This document discusses optimization techniques that can be applied to synchronous generators. It provides an overview of various optimization algorithms including ant colony optimization, artificial bee colony algorithm, genetic algorithm, and particle swarm optimization. These algorithms are surveyed as potential methods for modeling synchronous generators through parameter estimation and for solving problems like optimal power flow. The document also provides context on why optimization is important for synchronous generators and power systems in areas like accurate modeling, parameter estimation, and addressing challenges like uncertainty.
A Particle Swarm Optimization for Optimal Reactive Power DispatchIJRST Journal
This paper presents particle swarm optimization (PSO) based approach for solving optimal reactive power dispatch for minimizing power losses. The control variables are bus voltage magnitudes (continuous type), transformer tap settings (discrete type) and reactive power generation of capacitor banks (discrete type). The algorithm solution of PSO is tested on a standard IEEE 30 Bus system. The intention is to minimize power losses by optimizing the reactive power dispatch with optimal setting of control variables without violating inequality constraints and satisfying equality constraint. The detailed results for different cases have been listed
Security Constraint Unit Commitment Considering Line and Unit Contingencies-p...IJAPEJOURNAL
This summary provides the key details about the document in 3 sentences:
The document presents a new approach for security constrained unit commitment that considers both generator and transmission line contingencies using an incidence matrix methodology. It formulates the security constrained unit commitment problem and proposes modeling the optimal power flow using an incidence matrix to overcome challenges of admittance matrix based methods. The methodology allows easier modeling of multiple contingencies without changes to the network topology.
A Critical Review on Employed Techniques for Short Term Load ForecastingIRJET Journal
This document discusses techniques for short term load forecasting. It begins by defining the importance of load forecasting for electric utilities in planning energy purchasing and generation. It then reviews various short term load forecasting methods including artificial neural networks, fuzzy logic, genetic algorithms, and time series approaches. Finally, it provides details on artificial neural networks and their benefits for load forecasting applications. In summary, the document provides an overview of short term load forecasting and a critical review of techniques such as artificial neural networks, fuzzy logic and genetic algorithms.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Electric Load Forecasting Using Genetic Algorithm – A Review IJMER
Many real-world problems from operations research and management science are very
complex in nature and quite hard to solve by conventional optimization techniques. So, intelligent
solutions based on genetic algorithm (GA), to solve these complicated practical problems in various
sectors are becoming more and more widespread nowadays. GAs are being developed and deployed
worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and
explanation capabilities.
This paper provides an overview of GAs, as well as their current use in the field of electric load
forecasting. The types of GA are outlined, leading to a discussion of the various types and parameters of
load forecasting. The paper concludes by sharing thoughts and estimations on GA for load forecasting
for future prospects in this area. This review reveals that although still regarded as a novel
methodology, GA technologies are shown to have matured to the point of offering real practical benefits
in many of their applications.
HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in...TELKOMNIKA JOURNAL
Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made.
IRJET- Particle Swarm Intelligence based Dynamics Economic Dispatch with Dail...IRJET Journal
This document discusses particle swarm intelligence techniques for solving economic load dispatch problems. It begins with an abstract that introduces economic load dispatch as a technique for allocating power generation levels among generating units to minimize costs while meeting demand and operational constraints. It then provides background on economic load dispatch and describes how particle swarm optimization can be applied to solve non-convex economic dispatch problems. Finally, it reviews several related works applying evolutionary algorithms like particle swarm optimization, genetic algorithms, and cuckoo search to economic load dispatch problems.
Grid Connected Electricity Storage Systems (2/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
A Particle Swarm Optimization for Optimal Reactive Power DispatchIJRST Journal
This paper presents particle swarm optimization (PSO) based approach for solving optimal reactive power dispatch for minimizing power losses. The control variables are bus voltage magnitudes (continuous type), transformer tap settings (discrete type) and reactive power generation of capacitor banks (discrete type). The algorithm solution of PSO is tested on a standard IEEE 30 Bus system. The intention is to minimize power losses by optimizing the reactive power dispatch with optimal setting of control variables without violating inequality constraints and satisfying equality constraint. The detailed results for different cases have been listed
Security Constraint Unit Commitment Considering Line and Unit Contingencies-p...IJAPEJOURNAL
This summary provides the key details about the document in 3 sentences:
The document presents a new approach for security constrained unit commitment that considers both generator and transmission line contingencies using an incidence matrix methodology. It formulates the security constrained unit commitment problem and proposes modeling the optimal power flow using an incidence matrix to overcome challenges of admittance matrix based methods. The methodology allows easier modeling of multiple contingencies without changes to the network topology.
