired current into the grid. Proposed Impedance network based Switched Capacitor MLI (ISCMLI) performance in stand-alone and with grid integration is analyzed with MATLAB/SIMULINK and to validate the performance of proposed ISCMLI a proto model is developed.
TL;DR: The usefulness of HDRI technology for photometric measurements and luminance distributions of illuminated interiors and the quality of lighting in colour viewing booth of a printing press is demonstrated.
Abstract: High Dynamic Range Imaging (HDRI) techniques for luminance measurement is gaining importance in recent years. This paper presents the application of the HDRI system for obtaining the photometric characteristics of lighting fixtures as well to assess the quality of lighting in colour viewing booth of a printing press. The process of quality control of prints in a printing press is known as graphic arts evaluation. This light booth plays a major role in the quality control of prints. In this work, Nikon D5100 camera was used to obtain the photometric characteristics of narrow beam spotlight. The results of this experiment are in agreement with photometric characteristics obtained from a standard industry grade Gonio-photometer. Similarly, Canon 60D camera was used to assess the quality of spatial luminance distribution of light in the colour viewing booth. This work demonstrates the usefulness of HDRI technology for photometric measurements and luminance distributions of illuminated interiors.
TL;DR: A non-isolated PFC converter is employed at the input of isolated converter that is capable of improving the input power quality apart from regulating the dc voltage at its output.
Abstract: Power Supplies (PSs) employed in personal computers pollute the single phase ac mains by drawing distorted current at a substandard Power Factor (PF). The harmonic distortion of the supply current in these personal computers are observed 75% to 90% with the Crest Factor (CF) being very high which escalates losses in the distribution system. To find a tangible solution to these issues, a non-isolated PFC converter is employed at the input of isolated converter that is capable of improving the input power quality apart from regulating the dc voltage at its output. This is given to the isolated stage that yields completely isolated and stiffly regulated multiple output voltages which is the prime requirement of computer PS. The operation of the proposed PS is evaluated under various operating conditions and the results show improved performance depicting nearly unity PF and low input current harmonics. The prototype of this PS is developed in laboratory environment and test results are recorded which corroborate the power quality improvement observed in simulation results under various operating conditions.
TL;DR: The paper presents a method for deriving a new voltage stability index for a power system using network partitioning technique to transform the Load Flow Jacobian Matrix of a multi-bus power system into a 2 × 2 Jacobian matrix referred to a selected bus.
Abstract: The paper presents a method for deriving a new voltage stability index for a power system using network partitioning technique. Network partitioning technique is used to transform the Load Flow Jacobian Matrix of a multi-bus power system into a 2 × 2 Jacobian Matrix referred to a selected bus. Using the elements of this transformed 2 × 2 Jacobian Matrix, a voltage stability index is proposed. IEEE 30 and IEEE 118 bus test systems were adopted to verify the validity of proposed voltage stability index.
TL;DR: In this article, a roof-top wind energy conversion system (RTWS) is proposed to extract extra amount of energy from regions rich in wind power, where a Vertical Axis Wind Turbine (VAWT) driven generator is used for energy conversion.
Abstract: Demand for clean energy is increasing day by day owing to depleting conventional energy resources and increasing global warming. This paper proposes a novel roof-top wind energy conversion system (RTWS) to extract extra amount of energy from regions rich in wind power. Unlike in conventional Wind Energy Conversion System (WECS), a Vertical Axis Wind Turbine (VAWT) driven generator is proposed to be used for energy conversion. Absence of blade-pitch control and yaw control in VAWT have been countered by a variable-flux generator. Variable flux in the generator has been achieved by mechanical means. Based upon proposed system a proof-of-concept experimental setup has been fabricated and tested for Variable Wind Constant Load (VWCL) and Constant Wind Variable Load (CWVL). Results support the hypothesis of using proposed system as RTWS under varying wind and load. The proposed system can bring revolutionary changes in the composition of energy sector.
