Neural computing is now one of the most promising technologies in all fields of engineering,
resulting in the development of a number of Artificial Neural Networks (ANN). Double circuit transmission lines
are being employed in the distribution of power to consumers and have become more widespread than single
transmission line, as they increase the electric power transmission capacity and the reliability of an electrical
system. Losses along transmission lines occur due to faults. Possible faults on the transmission line were
predicted using Artificial Neutral Network. In this work, the simulation of fault on a 132kV double circuit
transmission lines using MATLAB was undertaken. Parameters considered during the simulation were the input
of the network which is the fault current value at each fault location while the output of the network is the fault
location. The efficiency of the neural network was tested and verified. This approach provided satisfactory
results with accuracy of 95% or higher.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
Load Balancing for Achieving the Network Lifetime in WSN-A SurveyAM Publications
a wireless sensor network is network form of sense compute, and communication elements which helps to
observe, events in a specified environment. Sensor nodes in wireless sensor network are depends on battery power they
have limited transmission range that’s why energy efficiency plays a vital role to minimize the overhead through which
the Network Lifetime can be achieved. The lifetime of network, depends on number of nodes, strength, range of area
and connectivity of nodes in the network. In this paper we are over viewing techniques which are used in wireless sensor
network for load balancing. Wireless sensor network having different nodes with different kind of energy which can be
improve the lifetime of the network and its dependability. This paper will provide the person who reads with the
groundwork for research in load balancing techniques for wireless sensor networks.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS BASED ON QOSIAEME Publication
Energy is a serious resource parameter in Wireless Sensor Networks. Utilizing energy in an effectual manner is a challenging task in Wireless Sensor Networks. This paper presents an overview on various energy efficient routing protocols which fulfills the criteria of QoS parameters. Various energy effective and QoS based routing protocols have been compared. To improve the QoS in a network, data fusion and data accumulation is considered to be one of major energy saving technique. The routing protocols based on data aggregation, reduced cost routing and secure routing are also discussed in detail. Simulation tools like NS2, NS3, OMNET etc can be used to evaluate the network performance.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
Load Balancing for Achieving the Network Lifetime in WSN-A SurveyAM Publications
a wireless sensor network is network form of sense compute, and communication elements which helps to
observe, events in a specified environment. Sensor nodes in wireless sensor network are depends on battery power they
have limited transmission range that’s why energy efficiency plays a vital role to minimize the overhead through which
the Network Lifetime can be achieved. The lifetime of network, depends on number of nodes, strength, range of area
and connectivity of nodes in the network. In this paper we are over viewing techniques which are used in wireless sensor
network for load balancing. Wireless sensor network having different nodes with different kind of energy which can be
improve the lifetime of the network and its dependability. This paper will provide the person who reads with the
groundwork for research in load balancing techniques for wireless sensor networks.
Wireless sensor network is the combination of sensor nodes where sensor nodes are distributed all over the network. There are some challenges that come into the wireless sensor network n context to energy efficiency, network lifetime, storage and battery backup. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network’s lifetime. In this paper, we have analyzed various routing techniques for WSN that increases the network lifetime and energy consumption.
A Review on Energy Efficient Modulation and Coding Techniques for Clustered W...Editor IJARCET
A standard wireless sensor network comprises of a huge number of sensor nodes with data processing and communication capabilities. The sensor nodes pass the gathered data using radio transmitter, to a sink either straightforwardly or through other nodes in a multi-hop approach. Wireless sensor network is a power consuming system since nodes perform on restricted power supply which decreases its lifetime. Optimally selected modulation and coding is extremely vital technique in wireless sensor networks. This paper surveys the performance of different modulation schemes and error control codes used in Sensor Networks. The survey also analyzes the role of modulation and coding techniques apply to different channel conditions to improve the lifetime of the clustered sensor network.
Approach to minimizing consumption of energy in wireless sensor networks IJECEIAES
The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime.
CLASS D POWER AMPLIFIER FOR MEDICAL APPLICATIONieijjournal
The objective of this research was to design a 2.4 GHz class AB Power Amplifier (PA), with 0.18um
Semiconductor Manufacturing International Corporation (SMIC) CMOS technology by using Cadence
software, for health care applications. The ultimate goal for such application is to minimize the trade-offs
between performance and cost, and between performance and low power consumption design. This paper
introduces the design of a 2.4GHz class D power amplifier which consists of two stage amplifiers. This
power amplifier can transmit 15dBm output power to a 50Ω load. The power added efficiency was 50%
and the total power consumption was 90.4 mW. The performance of the power amplifier meets the
specification requirements of the desired.
Novel framework of retaining maximum data quality and energy efficiency in re...IJECEIAES
There are various unseen and unpredictable networking states in Wireless Sensor Network (WSN) that adversely affect the aggregated data quality. After reviewing the existing approaches of data quality in WSN, it was found that the solutions are quite symptomatic and they are applicable only in a static environment; however their successful applicability on dynamic and upcoming reconfigurable network is still a big question. Moreover, data quality directly affects energy conservation among the nodes. Therefore, the proposed system introduces a simple and novel framework that jointly addresses the data quality and energy efficiency using probability-based design approach. Using a simplified analytical methodology, the proposed system offers solution in the form of selection transmission of an aggergated data on the basis of message priority in order to offer higher data utilization factor. The study outcome shows proposed system offers a good balance between data quality and energy efficiency in contrast to existing system.
Power distribution system fault monitoring device for supply networks in NigeriaIJECEIAES
Electric power is the bedrock of our modern way of life. In Nigeria, power supply availability, sufficiency and reliability are major operational challenges. At the generation and transmission level, effort is made to ensure status monitoring and fault detection on the power network, but at the distribution level, particularly within domestic consumer communities there are no fault monitoring and detection devices except for HRC fuses at the feeder pillar. Unfortunately, these fuses are sometimes replaced by a copper wire bridge at some locations rendering the system unprotected and creating a great potential for transformer destruction on overload. This study is focused on designing an on-site power system monitoring device to be deployed on selected household entry power cables for detecting and indicating when phase off, low voltage, high voltage, over current, and blown fuse occurs on the building’s incomer line. The fault indication will help in reducing troubleshooting time and also ensure quick service restoration. After design implementation, the test result confirms design accuracy, device functionality and suitability as a low-cost solution to power supply system fault monitoring within local communities.