A Critical Review on Employed Techniques for Short Term Load ForecastingIRJET Journal
This document discusses techniques for short term load forecasting. It begins by defining the importance of load forecasting for electric utilities in planning energy purchasing and generation. It then reviews various short term load forecasting methods including artificial neural networks, fuzzy logic, genetic algorithms, and time series approaches. Finally, it provides details on artificial neural networks and their benefits for load forecasting applications. In summary, the document provides an overview of short term load forecasting and a critical review of techniques such as artificial neural networks, fuzzy logic and genetic algorithms.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Electric Load Forecasting Using Genetic Algorithm – A Review IJMER
Many real-world problems from operations research and management science are very
complex in nature and quite hard to solve by conventional optimization techniques. So, intelligent
solutions based on genetic algorithm (GA), to solve these complicated practical problems in various
sectors are becoming more and more widespread nowadays. GAs are being developed and deployed
worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and
explanation capabilities.
This paper provides an overview of GAs, as well as their current use in the field of electric load
forecasting. The types of GA are outlined, leading to a discussion of the various types and parameters of
load forecasting. The paper concludes by sharing thoughts and estimations on GA for load forecasting
for future prospects in this area. This review reveals that although still regarded as a novel
methodology, GA technologies are shown to have matured to the point of offering real practical benefits
in many of their applications.
HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in...TELKOMNIKA JOURNAL
Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made.
IRJET- Particle Swarm Intelligence based Dynamics Economic Dispatch with Dail...IRJET Journal
This document discusses particle swarm intelligence techniques for solving economic load dispatch problems. It begins with an abstract that introduces economic load dispatch as a technique for allocating power generation levels among generating units to minimize costs while meeting demand and operational constraints. It then provides background on economic load dispatch and describes how particle swarm optimization can be applied to solve non-convex economic dispatch problems. Finally, it reviews several related works applying evolutionary algorithms like particle swarm optimization, genetic algorithms, and cuckoo search to economic load dispatch problems.
Grid Connected Electricity Storage Systems (2/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
Optimal design of adaptive power scheduling using modified ant colony optimi...IJECEIAES
For generating and distributing an economic load scheduling approach, artificial neural network (ANN) has been introduced, because power generation and power consumption are economically non-identical. An efficient load scheduling method is suggested in this paper. Normally the power generation system fails due to its instability at peak load time. Traditionally, load shedding process is used in which low priority loads are disconnected from sources. The proposed method handles this problem by scheduling the load based on the power requirements. In many countries the power systems are facing limitations of energy. An efficient optimization algorithm is used to periodically schedule the load demand and the generation. Ant colony optimization (ACO) based ANN is used for this optimal load scheduling process. The present work analyse the technical economical and time-dependent limitations. Also the works meets the demanded load with minimum cost of energy. Inorder to train ANN back propagation (BP) technics is used. A hybrid training process is described in this work. Global optimization algorithms are used to provide back propagation with good initial connection weights.
IRJET- Optimal Power Flow Solution of Transmission Line Network of Electric p...IRJET Journal
This document discusses using a genetic algorithm to solve the optimal power flow problem in large power transmission networks. The optimal power flow problem aims to minimize generation costs while meeting operational constraints. A genetic algorithm is proposed to solve this problem globally and efficiently. The controllable variables are divided into dynamic constraints directly impacting cost and static constraints maintained within limits by the load flow. The algorithm is tested on the IEEE 30-bus system and shown to effectively find the optimal solution. Genetic algorithms are well-suited for this problem as they can evaluate multiple solutions in parallel without requiring derivative information like traditional methods.