TL;DR: In this article, a rice straw supported biomass incineration power plant was evaluated through plant performance characterization, plant economics, and co-firing issues with emission analysis, where the unutilized rice straw is found promising for heat and power generation either through incineration (direct combustion) or thermo chemical conversion.
Abstract: Biomass energy is one of the potential renewable energy sources which occupy 77% of the available natural resources of the world. In India, agro residues constitute a major part of the total annual production of the biomass resource. Rice is the major crop in India that leaves substantial quantity of straw in the field. 34% of rice straw residue produced in the country is surplus and is either left in the field as uncollected or to a large extent open-field burnt. Thus, the unutilized rice straw is found promising for heat and power generation either through incineration (direct combustion) or thermo chemical conversion. This present work envisages the comprehensive performative evaluation of a rice straw supported biomass incineration power plant mainly through plant performance characterization, plant economics, and co-firing issues with emission analysis.
TL;DR: The Neural Network Ensemble is used to increase the accuracy of the Jaya algorithm that is used for the segmentation, as well as extraction of the abnormal portion of the brain, takes less execution time as compared to Particle Swarm Optimization and Genetic Algorithm that have been used earlier.
Abstract: Brain plays an important role in performing the routine tasks But, the normal functioning of the brain is hindered because of the blockage and tumors etc There exist various classifiers for the classification of MRI images into the normal and abnormal brain This paper uses the Neural Network Ensemble to increase the accuracy of the system Jaya algorithm that is used for the segmentation, as well as extraction of the abnormal portion of the brain, takes less execution time as compared to Particle Swarm Optimization and Genetic Algorithm that have been used earlier This paper also discusses the classification of the possibility of having a benign or malignant tumor
TL;DR: Different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm are analyzed and it helps in developing a novel gender classification algorithm with less computation cost and more accuracy.
Abstract: One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.
TL;DR: In this paper modeling of STATCOM with IEEE first benchmark model is presented and a supplementary signal is developed which is capable to make the system stable for all critical values of series compensation.
Abstract: In FACTS devices supplementary signals are widely used to enhance damping and mitigation of subsynchronous resonance in power system. Subsynchronous resonance occurs due to series capacitor in the power systems. High value of series capacitive reactance may destabilize low frequency mode which is more dangerous. There are four critical values of series compensation (XC) against which rotor oscillations may be very high in IEEE first benchmark model. In this paper modeling of STATCOM with IEEE first benchmark model is presented. Then a supplementary signal is developed which is capable to make the system stable for all critical values of series compensation. The eigenvalues are presented against all four critical values of series compensation.
TL;DR: A novel algorithm for load shedding and network reconfiguration in an isolated microgrid with prioritized loads and multiple islands, which will help to quickly restore the system in the event of a fault is proposed.
Abstract: Maintenance of power balance between generation and demand is one of the most critical requirements for the stable operation of a power system network. To mitigate the power imbalance during the occurrence of any disturbance in the system, fast acting algorithms are inevitable. This paper proposes a novel algorithm for load shedding and network reconfiguration in an isolated microgrid with prioritized loads and multiple islands, which will help to quickly restore the system in the event of a fault. The performance of the proposed algorithm is enhanced using genetic algorithm and its effectiveness is illustrated with simulation results on modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid.
TL;DR: The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement of Permanent Magnet Synchronous Generator.
Abstract: This paper deals wind energy based power generation system using Permanent Magnet Synchronous Generator (PMSG). It is controlled using advanced enhanced phase-lock loop for power quality features using distribution static compensator to eliminate the harmonics and to provide KVAR compensation as well as load balancing. It also manages rated potential at the point of common interface under linear and non-linear loads. In order to have better efficiency and reliable operation of PMSG driven by wind turbine, it is necessary to analyze the governing equation of wind based turbine and PMSG under fixed and variable wind speed. For handling power quality problems, power electronics based shunt connected custom power device is used in three wire system. The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement. The performance results show the adequate performance of PMSG based power generation system and control algorithm.