Optimization scheme for intelligent master controller with collaboratives ene...IAESIJAI
This paper explores the use of deep learning to optimize the performance of a peer-to-peer energy system with an intelligent master controller. The goal addresses inefficiencies caused by energy seasonality by predicting hourly power consumption through a deep learning algorithm. The intelligent master controller was designed to manage the collaborative energy system, and the deep learning technique was employed as an optimization scheme to forecast power system performance for more efficient utilization. The deep learning algorithm was trained using dataset from American electric power, where consumer load data serves as input, and forecasted power serves as output. The forecasted power was then used as input to the intelligent master controller, which determines suitable power supply for generation and storage based on the predicted demand. The experiment results show promising accuracy with a root mean square error (RMSE) of 0.1819 for hourly energy consumption averaged over a year, 0.2419 for hourly energy consumption averaged over a month, 0.0662 for hourly energy consumption averaged per day, and 0.0217 for hourly energy consumption. These findings demonstrate that the system is well-trained and capable of accurately predicting the energy required by the intelligent master controller, thus enhancing the overall performance of the peer-to-peer energy system.
Influencing Factors on Power Losses in Electric Distribution NetworkIJAEMSJORNAL
Line losses reduction greatly affects the performance of the electric distribution network. This paper aims to identify the influencing factors causing power losses in that network. Newton-Raphson method is used for the loss assessment and the Sensitivity analysis by approach One-Factor-At-A-Time (OAT) for the influencing factors identification. Simulation with the meshed IEEE-30 bus test system is carried out under MATLAB environment. Among the 14 parameters investigated of each line, the result shows that the consumed reactive powers by loads, the bus voltages and the linear parameters are the most influencing on the power losses in several lines. Thus, in order to optimize these losses, the solution consists of the reactive power compensation by using capacitor banks; then the placement of appropriate components in the network according to the corresponding loads; and finally, the injection of other energy sources into the bus which recorded high level losses by using the hybrid system for instance.
Wireless sensor network is the combination of sensor nodes where sensor nodes are distributed all over the network. There are some challenges that come into the wireless sensor network n context to energy efficiency, network lifetime, storage and battery backup. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network’s lifetime. In this paper, we have analyzed various routing techniques for WSN that increases the network lifetime and energy consumption.
A Review on Energy Efficient Modulation and Coding Techniques for Clustered W...Editor IJARCET
A standard wireless sensor network comprises of a huge number of sensor nodes with data processing and communication capabilities. The sensor nodes pass the gathered data using radio transmitter, to a sink either straightforwardly or through other nodes in a multi-hop approach. Wireless sensor network is a power consuming system since nodes perform on restricted power supply which decreases its lifetime. Optimally selected modulation and coding is extremely vital technique in wireless sensor networks. This paper surveys the performance of different modulation schemes and error control codes used in Sensor Networks. The survey also analyzes the role of modulation and coding techniques apply to different channel conditions to improve the lifetime of the clustered sensor network.
Approach to minimizing consumption of energy in wireless sensor networks IJECEIAES
The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime.
CLASS D POWER AMPLIFIER FOR MEDICAL APPLICATIONieijjournal
The objective of this research was to design a 2.4 GHz class AB Power Amplifier (PA), with 0.18um
Semiconductor Manufacturing International Corporation (SMIC) CMOS technology by using Cadence
software, for health care applications. The ultimate goal for such application is to minimize the trade-offs
between performance and cost, and between performance and low power consumption design. This paper
introduces the design of a 2.4GHz class D power amplifier which consists of two stage amplifiers. This
power amplifier can transmit 15dBm output power to a 50Ω load. The power added efficiency was 50%
and the total power consumption was 90.4 mW. The performance of the power amplifier meets the
specification requirements of the desired.
Novel framework of retaining maximum data quality and energy efficiency in re...IJECEIAES
There are various unseen and unpredictable networking states in Wireless Sensor Network (WSN) that adversely affect the aggregated data quality. After reviewing the existing approaches of data quality in WSN, it was found that the solutions are quite symptomatic and they are applicable only in a static environment; however their successful applicability on dynamic and upcoming reconfigurable network is still a big question. Moreover, data quality directly affects energy conservation among the nodes. Therefore, the proposed system introduces a simple and novel framework that jointly addresses the data quality and energy efficiency using probability-based design approach. Using a simplified analytical methodology, the proposed system offers solution in the form of selection transmission of an aggergated data on the basis of message priority in order to offer higher data utilization factor. The study outcome shows proposed system offers a good balance between data quality and energy efficiency in contrast to existing system.
Power distribution system fault monitoring device for supply networks in NigeriaIJECEIAES
Electric power is the bedrock of our modern way of life. In Nigeria, power supply availability, sufficiency and reliability are major operational challenges. At the generation and transmission level, effort is made to ensure status monitoring and fault detection on the power network, but at the distribution level, particularly within domestic consumer communities there are no fault monitoring and detection devices except for HRC fuses at the feeder pillar. Unfortunately, these fuses are sometimes replaced by a copper wire bridge at some locations rendering the system unprotected and creating a great potential for transformer destruction on overload. This study is focused on designing an on-site power system monitoring device to be deployed on selected household entry power cables for detecting and indicating when phase off, low voltage, high voltage, over current, and blown fuse occurs on the building’s incomer line. The fault indication will help in reducing troubleshooting time and also ensure quick service restoration. After design implementation, the test result confirms design accuracy, device functionality and suitability as a low-cost solution to power supply system fault monitoring within local communities.
Optimization scheme for intelligent master controller with collaboratives ene...IAESIJAI
This paper explores the use of deep learning to optimize the performance of a peer-to-peer energy system with an intelligent master controller. The goal addresses inefficiencies caused by energy seasonality by predicting hourly power consumption through a deep learning algorithm. The intelligent master controller was designed to manage the collaborative energy system, and the deep learning technique was employed as an optimization scheme to forecast power system performance for more efficient utilization. The deep learning algorithm was trained using dataset from American electric power, where consumer load data serves as input, and forecasted power serves as output. The forecasted power was then used as input to the intelligent master controller, which determines suitable power supply for generation and storage based on the predicted demand. The experiment results show promising accuracy with a root mean square error (RMSE) of 0.1819 for hourly energy consumption averaged over a year, 0.2419 for hourly energy consumption averaged over a month, 0.0662 for hourly energy consumption averaged per day, and 0.0217 for hourly energy consumption. These findings demonstrate that the system is well-trained and capable of accurately predicting the energy required by the intelligent master controller, thus enhancing the overall performance of the peer-to-peer energy system.