Techno-economical Unit Commitment Using Harmony Search Optimization ApproachIJAPEJOURNAL
In this paper, Security-Constrained Unit Commitment (SCUC) model is proposed in a restructured power system. This model consists of a closed-loop modified Unit Commitment (UC) and Security-constrained Optimal Power Flow (SCOPF). The objective of this SCUC model is to obtain the maximum social welfare-based system operating cost while maintaining the system security. In conventional power systems, the demand was forecasted before market operation and determined as a fixed constant. Supplying this demand was therefore considered as a constraint. However, in restructured power system which is based on Standard Market Design (SMD), DISCOs offer the demand and their proposed prices; therefore the demand is modeled as an elastic load. Independent System Operator (ISO) is responsible for operating the power market. The ISO performed the power market using the SCUC software to obtain feasible and economical operation as much as possible. In this paper, Harmony Search Algorithm (HSA) has been implemented to solve SCUC problem. Since the SCUC problem is a non-linear, mixed integer, large scale and non-convex problem, harmony search optimization is addressed as an efficient technique to overcome the aforementioned challenges. The simulation results show that the presented method is both satisfactory and consistent with expectation.
This document provides an overview of using neural network techniques in power systems. It discusses how neural networks have been applied to areas like fault diagnosis, security assessment, load forecasting, economic dispatch, and harmonic analysis. The number of published papers in these areas has grown significantly from 1990-1996 to 2000-2005, particularly in load forecasting, fault diagnosis/location, economic dispatch, security assessment, and transient stability. The document then reviews in more detail how neural networks have been applied to load forecasting, fault diagnosis/location, and economic dispatch problems in the power industry.
This paper presents a novel approach for static transmission expansion planning and
allocation of the associated expansion costs to individual market entities in a restructured power
system. The approach seeks the optimal addition of transmission lines among the possible candidate
transmission lines minimizing the overall system costs and at the same time satisfying the system
operational and security constraints. Novelty of the approach lies in applying a widely known
technique used for overload security analysis to an area such as Transmission expansion planning.
Transmission expansion costs are allocated using distribution factors to the individual entities in a
fair and transparent manner. The results for modified Garver Test system demonstrate that the
approach with the advantage of its simplicity can be applied to transmission expansion planning and
cost allocation in restructured power system
IRJET- Reducing electricity usage in Internet using transactional dataIRJET Journal
This document summarizes a research paper that proposes a method to reduce electricity usage and costs for internet services by optimizing how transactional data is mapped across geographically distributed data centers. It formulates the problem as a stochastic programming problem to maximize energy utilization within a cost budget. An efficient online algorithm is developed using Lyapunov optimization to map user requests to data centers based on changing factors like electricity prices and workload, with the goal of significantly reducing costs compared to baseline strategies. The system architecture involves front-end servers collecting user requests and dispatching them to appropriate back-end data centers for processing.
Optimal Power Flow With UPFC Using Fuzzy- PSO With Non-Smooth Fuel Cost FunctionIJERA Editor
This paper presents an efficient and reliable evolutionary based approach to solve the Optimal Power Flow problem in electrical power network. The Particle Swarm Optimization method is used to solve optimal power Flow problem in power system by incorporating a powerful and most versatile Flexible Alternating Current Transmission Systems device such as Unified power Flow Controller. It is a new device in FACTS family and has great flexibility that can control Active power, Reactive power and voltage magnitudes simultaneously. In this paper optimal location is find out using Fuzzy approach and control settings of UPFC are determined by PSO. The proposed approach is examined on IEEE-30 bus system with different objective function that reflects fuel cost minimization and fuel cost with valve point effects. The test results show the effectiveness of robustness of the proposed approachcompared with the existing results in the literature.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMaeijjournal
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its
exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is
equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the
optimization of the generative units to minimize the full action cost regarding problem constraints. In this
article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in
a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power
system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
The document describes a two-stage method for optimal allocation of capacitors in a radial distribution system. In the first stage, loss sensitivity factors are used to calculate candidate locations for capacitors. In the second stage, a harmony search algorithm is used to minimize total costs, including capacitor costs and power loss costs, by determining the optimal capacitor sizes and numbers placed at the candidate locations. The method is tested on 33-bus and 69-bus test systems and results in reduced power losses and costs compared to the base case without capacitors.
Electricity Generation Scheduling an Improved for Firefly Optimization AlgorithmIRJET Journal
This document describes using an improved firefly optimization algorithm to schedule electricity generation from thermal and wind power plants. The algorithm aims to minimize total generation costs while meeting load demand and reserve requirements, taking into account wind power availability constraints and both generation unit and system constraints. It formulates the objective function and constraints for the generation scheduling problem and applies the firefly algorithm to a test system with 30 conventional units and 4 wind farms, comparing results to a particle swarm optimization method. The firefly algorithm performance is found to provide better schedules with lower total costs compared to particle swarm optimization.
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...IJECEIAES
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Economical and Reliable Expansion Alternative of Composite Power System under...IJECEIAES
The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions.
Multi objective economic load dispatch using hybrid fuzzy, bacterialIAEME Publication
The document summarizes a research paper that proposes a new approach for solving the economic load dispatch problem using a hybrid fuzzy, bacterial foraging-Nelder–Mead algorithm. The economic load dispatch problem minimizes generation costs while satisfying load demand under system constraints. The proposed approach considers generation costs, spinning reserve costs, and emission costs simultaneously. It also accounts for valve-point effects, prohibited operating zones, and other practical constraints. A hybrid bacterial foraging and Nelder–Mead algorithm combined with fuzzy logic is used to solve the optimization problem. Simulation results show the advantages of the proposed method in reducing total system costs.
IRJET - Optimal Parameters of Electro-Chemical MachiningIRJET Journal
This document discusses optimizing the parameters of electrochemical machining (ECM) using genetic algorithms. The optimization problem aims to maximize the material removal rate by selecting optimal values for the design variables of electrolyte concentration, flow rate, applied voltage, and feed rate. Genetic algorithms from MATLAB are applied to solve the optimization problem and determine the optimal parameter values for ECM. The results found the maximum material removal rate was achieved with electrolyte concentration of 18.3, flow rate of 5, applied voltage of 15 volts, and feed rate of 0.9.
Grid Connected Electricity Storage Systems (1/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
This document provides a literature survey of recent methods for solving the optimal power flow (OPF) problem. It begins with an introduction to OPF, describing it as a nonlinear optimization problem that aims to optimize the operation of power systems while meeting constraints. It then categorizes OPF solution methods as conventional (e.g. Newton, gradient) or intelligent (e.g. artificial neural networks, genetic algorithms) and provides examples of each. The document surveys specific OPF formulations and solution techniques in detail. It concludes by discussing ongoing challenges for OPF methods related to power system modeling and operations in deregulated electricity markets.
IRJET- Optimal Placement and Size of DG and DER for Minimizing Power Loss and...IRJET Journal
This document presents a study on using optimization techniques to determine the optimal placement and sizing of distributed generation (DG) and distributed energy resources (DER) in a 69-bus distribution system. The study uses two optimization algorithms - Grasshopper Optimization Algorithm (GOA) and Moth Flame Optimization (MFO) - to minimize power losses and annual energy losses at different load levels. The results show that MFO performs better, identifying bus locations 61, 11, and 18 as optimal for DG placement, reducing losses more than GOA. For DER placement using MFO, losses are minimized by placing DG at buses 69, 61, 22 and capacitors at buses 61, 49, 12. Overall, the
IRJET- A Research on Vibration Analysis & Optimization of Housing for ECU in ...IRJET Journal
This document discusses a research project that aims to analyze and optimize the housing for an electronic control unit (ECU) in an automobile using finite element analysis (FEA) and an FFT analyzer. The researchers first design an ECU housing model using CAD software. They then perform modal and harmonic analysis using FEA to investigate the housing's mode shapes and response at different frequencies. Experimental modal analysis is also conducted using an accelerometer, impact hammer, and FFT analyzer. The FEA results are compared to the experimental results. The objective is to minimize vertical vibrations in the ECU housing by adding stiffening ribs and optimizing the design to withstand vibrations from the engine.
1) The document discusses speed control of a universal motor using two controllers - an output rate controller and an output reset controller. Ant colony optimization is used to tune the parameters of the controllers.
2) Mathematical models of the universal motor are developed. Simulation results show that the proposed ant colony optimization technique tunes the controllers' parameters optimally, improving their performance for speed control of the motor under varying load conditions.
3) The tuning results in zero overshoot and undershoot, slight rise and settling times, and a fast response for the motor speed when subjected to different load disturbances.
Analysis and implementation of local modular supervisory control forIAEME Publication
1. The document describes the analysis and implementation of a local modular supervisory control system for a manufacturing cell using programmable logic controllers (PLCs).