Influencing Factors on Power Losses in Electric Distribution NetworkIJAEMSJORNAL
Line losses reduction greatly affects the performance of the electric distribution network. This paper aims to identify the influencing factors causing power losses in that network. Newton-Raphson method is used for the loss assessment and the Sensitivity analysis by approach One-Factor-At-A-Time (OAT) for the influencing factors identification. Simulation with the meshed IEEE-30 bus test system is carried out under MATLAB environment. Among the 14 parameters investigated of each line, the result shows that the consumed reactive powers by loads, the bus voltages and the linear parameters are the most influencing on the power losses in several lines. Thus, in order to optimize these losses, the solution consists of the reactive power compensation by using capacitor banks; then the placement of appropriate components in the network according to the corresponding loads; and finally, the injection of other energy sources into the bus which recorded high level losses by using the hybrid system for instance.
Electricity-theft detection in smart grids based on deep learningjournalBEEI
lectricity theft is a major concern for utilities. The smart grid (SG) infrastructure generates a massive amount of data, including the power consumption of individual users. Utilizing this data, machine learning, and deep learning techniques can accurately identify electricity theft users. A convolutional neural network (CNN) model for automatic electricity theft detection is presented. This work considers experimentation to find the best configuration of the sequential model (SM) for classifying and identifying electricity theft. The best performance has been obtained in two layers with the first layer consists of 128 nodes and the second layer is 64 nodes. The accuracy reached up to 0.92. This enables the design of high-performance electricity signal classifiers that can be used in several applications. Designing electricity signals classifiers has been achieved using a CNN and the data extracted from the electricity consumption dataset using an SM. In addition, the blue monkey (BM) algorithm is used to reduce the features in the dataset. In this respect, the focusing of this work is to reduce the features in the dataset to obtain high-performance electricity signals classifier models.
Development of a Wavelet-ANFIS based fault location system for underground po...IOSRJEEE
In the past decade, electricity demand has increased rapidly in metropolitan areas. All over the world, large scale underground power cable installations networks are replacing overhead transmission lines due to environmental concerns in densely populated areas. Underground cable systems are manufactured to have long life with reliability. However, the useful life span of these cables is not infinite. The increase in failure rates and system breakdowns on older underground power cables are now adversely impacting system reliability and many losses involved; therefore it is readily apparent that necessary action has to be taken to manage the consequences of this trend. In this paper, a method that combines wavelets and Neuro-fuzzy technique for fault location and identification is proposed. A 10km, 34.5KV, 50Hz power transmission line model was developed and different faults and locations simulated, and then certain selected features of the wavelet transformed signals were extracted to develop an ANFIS for fault location. Comparison of the ANFIS output values and the actual values show that the percentage error was established to be less than 1%. Thus, it can be concluded that the wavelet-ANFIS technique is accurate enough to be used in identifying and locating underground power line faults.
A transient current based micro grid connected power system protection scheme...IJECEIAES
Micro-grids comprise Distributed Energy Resources (DER’s) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DER’s provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DER’s from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network. This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.
New solutions for optimization of the electrical distribution system availabi...Mohamed Ghaieth Abidi
This paper deals with the availability in microgrids that are composed of a set of sources (Photovoltaic generators, wind turbines, diesel generators and batteries) and a set of loads (critical and uncritical loads). The energy produced by various sources will be grouped in an alternative bus (AC bus), and it will be distributed on loads through an electrical distribution system. The occurrence of a fault in the system can cause a total or partial unavailability of energy required by the loads. The objective of this paper is to characterize the fault caused by the limited reliability of the components of the electrical distribution system and to propose an new design methodology to optimize the availability of this system (as well as the availability of power supply) by taking into account all the economic constraints. The proposed methodology is based on the redundancy of electrical distribution paths. An application of this optimization to a petroleum platform shows clearly a high degree of supply availability distribution in microgrid.
EVOLVING TRENDS FOR ENHANCING THE ACCURACY OF FAULT LOCATION IN POWER DISTRIB...paperpublications3
Keywords:Power distribution networks, fault location, artificial intelligence, fuzzy logic, genetic algorithm, impedance-based algorithm.
Title:EVOLVING TRENDS FOR ENHANCING THE ACCURACY OF FAULT LOCATION IN POWER DISTRIBUTION NETWORKS
Author:Surender Kumar Yellagoud, Prof. T. Purnachandra Rao, Dr. G. N.Sreenivas
International Journal of Recent Research in Electrical and Electronics Engineering (IJRREEE)
ISSN 2349-7815
Paper Publications
P LACEMENT O F E NERGY A WARE W IRELESS M ESH N ODES F OR E-L EARNING...IJCI JOURNAL
Energy efficiency solutions are more vital for Gree
n Mesh Network (GMN) campuses. Today students are
benefited using these e-learning methodologies. Ren
ewable energies such as solar, wind, hydro has
tremendous applications on energy efficient wireles
s networks for sustaining the ever growing traffic
demands. One of the major issues in designing a GMN
is minimizing the number of deployed mesh routers
and gateways and satisfying the sustainable QOS bas
ed energy constraints. During low traffic periods t
he
mesh routers are switched to power save or sleep mo
de. In this paper we have mathematically formulated
a
single objective function with multi constraints to
optimize the energy. The objective is to place min
imum
number of Mesh routers and gateways in a set of can
didate location. The mesh nodes are powered using
the solar energy to meet the traffic demands. Two g
lobal optimisation algorithms are compared in this
paper to optimize the energy sustainability, to gua
rantee seamless connectivity
Energy Proficient and Security Protocol for WSN: A Reviewtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
EVOLVING TRENDS FOR ENHANCING THE ACCURACY OF FAULT LOCATION IN POWER DISTRIB...paperpublications3
Abstract: Fault location has been the subject of considerable interest to electric power utility engineers and
researchers for many years. Quantum of research done has been more on locating faults on transmission lines.