2. A local modular approach is used where modular supervisors are obtained for each behavioral specification by considering only locally affected subsystems, avoiding state space explosion.
3. The modular supervisors are implemented on the PLC in a three-level structure that executes the supervisors concurrently and interfaces them to the physical system.
IRJET- Performance Improvement of the Distribution Systems using Meta-Heu...IRJET Journal
This document summarizes a research paper that proposes using a Whale Optimization Algorithm (WOA) to optimize the control of photovoltaic (PV) systems connected to distribution networks in Egypt. The high penetration of PV systems can cause voltage issues in distribution grids. The paper aims to enhance distribution network performance by optimally designing a proportional-integral controller for PV inverters using WOA. WOA is inspired by the hunting behavior of humpback whales and is applied to minimize voltage deviations across the network. The effectiveness of the WOA-designed controller is evaluated through simulations and compared to controllers designed using genetic algorithms.
Optimal design of adaptive power scheduling using modified ant colony optimi...IJECEIAES
For generating and distributing an economic load scheduling approach, artificial neural network (ANN) has been introduced, because power generation and power consumption are economically non-identical. An efficient load scheduling method is suggested in this paper. Normally the power generation system fails due to its instability at peak load time. Traditionally, load shedding process is used in which low priority loads are disconnected from sources. The proposed method handles this problem by scheduling the load based on the power requirements. In many countries the power systems are facing limitations of energy. An efficient optimization algorithm is used to periodically schedule the load demand and the generation. Ant colony optimization (ACO) based ANN is used for this optimal load scheduling process. The present work analyse the technical economical and time-dependent limitations. Also the works meets the demanded load with minimum cost of energy. Inorder to train ANN back propagation (BP) technics is used. A hybrid training process is described in this work. Global optimization algorithms are used to provide back propagation with good initial connection weights.
IRJET- Optimal Power Flow Solution of Transmission Line Network of Electric p...IRJET Journal
This document discusses using a genetic algorithm to solve the optimal power flow problem in large power transmission networks. The optimal power flow problem aims to minimize generation costs while meeting operational constraints. A genetic algorithm is proposed to solve this problem globally and efficiently. The controllable variables are divided into dynamic constraints directly impacting cost and static constraints maintained within limits by the load flow. The algorithm is tested on the IEEE 30-bus system and shown to effectively find the optimal solution. Genetic algorithms are well-suited for this problem as they can evaluate multiple solutions in parallel without requiring derivative information like traditional methods.
Techno-economical Unit Commitment Using Harmony Search Optimization ApproachIJAPEJOURNAL
In this paper, Security-Constrained Unit Commitment (SCUC) model is proposed in a restructured power system. This model consists of a closed-loop modified Unit Commitment (UC) and Security-constrained Optimal Power Flow (SCOPF). The objective of this SCUC model is to obtain the maximum social welfare-based system operating cost while maintaining the system security. In conventional power systems, the demand was forecasted before market operation and determined as a fixed constant. Supplying this demand was therefore considered as a constraint. However, in restructured power system which is based on Standard Market Design (SMD), DISCOs offer the demand and their proposed prices; therefore the demand is modeled as an elastic load. Independent System Operator (ISO) is responsible for operating the power market. The ISO performed the power market using the SCUC software to obtain feasible and economical operation as much as possible. In this paper, Harmony Search Algorithm (HSA) has been implemented to solve SCUC problem. Since the SCUC problem is a non-linear, mixed integer, large scale and non-convex problem, harmony search optimization is addressed as an efficient technique to overcome the aforementioned challenges. The simulation results show that the presented method is both satisfactory and consistent with expectation.
This document provides an overview of using neural network techniques in power systems. It discusses how neural networks have been applied to areas like fault diagnosis, security assessment, load forecasting, economic dispatch, and harmonic analysis. The number of published papers in these areas has grown significantly from 1990-1996 to 2000-2005, particularly in load forecasting, fault diagnosis/location, economic dispatch, security assessment, and transient stability. The document then reviews in more detail how neural networks have been applied to load forecasting, fault diagnosis/location, and economic dispatch problems in the power industry.
This paper presents a novel approach for static transmission expansion planning and
allocation of the associated expansion costs to individual market entities in a restructured power
system. The approach seeks the optimal addition of transmission lines among the possible candidate
transmission lines minimizing the overall system costs and at the same time satisfying the system
operational and security constraints. Novelty of the approach lies in applying a widely known
technique used for overload security analysis to an area such as Transmission expansion planning.
Transmission expansion costs are allocated using distribution factors to the individual entities in a
fair and transparent manner. The results for modified Garver Test system demonstrate that the
approach with the advantage of its simplicity can be applied to transmission expansion planning and
cost allocation in restructured power system
IRJET- Reducing electricity usage in Internet using transactional dataIRJET Journal
This document summarizes a research paper that proposes a method to reduce electricity usage and costs for internet services by optimizing how transactional data is mapped across geographically distributed data centers. It formulates the problem as a stochastic programming problem to maximize energy utilization within a cost budget. An efficient online algorithm is developed using Lyapunov optimization to map user requests to data centers based on changing factors like electricity prices and workload, with the goal of significantly reducing costs compared to baseline strategies. The system architecture involves front-end servers collecting user requests and dispatching them to appropriate back-end data centers for processing.
Optimal Power Flow With UPFC Using Fuzzy- PSO With Non-Smooth Fuel Cost FunctionIJERA Editor
This paper presents an efficient and reliable evolutionary based approach to solve the Optimal Power Flow problem in electrical power network. The Particle Swarm Optimization method is used to solve optimal power Flow problem in power system by incorporating a powerful and most versatile Flexible Alternating Current Transmission Systems device such as Unified power Flow Controller. It is a new device in FACTS family and has great flexibility that can control Active power, Reactive power and voltage magnitudes simultaneously. In this paper optimal location is find out using Fuzzy approach and control settings of UPFC are determined by PSO. The proposed approach is examined on IEEE-30 bus system with different objective function that reflects fuel cost minimization and fuel cost with valve point effects. The test results show the effectiveness of robustness of the proposed approachcompared with the existing results in the literature.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMaeijjournal
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its
exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is
equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the
optimization of the generative units to minimize the full action cost regarding problem constraints. In this
article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in
a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power
system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
The document describes a two-stage method for optimal allocation of capacitors in a radial distribution system. In the first stage, loss sensitivity factors are used to calculate candidate locations for capacitors. In the second stage, a harmony search algorithm is used to minimize total costs, including capacitor costs and power loss costs, by determining the optimal capacitor sizes and numbers placed at the candidate locations. The method is tested on 33-bus and 69-bus test systems and results in reduced power losses and costs compared to the base case without capacitors.
Electricity Generation Scheduling an Improved for Firefly Optimization AlgorithmIRJET Journal
This document describes using an improved firefly optimization algorithm to schedule electricity generation from thermal and wind power plants. The algorithm aims to minimize total generation costs while meeting load demand and reserve requirements, taking into account wind power availability constraints and both generation unit and system constraints. It formulates the objective function and constraints for the generation scheduling problem and applies the firefly algorithm to a test system with 30 conventional units and 4 wind farms, comparing results to a particle swarm optimization method. The firefly algorithm performance is found to provide better schedules with lower total costs compared to particle swarm optimization.
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...IJECEIAES
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Economical and Reliable Expansion Alternative of Composite Power System under...IJECEIAES
The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions.
Multi objective economic load dispatch using hybrid fuzzy, bacterialIAEME Publication
The document summarizes a research paper that proposes a new approach for solving the economic load dispatch problem using a hybrid fuzzy, bacterial foraging-Nelder–Mead algorithm. The economic load dispatch problem minimizes generation costs while satisfying load demand under system constraints. The proposed approach considers generation costs, spinning reserve costs, and emission costs simultaneously. It also accounts for valve-point effects, prohibited operating zones, and other practical constraints. A hybrid bacterial foraging and Nelder–Mead algorithm combined with fuzzy logic is used to solve the optimization problem. Simulation results show the advantages of the proposed method in reducing total system costs.
IRJET - Optimal Parameters of Electro-Chemical MachiningIRJET Journal
This document discusses optimizing the parameters of electrochemical machining (ECM) using genetic algorithms. The optimization problem aims to maximize the material removal rate by selecting optimal values for the design variables of electrolyte concentration, flow rate, applied voltage, and feed rate. Genetic algorithms from MATLAB are applied to solve the optimization problem and determine the optimal parameter values for ECM. The results found the maximum material removal rate was achieved with electrolyte concentration of 18.3, flow rate of 5, applied voltage of 15 volts, and feed rate of 0.9.