This is more justified, for the impact of transmission line faults on the power systems is greater, than that of
distribution lines. However, fault location on distribution lines is gaining attention in many utilities, especially
operating in deregulated power markets attempting to increase availability of power supply to the customers. So,
there is a need for more accurate and efficient methods for fault location, which lead to high-quality of customer
service and reduced overall cost. Fast and accurate identification of the faulted section in distribution networks
leads to least inconvenience to the connected customers. The research work on this issue has an interesting
emergence over the years. It would not be an exaggeration, if one states that still to this day there is a greater scope
for improving the accuracy. This paper reviews the work and presents a comprehensive content demonstrating the
evolution of various tools and techniques, which are ruling the research domain of fault location over a timestretch
of 10 years to this day.
Keywords: Power distribution networks, fault location, artificial intelligence, fuzzy logic, genetic algorithm,
impedance-based algorithm.
Similar to Software Based Transmission Line Fault Analysis (20)
Efforts made in many countries to stop the COVID-19 pandemic include vaccinations. However,
public skepticism about vaccines is a pressing issue for health authorities. With the COVID-19 vaccine
available,
SARS-CoV-2, as the causative agent of COVID-19, has spread throughout the world after becoming
a pandemic in March 2020. In the midst of the ongoing COVID-19 pandemic, we are also faced with another
serious health problem
This paper discusses the construction and implementation of a system for the measurement of
electrical power parameters; amperage and voltage of the hybrid system photovoltaic solar-wind, to evaluate
the system parameters and performance. The basis of the development of the measuring apparatus is the use of
an Arduino Mega 2560 to provide the interface between the electrical circuits of the sensors and the dynamics
of the voltage-amperage as well as collect data in an analog format as well as development of functional
dependence relationships. The collected data is converted into digital format and stored it in an Excel format
through the "PLX-DAQ Spreadsheet" that connects the Arduino and the PC for display and analysis of the
system parameters. The proposed technique for power measurements of AC and DC proved to be reliable and
can predict the power amperage and voltage within relative error of 1.63 % for AC and 4.16% for DC,
respectively.
The optimum speed required for mass-size reduction of shells to produce most sizes that are small
comparable with kernel sizes; coupled with retention of kernel wholeness in cracked palm nut mixture under
repeated impact was investigated. This is to enhance whole kernel separation by dry method, reduce maintenance
and production cost of palm kernel oil (PK0); and lower the risk of oil rancidity associated with split kernel
production and wet method of separation. A static nut cracker and centrifugal nut cracker were used in this study as
Test Rigs while sieves were used to grade cracked shells and whole kernels. The data generated were evaluated. A
model was developed for energy via speed required to retain kernels wholeness following repeated impact in the
crackers. Technical analysis revealed that the maximum allowable speed to retain kernel wholeness is 27.93 m/s;
the minimum allowable average speed to fragment cracked shells is 24.95 m/s. Further analysis showed that the
optimum speed and energy required for cracked nut mixture under repeated impact to have kernel wholeness
retention and production of small sizes of cracked shells relative to kernel sizes are 25.71 m/s and 0.4 J,
respectively.
This review was written to provide a comprehensive summary of the suggested etiologies of Chronic Kidney
Disease of Unknown Etiology (CKDu) in Sri Lanka. In this review, Chronic Kidney Disease (CKD) is explained
in detail and its known etiologies are discussed. CKDu is defined and its epidemiology is discussed, with the
compilation of statistic from over 15 research papers through the years 2000 to present.
This work contributes to the monitoring of water pollution of some selected Dams in Katsina
State, North western Nigeria by assessing the degree of heavy metal pollution in the Dams sediment samples.
The study was conducted in the year 2017 within some selected Dams in the State (Ajiwa, Zobe,
Sabke/Dannakola) that are beehives of fishing and Agricultural activities in Katsina State. Analysis for the
concentration of these heavy metals; Cr, Cd, Fe, Ni, Mn, Pb and Zn was conducted by the use of AAS (by
Atomic Absorption Spectrophotometry) method. Several indices were used to assess the metal contamination
levels in the sediment samples, namely; Geo-accumulation Index (Igeo), Enrichment Factor (EF),
Contamination Factor (CF), Degree of Contamination (Cd), Pollution Load Index (PLI) and Potential
Ecological Risk Index (PERI). The result of this study has shown that generally among the heavy metals
evaluated, the highest concentration was observed for Fe (range: 2.6718-4.2830 ppm), followed by Zn (range:
0.4265-0.7376 ppm), Cr (range: 0.1106-0.1836 ppm), Cd (range: 0.1333-0.1273 ppm) and Mn (range: 0.1136-
0.1271 ppm). While Pb has the lowest concentration (range: 0.0472-0.0598 ppm). For all the site sampled the
heavy metal Ni was below detection level (BDL). From the results of heavy metals I-geo values, according to
Muller’s classification, all the sediment samples from the selected dams were unpolluted (class 0). The result for
the enrichment factor has shown that for all the selected dam sediment samples the heavy metals show
deficiency to minimal enrichment. Also based on the contamination factors for all sediment samples the heavy
metal Cd has a CF values range of 0.5430-0.6665 (~1), indicating that the sediment samples are moderately
contaminated with Cd. In contrast, the rest of the heavy metals exhibit low contamination in general. The value
of PLI ranges from 0.2408 to 0.4935, indicating unpolluted to moderate pollution. The Eri values for all
samples are all < 40, presenting low ecological risk. The results suggest that the sediment samples from the
selected dams in Katsina state has low contamination by the heavy metals evaluated.
Using QR Decomposition to calculate the sum of squares of a model has a limitation that the number of rows,
which is also the number of observations or responses, has to be greater than the total number of parameters used in the
model. The main goal in the experimental design model, as a part of the Linear Model, is to analyze the estimable function
of the parameters used in the model. In order not to deal with generalized invers, partitioned design matrix may be used
instead. This partitioned design matrix method may be used to calculate the sum of squares of the models whenever the total
number of parameters is greater than the number of observations. It can also be used to find the degrees of freedom of each
source of variation components. This method is discussed in a Balanced Nested-Factorial Experimental Design.