Grid Connected Electricity Storage Systems (1/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
This document provides a literature survey of recent methods for solving the optimal power flow (OPF) problem. It begins with an introduction to OPF, describing it as a nonlinear optimization problem that aims to optimize the operation of power systems while meeting constraints. It then categorizes OPF solution methods as conventional (e.g. Newton, gradient) or intelligent (e.g. artificial neural networks, genetic algorithms) and provides examples of each. The document surveys specific OPF formulations and solution techniques in detail. It concludes by discussing ongoing challenges for OPF methods related to power system modeling and operations in deregulated electricity markets.
IRJET- Optimal Placement and Size of DG and DER for Minimizing Power Loss and...IRJET Journal
This document presents a study on using optimization techniques to determine the optimal placement and sizing of distributed generation (DG) and distributed energy resources (DER) in a 69-bus distribution system. The study uses two optimization algorithms - Grasshopper Optimization Algorithm (GOA) and Moth Flame Optimization (MFO) - to minimize power losses and annual energy losses at different load levels. The results show that MFO performs better, identifying bus locations 61, 11, and 18 as optimal for DG placement, reducing losses more than GOA. For DER placement using MFO, losses are minimized by placing DG at buses 69, 61, 22 and capacitors at buses 61, 49, 12. Overall, the
IRJET- A Research on Vibration Analysis & Optimization of Housing for ECU in ...IRJET Journal
This document discusses a research project that aims to analyze and optimize the housing for an electronic control unit (ECU) in an automobile using finite element analysis (FEA) and an FFT analyzer. The researchers first design an ECU housing model using CAD software. They then perform modal and harmonic analysis using FEA to investigate the housing's mode shapes and response at different frequencies. Experimental modal analysis is also conducted using an accelerometer, impact hammer, and FFT analyzer. The FEA results are compared to the experimental results. The objective is to minimize vertical vibrations in the ECU housing by adding stiffening ribs and optimizing the design to withstand vibrations from the engine.
1) The document discusses speed control of a universal motor using two controllers - an output rate controller and an output reset controller. Ant colony optimization is used to tune the parameters of the controllers.
2) Mathematical models of the universal motor are developed. Simulation results show that the proposed ant colony optimization technique tunes the controllers' parameters optimally, improving their performance for speed control of the motor under varying load conditions.
3) The tuning results in zero overshoot and undershoot, slight rise and settling times, and a fast response for the motor speed when subjected to different load disturbances.
Analysis and implementation of local modular supervisory control forIAEME Publication
1. The document describes the analysis and implementation of a local modular supervisory control system for a manufacturing cell using programmable logic controllers (PLCs).
2. A local modular approach is used where modular supervisors are obtained for each behavioral specification by considering only locally affected subsystems, avoiding state space explosion.
3. The modular supervisors are implemented on the PLC in a three-level structure that executes the supervisors concurrently and interfaces them to the physical system.
IRJET- Performance Improvement of the Distribution Systems using Meta-Heu...IRJET Journal
This document summarizes a research paper that proposes using a Whale Optimization Algorithm (WOA) to optimize the control of photovoltaic (PV) systems connected to distribution networks in Egypt. The high penetration of PV systems can cause voltage issues in distribution grids. The paper aims to enhance distribution network performance by optimally designing a proportional-integral controller for PV inverters using WOA. WOA is inspired by the hunting behavior of humpback whales and is applied to minimize voltage deviations across the network. The effectiveness of the WOA-designed controller is evaluated through simulations and compared to controllers designed using genetic algorithms.
Cost and performance optimization of induction motor using geneticIAEME Publication
This document describes research on optimizing the design of induction motors using genetic algorithms. It presents three optimal motor designs that were compared to a classically designed motor with the same ratings. The genetic algorithm optimization considered three objective functions: efficiency, torque, and cost. Key design variables like stator and rotor dimensions were selected as variables to be optimized. Performance constraints like efficiency, power factor, and current densities were also defined. The optimal designs found by the genetic algorithm were intended to improve performance while reducing costs compared to the classical design approach.