Introduction:It has been proven twice that the Hambantota District has the highest life expectancy in male
population. This study focused to find and identify reasons for Hambantota District people to have high life
expectancy at birth.
Methodology: Research was carried out in both qualitative and quantitative phases in five MOH (Medical
Health Officer) divisions in HambantotaDistrict. Study focused on 3 age categories, 55-65 Years, 66-75 Years,
and above 76 Years. Main objectives and key information areas are Life Style and Social Behaviors, Food
Consumption and Diet, Familial Trait and Physical and Mental Health.
Findings: Majority of the male population have educated up to grade 5and most are engaged in the agriculture
while others engaged in fishery and self-employment etc. Almost everyone reachestheir workplaces by foot or by
bicycle. Many of them work less than six hours. They spend their free time with their family members and watch
TV. Most of them do not consume alcohol and smoke. Almost everyone take part in social activities. Majority eat
red rice for all three meals. Almost everyone eats fish every day. They have a high salt intake. Their parents and
ancestors have also have had a high life expectancy. Only a minority suffer from chronic illnesses. They all have
a good physical and mental health condition. They spend happy and relaxed lifestyle.
Conclusion: Healthy diet, low alcohols consumption and smoking, high iodine intake, physical activeness and
their social wellbeing effect for high life expectancy within the male population of selected five MOH divisions
in Hambantota District. They have a free and happy life. Genetics of these people also may contribute for high
life expectancy. Abundance of neem trees in this area also may effect on their high life expectancy.
A clay deposit in Chavakali of western Kenya was evaluated for its potential as refractory raw
material. The collected clay sample was crushed, sieved and the chemical composition determined in
percentage weight (wt %) of (SiO2, Al2O3, Fe2O3, etc) using Atomic Absorption Spectrophotometer (AAS). The
samples were moulded into rectangular shaped bricks of 40mm height, 40mm width and 80mm length, allowed
to dry and later fired up to a temperature of 10000C. Refractory properties like Compressive strength,
Hardness, Linear shrinkage on firing, Apparent porosity and Density were determined using standard
techniques. The result of chemical analysis indicated that the clay was composed of Silica (SiO2), 67.3%;
Alumina (Al2O3), 16.67%; Iron Oxide (Fe2O3), 3.87%; Calcium Oxide (CaO), 0.37%; Potassium Oxide (K2O),
2.30%; Sodium Oxide (Na2O), 1.39%; and other traces. The physical and mechanical tests show that the clay
has Cold Crushing Strength of 10.36MPa, Hardness of 40.080 GPa, Linear shrinkage of 6.17%, Apparent
Porosity of 32.71% and Bulk Density of 2.77g/cm3
. Chavakali clay can make better local refractory
Nihon University challenged world record of the human-powered aircraft flight based on the
regulation of Fédération Aérionautique Internationale in Kasumigaura Lake, Japan, 2014. The wing fell off in
midair immediately after take-off, the pilot landed to the lake for safety. So, the challenge failed. It guessed the
operational errors were correlated with the wing falling in midair, which had not happened in our experience.
The flight recording camera and the salvaged airplane were investigated. The fault tree analysis was conducted
for cause investigation. The wing falling was the result as the chain destruction starting from the coupling parts
being damaged in take-off. The defective take-off was caused by composite factors on only operational errors.
The risk that the ultralight airplane might disintegrate in midair by only operational error became apparent.
Due to the large-scale exploitation of mineral resources and the unreasonable human activities, the
geological disasters in Jiaozuo City have become increasingly prominent and the degree of harm increased. This
leds to a tremendous threat to human life and property safety. Jiaozuo City, the main types of geological
disasters, landslides, ground subsidence, debris flow and ground fissures. It has great significance to the
development of the city and the protection of people's life and property to explore the hidden dangers of
geological disasters and actively take preventive and control measures. The establishment of geological
hazard group measurement system of prevention and control to achieve the timely detection of geological
disasters, rapid early warning and effective avoidance.
Dangerous gas explosion accidents result in considerable amount of casualties and property damage.
Hence, an investigation on the generation of poisonous gases in gas explosions exerts important implications
for accident prevention and control and in the decision-making processes of fire rescue. Therefore, a gas
explosion piping test system is established in this paper. Experimental research on gas explosion is conducted by
selecting methane/air premixed gases with concentrations of 7%, 9%, 11%, 13%, and 15% in the gas explosive
range. This research aims to reveal the regularity of CO generation after gas explosion in pipelines.
Experimental results showed that when the gas concentration is small (< 9%), 1500–3000 ppm CO will be
produced. When the gas concentration is large (> 9%), the CO amount will reach 3000–40000 ppm. The
variation trend in CO concentration and the quantity of explosive gas are also obtained.
To evaluate the influence of the entry speed to flow field above the water surface on an object
high-speed entering into water, the flow field was measured experimentally by using an optical visualization
method. The entry speed was ranging from 0.2 to 1.5 km/s. In case that the entry speed was higher than the
sound speed of gas above the water surface, the vertical velocity of the tip of a water splash was linear to the
vertical location of the tip. The ratio between the initial vertical velocity of a water splash and the entry speed
was independent from the entry speed and was constant.A shock wave was driven above the water surface by the
entry even thoughthe entry speed was lower than the sound speed of gas above the water surface.A scaling law
for the propagation of a shock wave driven by explosion of an explosive was applicable to the propagation of
the shock wave driven by the water entry by using the kinetic energy of the entry object instead of the explosive
energy.
Pingdingshan Coal Mine district is one of the six mining areas of Henan Province, which is a
large coal base in China. After 60 years of exploitation, it has brought great benefits, at the same time,
serious geological disasters have been occurred. It has seriously damaged the normal production of the
masses, life, restricting the development of Pingdingshan coal mine economy. In this paper, the
geological disasters such as ground collapse, ground fissures and ground subsidence in Pingdingshan coal
mine are analyzed, and the degree of geological disasters in the mining area is analyzed in combination
with the severely affected mining area. Finally, reasonable and feasible countermeasures have been put
forward.
Kelud volcano is located in East Java Province, Indonesia. According to Geochemical study of
Kelud Volcano, it could be divided into 3 periods which are Kelud I (older than 100 ky BP), Kelud II (40 – 100
ky BP), and Kelud III (younger than 40 ky BP). A specific petrogenesis of Kelud are dominatad by magma
mixing and fractional crystalization. New petrological data from Kelud volcano was taken through products of
the eruption in 1990 (Vulkanian type), 2007 (Lava plug forming) and 2014 (Plinian type). Petrographic study
on these rocks showed that reverse and oscilatory zoning on plagioclases, Shieve-like and corroded textures on
plagioclases and pyroxenes are common. However, normal zoning textures were also found on plagioclases and
pyroxenes. Whole rock study on these rocks showed all rocks were classified into Basalt to Andesite in
composition with calc-alkaline group. The study indicated that their magma origin derrived from slab with
fractional crystallization during in the magma reservoir, and magma mixing processes are dominant expecially
in magma pockets. Concequently, the magma origin and petrogenesis of Kelud magma after the 1966 eruption
are still the same as those of old magma of Kelud.
Black cotton soils are among a group of soils termed as problematic soils. These soils have
undesirable characteristics in relation to construction works and therefore need some form of improvement
when encountered in construction projects. Techniques for improvement of black cotton soils include
replacement, moisture control or adding a stabilizer. Cement and/or lime has been commonly used in soil
stabilization for ages. However, due to the associated cost, required quality control and the need to utilize waste
materials in construction, new stabilizing materials are emerging. This paper presents a study on application of
quarry dust for improving properties of black cotton soil in Mbeya region, Tanzania. The targeted improvement
was to achieve minimum acceptable characteristics for road subgrade as per Tanzania standards. It was
determined that 40% by weight of quarry dust added to the black cotton soil was able to improve the
characteristics by increasing CBR value from 3.8 to 15.7 and reducing PI from 32% to 15%. It will be worthy
studying the cost implication of the suggested improvement in relation to other techniques before application of
the study findings.
High intensity rain and morphometri in Padang city cause at Arau. Morphometri
geomorphologi that is related to wide of, river network, stream pattern and gradien of river. The form wide
of DAS will be by stream pattern and level.This will influence to the number of rain. Make an index to
closeness of stream depict closeness of river stream at one particular DAS. Speed of river stream influenced
by storey, level steepness of river. Steepness storey, level is comparison of difference height of river
downstream and upstream. Ever greater of steepness of river stream, excelsior speed of river stream that
way on the contrary. High to lower speed of river stream influence occurence of floods, more than anything
else if when influenced by debit big. By using rainfall from year 2005 to year 2015, and use Thiessen method
got a rainfall. Use the DEM IFSAR, analysed sofware ARGIS, and with from earth map, the result got DAS
in at condition of floods gristle and sedimentation. There are band evakuasi for resident which data in
floods area.
The chemical (extractives and lignin) content and histological property (microscopic structure)
of tissues of Ricinodendron heudelotii (Baill, Pierre ex Pax), an angiosperm, were investigated for its potential
as a fibrous raw material for pulp and paper production. Bolts of about 70 cm were cut from the felled trees at
three different merchantable height levels of 10%, 50%, and 90% to obtain: corewood, middlewood and
outerwood samples. The fiber characteristics of the selected trees viz: the fiber length, fibre diameter and lumen
diameter were measured while the cell wall thickness was derived from the measured fibre dimensions. The
average fiber length, cell wall thickness, and lumen width, were 1.40 mm, 4.6 µm, and 32.3 µm, respectively.
The extractive and lignin contents were determined. Klason lignin content was about 30%. Extractive content of
R. heudelotii ranged from 0.41 to 0.5%. Based on these findings R. heudelotii is suitable for pulp and paper
production.
The prolific Niger Delta Basin is a mature petroleum province. Therefore, further prospectivity in
the basin lies within deeper plays which are high pressure and high temperature (HPHT) targets. One of the
main characteristics of the Niger Delta is its unique diachronous tripartite stratigraphy. Its gross onshore and
shallow offshore lithostratigraphy consists of the deep-seated Akata Formation and is virtually exclusively
shale, the petroliferous paralic Agbada Formation in which sand/shale proportion systematically increases
upward, and at the top the Benin Formation composed almost exclusively of sand. This stratigraphic pattern is
not exactly replicated in the deep offshore part of the delta.
A low-carbon steel wire of AISI 1022 is used to easily fabricate into self-drilling tapping screws,
which are widely used for construction works. The majority of carbonitriding activity is performed to improve
the wear resistance without affecting the soft, tough interior of the screws in self-drilling operation. In this
study, Taguchi technique is used to obtain optimum carbonitriding conditions to improve the mechanical
properties of AISI 1022 self-drilling tapping screws. The carbonitriding qualities of self-drilling tapping screws
are affected by various factors, such as quenching temperature, carbonitriding time, atmosphere composition
(carbon potential and ammonia level), tempering temperature and tempering time. The quality characteristics of
carbonitrided tapping screws, such as case hardness and core hardness, are investigated, and so are their
process capabilities. It is experimentally revealed that the factors of carbonitriding time and tempering
temperature are significant for case hardness. The optimum mean case hardness is 649.2HV. For the case
hardness, the optimum process-capability ratio increases by about 200% compared to the original result. The
new carbonitriding parameter settings evidently improve the performance measures over their values at the
original settings. The strength of the carbonitrided AISI 1022 self-drilling tapping screws is effectively improved.
More from International journal of scientific and technical research in engineering (IJSTRE) (20)
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water Industry Process Automation and Control Monthly - May 2024.pdf
Software Based Transmission Line Fault Analysis
1. International journal of scientific and technical research in engineering (IJSTRE)
www.ijstre.com Volume 1 Issue 3 ǁ June 2016.
Manuscript id. 697458203 www.ijstre.com Page 123
Software Based Transmission Line Fault Analysis
E. O. Ogunti1
1
(Department of Electrical and Electronics Engineering, School of Engineering and Engineering Technology/
The Federal University of Technology, Akure, Nigeria)
ogunti@gmail.com
ABSTRACT: Neural computing is now one of the most promising technologies in all fields of engineering,
resulting in the development of a number of Artificial Neural Networks (ANN). Double circuit transmission lines
are being employed in the distribution of power to consumers and have become more widespread than single
transmission line, as they increase the electric power transmission capacity and the reliability of an electrical
system. Losses along transmission lines occur due to faults. Possible faults on the transmission line were
predicted using Artificial Neutral Network. In this work, the simulation of fault on a 132kV double circuit
transmission lines using MATLAB was undertaken. Parameters considered during the simulation were the input
of the network which is the fault current value at each fault location while the output of the network is the fault
location. The efficiency of the neural network was tested and verified. This approach provided satisfactory
results with accuracy of 95% or higher.
KEYWORDS -Artificial Neutral Network (ANN), 132 kV Double Transmission Line, Multi-Layer Feed-
Forward Back propagation (MLFFBP), Matlab
I. Introduction
Electrical Power system is a complex system in the world and it consists of generation, transmission and
distribution. Challenging problems are usually encountered in the design of power systems to deliver amounts of
electrical energy in safe, clean and economical manner. Transmission lines are used to transfer the energy from
generation through distribution to the consumer. Mostly, electrical transmission line is exposed to the
environment and the possibility of experiencing faults on these lines is generally higher than that on other main
components of the electric power system. In Nigeria, the transmission lines covers thousands of kilometers over
some difficult and impossible to access terrains. When a fault occurs on an electrical transmission line, it is very
important to detect and locate it in order to make necessary repairs and to restore power as soon as possible to
the consumers. This may take days and weeks in any part of Nigeria throwing the consumers into darkness with
attendant health and economic losses. The time needed to determine the fault point along the line will affect the
quality of the power delivery [1]. In power system stability, many different techniques can be utilized for fault
analysis, however most of them are based on assumed fault equations and the parameters of the equation are
estimated through curve fittings. Because of complexity of power system, the assumed equations may not
capture power, frequency, current, and voltage phenomena simultaneously and accurately. To improve the
power sector, the Nigerian government has undertaken long-term structural reforms (which started in 2005 but
gained momentum in 2010) focused on privatizing legacy power assets and instituting regulatory reform.
However, these reforms have proved insufficient and more must be done to address the challenges in the sector,
which include sub-optimal utilization of generation plants (partly due to insufficient gas molecule availability),
inadequate transmission infrastructure and high distribution losses (with related liquidity and viability issues).
Of the four segments of the power chain system, distribution is the aspect most visible to the consumer,
and this segment in Nigeria can incur close to 46% losses due to technical, commercial and collection issues [2].
2. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 124
Figure 1: Overview of distribution performance in 2014, adapted from [2]
In attempt to solve its distribution problems, the government sold its principal shares in the power
sector to private investors. This process started in 2005, went through a change of government and then picked
up again in 2010. The investors that took over were called DISCOs with the promise of grid expansion, and the
increase in the number of new connections and capex to be spent on meters.However, the DISCOs face
significant financial pressures largely due to low energy tariffs, outages and the unwillingness of the customers
to pay for non-existent power. In March 2015, the regulator ruled that collection losses could not be passed on to
consumers via retail tariffs. With collection losses set at zero, distribution companies would have needed to
achieve dramatically lower loss levels to meet their loss commitments. Faced with this situation, several
distribution companies declared force majeure, triggering a regulatory crisis and a temporary loss of investor
confidence [2]. Most of the losses shown in Fig. 1 are due to one form of fault or the other on the transmission
line before the power arrive at the consumer. It therefore becomes extremely necessary to investigate cheap and
fast new fault modeling techniques for power system stability analysis in Nigeria since most operators are weary
of new heavy financial investment in the power sector.
Fault (which in Nigeria may occur as a result of lightning strikes on bus bar, collapse of transmission
line, accidental short circuit by snake, kite and bird,tree or bamboo touching line, human mistake) is an
unwanted condition that occurs in power system. Fault occurs due to insulation breakdown at one or more point
on a conductor or a conducting object coming in contact with live point as indicated above. These conditions
will affect voltage and current value on power system. Transmission line is the part of power system in which
fault most likely occur. Researches on fault analysis are very important for protection purposes to enhance
reliability of electricity supply. Double-circuit lines are now widely used in transmission systems due to their
significant economic and environmental advantages over single-circuit lines. Double circuit transmission lines
are defined as lines that share the same structure or a portion of their length. These lines have been extensively
utilized in modern power systems to enhance the power transfer, reliability and security for the transmission of
electrical energy.
Accurate detection and location of faults for an inspection-repair purpose is very important for accelerating
service restoration, thus reducing outage time, operating costs and consumers’ complaints. However, the fault
analysis for double-circuit lines is much more complicated than single circuit lines because of mutual couplings
between two circuits and the existence of more complex fault types.
3. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 125
There are many research work on fault detection through which different approaches have been
proposed to detect faults. The study in [1] used an offline detector method to detect faulty line by injecting
special frequency signals to the line. This method was neither safe nor convenient. Other methods identify the
phase to ground fault according to the changes of the three phase voltages and currents but cannot properly
distinguish between faulty line and healthy lines. Recently, with the advent of the microprocessors, various
analytical methods have been developed and tested to detect faults. Unfortunately, these methods use digital
signal processing which take time and do not have the ability to adapt dynamically to the system operating
condition. They are likely to make incorrect decision if the signals are noisy [3]. Artificial neural network on the
other hand, provide a promising alternative, because they can handle most situations which cannot be defined
sufficiently for finding a deterministic solution. The ANNs takes into account their noise immunity, robustness,
fault tolerance and generalization capabilities. The ANN networks have ability to learn the desired input-output
mapping based on training example, without looking for an exact mathematical model. The intent of this paper
is to analyze symmetrical faults on 132kV transmission line by modeling and simulating a double circuit 132kV
transmission line using MATLAB toolbox and Simulink. The detection of potential faults on the model line was
done using Artificial Neural Network (ANN) and validation of the ANN in fault prediction along transmission
lines. This approach is simple and cost effective and have a fast response time.
II. Artificial Neural Network Development
Neural network technology is an emerging technology in electrical engineering for power system modeling,
simulation, optimization and design. Multilayer Perceptron (MLP), Radial Basis Function (RBF), Knowledge
Based Neural Network (KBNN), Wavelet network and Recurrent Neural Network (RNN) are commonly used
NN structures. Selection of NN structure and training algorithm are two major issues in developing NN model.
The most important and time consuming step in model development is NN training. The NN model uses the
measured or simulated data for training. Training is an optimization process in the weight space and is often
done using optimization–based training algorithm such as backpropagation (BP). Training algorithms are an
internal part of neural model development. Any alternative structure may still fail to give a desired model,
unless trained by a suitable training algorithm [3]. The proper training algorithm manages to reduce the training
time by achieving better accuracy. A distinct advantage of neural computation is that, after proper training, it
completely bypasses the repeated use of complex iterative processes for new design presented to it.
2.2 Structure of Multi-Layer Feed-Forward Network
The standard multilayer feed-forward network (Fig. 2) is employed as the network architecture in this study.
The multi-layer feed-forward network is a network of neurons and synapses organized in the form of layers.
There are three kinds of layers in an ANN: the input layer, hidden layer and output layer. The function of the
input layer is simply to buffer the external inputs to the network. The hidden neurons have no connections to the
inputs or outputs. By including hidden layers, the network is empowered to extract higher-order statistics as the
network acquires a global perspective despite its local connectivity by virtue of the extra set of synaptic
connections and the extra dimension of neural interactions [4].
INPUT LAYER HIDDEN LAYER OUTPUT LAYER
Figure 2: Structure of Multi-Layer Feed-forward Network.
4. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 126
Basically, ANNs consist of a network of neurons and synapses arranged in layers, the source nodes in the input
layer of the network supply respective elements of the activation pattern, which constitute the input signals
applied to the neurons (computation nodes) in the second layer. The output signals of the second layer are used
as inputs to the third layer, and so on, for the rest of the network
2.3 Transmission Line Model
To determine the performance of the proposed neural network-based fault prediction, a 132 kV, 100km double
circuit transmission line extending between two sources as shown in Fig. 3 was developed for this study.
Figure 3: 132 kV Double Circuit Transmission Line Model
5. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 127
.All components were modeled by the MATLAB Simulink and Sim-Power System toolbox. The input and
output data used for training and testing the neural fault detector were obtained from the Sink/End of the power
system model. A highly accurate transmission line simulation technique (Fig. 4) was utilized to produce voltage
and current waveforms for phase to ground fault.
III. Methodology
For the design of a neural network system for the prediction of double circuit transmission line fault, a
FFBP algorithm was used which consists of three layers: input, hidden and output. The input and output layers
were selected to be the best that suits the requirement of the design. Sufficient amount of data were generated
for the training from the simulation of a model transmission line and the execution of algorithm starts with the
training process of ANN model (Fig. 2).Fortescu’s theorem was utilized to obtain the power system component
as shown in Fig. 4. After executing the algorithm the output was compared with the required target. When the
outcome of algorithm gave better result, then the ANN model was tested with new data to determine the
accuracy of the ANN model. The selection of number of neurons used for hidden layers and value of moment
count (mc) in algorithm plays very important role in providing higher accuracy for the developed ANN model.
When the accuracy was not achieved, the by number of neurons for hidden layers were changed along with the
number of epochs, so as to develop appropriate ANN model for the fault prediction.
Figure 4: Symmetrical component circuits in three phase balanced system
6. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 128
IV. Results and Discussion
In order to evaluate the performance of proposed FFBP-ANN based model for fault prediction on the
designed transmission line [5], simulated results were obtained from the modeled 132 KV double transmission
line. 81 input-output training patterns were used for training the proposed 3-20-3 ANN structure with the
following learning parameters: performance goal (Mean Square Error (MSE)) = 0.00771454, learning rate =
0.05 and maximum number of epochs = 21. The learning characteristic of proposed MLFFBP-ANN based
model is shown in Fig. 5.
Figure 5: Learning Characteristic of FFBP-ANN
It has been observed that total number of 21 epochs was needed to reduce MSE level to as low a value as
0.00771454. Achievement of such a low value of performance goal (MSE) indicates that trained ANN model is
an accurate model for predicting three phases to ground fault on the transmission line.
4.1 Regression Analysis of output and Targets
The regression analysis of ANN is shown in Fig. 6 for the training output versus target, validation output versus
target and test output versus target in which their regression data were expected to be less than one or equal to
one for accurate fault current input. In this study, the regression analysis is equal to 0.9627 (96.27%) for
Training outputs versus Targets, 0.89988 (89.99%) for Validation outputs versus Targets, 0.9823 (98.23%) for
Test outputs versus Targets which indicate the accurate results for the proposed ANN network.
7. Software Based Transmission Line Fault Analysis
Manuscript id. 697458203 www.ijstre.com Page 129
Figure 6: Training State of ANN
V. Conclusion
This study was conducted to analyze three-phase to ground fault on 132 kV double transmission lines span
across 100km range. The fault was simulated at different distances from the proposed transmission line model
and data were obtained for the Artificial Neural Network. The result of the analysis shows that the ANN has low
mean square error of 0.00771454, learning rate=0.05 and maximum number of epochs = 21. The regression
result indicated for the proposed ANN network shows the level accuracy of 95% higher. The design and
simulation of the faults was done successfully using Sim Power Systems Toolbox in MATLAB Software. This
technique is fast, cheap and reliable and can help the Nigerian power sector in quickly predicting faults thereby
lowering the down time in the power sector
References
[1] J. Barros and J. M Drake, “Real Time Fault Detection and Classification In Power System using Microprocessor” IEE Proc.
Gener. Transm. Distrib., Vol. 141, No. 4, 1994, pp. 315-322.
[2] Office of the Vice President, Nigeria, “Nigeria Baseline Power Report, 2015.
[3] A. T. Johs and R. K Aggarwal, “Digital Simulation of Fault E.H.V Transmission Line with Particular Reference to Very High
Speed Protection” IEE Proc. Gener. Transm. Distrb., Vol. 123, No.4, 1976, pp. 353-359.
[4] H. Simon (2004), “Neural Network: A Comprehensive Foundation”, Prentice Hall, Parparganj, Delhi, India.
[5] J. Anamika, A. S. Thoke, and R. N. Patel,” Fault Classification of Double Circuit Transmission Line Using Artificial Neural
Network”, World Academy of Science, Engineering and Technology, Vol.46, 2008, pp. 901-906.