The document summarizes research on optimizing the design parameters of an asynchronous machine using genetic algorithms. It presents the objective as minimizing losses to improve efficiency. A genetic algorithm approach is used to optimize five induction motor equivalent circuit parameters as design variables while satisfying constraints like nominal slip and temperature rise. The algorithm evaluates losses as the objective function and converges to an optimal solution with improved efficiency and performance characteristics like higher starting torque compared to the initial design.
Monitoring and analysis of reliaibility of electrical distribution systemIAEME Publication
This document summarizes a study on monitoring and analyzing the reliability of electrical distribution systems using MATLAB. The study develops a reliability analysis program in MATLAB to assess factors that affect distribution reliability. Field visits were conducted to distribution substations in India to collect data. The objectives of the study are to provide reliability data to utility management, allow performance comparisons, determine how design and maintenance affect reliability, and aid maintenance scheduling. The significance of the study is that distribution reliability is important for utilities facing market pressures to satisfy customers while minimizing costs. The MATLAB model allows a new method for evaluating reliability and identifying cost-effective preventative maintenance strategies.
Convergence Parameter Analysis for Different Metaheuristic Methods Control Co...IJPEDS-IAES
This paper is an extension of our previous work, which discussed the
difficulty in implementing different methods of resistance emulation
techniques on the hardware due to its control constant estimation delay. In
order to get rid of the delay this paper attempts to include the meta-heuristic
methods for the control constants of the controller. To achieve the minimum
Total Harmonic Disturbance (THD) in the AC side of the converter modern
meta-heuristic methods are compared with the traditional methods. The
convergence parameters, which are primary for the earlier estimation of the
control constants, are compared with the measured parameters, tabulated and
tradeoff inference is done among the methods. This kind of implementation
does not need the mathematical model of the system under study for finding
the control constants. The parameters considered for estimation are
population size, maximum number of epochs, and global best solution of the
control constants, best THD value and execution time. MatlabTM /Simulink
based simulation is optimized with the M-file based optimization techniques
like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo
Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm
and Bat Algorithm.
IRJET- Comprehensive Analysis on Optimal Allocation and Sizing of Distributed...IRJET Journal
This document summarizes a research paper that investigates the optimal allocation and sizing of distributed generation (DG) units in a distribution system using Particle Swarm Optimization (PSO). The objective is to minimize voltage deviation and total power loss. A 33-bus distribution network is used as a case study. The results show that allocating 3 DG units at buses 18, 14, and 17 with sizes of 1.7154 MW, 0.1908 MW, and 1.6159 MW respectively reduces voltage deviation at all buses and total power loss by 89.83%. The PSO technique effectively finds the optimal DG locations and sizes to improve the voltage profile and minimize losses in the distribution network.
IRJET- Swarm Optimization Technique for Economic Load DispatchIRJET Journal
This document discusses using particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problem in power systems. The ELD problem aims to minimize the total generation cost while satisfying constraints. PSO is applied to determine the optimal power outputs of generators. The key steps are: (1) Initialize a swarm of particles randomly within generator limits, (2) Evaluate fitness of each particle using a cost function, (3) Update particles' velocities and positions based on individual and global best positions, (4) Repeat steps 2-3 until convergence criteria is met. The method is tested on 3-unit and 6-unit systems and shown to find lower cost solutions than other algorithms like cuckoo search. PSO
Tap changer optimisation using embedded differential evolutionary programming...journalBEEI
Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and system loss increment. A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). Consequently, EDEP was for solving optimizations problem in power system through the tap changer optimizations scheme. Results obtained from this study are significantly superior compared to the traditional EP with implementation on the IEEE 30-bus reliability test system (RTS) for the loss minimization scheme.
This document discusses a pervasive computing approach for energy management in mobile devices. It proposes outsourcing computation from a mobile device to a remote server with an unlimited power source. The approach transforms a high-level source code into a client/server application, with the client on the mobile device and server on a surrogate machine. It uses methodologies from real-time systems to determine loop iterations and cost of outsourcing loops versus local computation. This allows generating code to intelligently decide whether to outsource or execute locally to optimize energy usage.
Generator Maintenance Scheduling Of Power System Using Hybrid TechniqueIRJET Journal
This document discusses generator maintenance scheduling for power systems using hybrid techniques. It aims to minimize total operation costs while satisfying constraints. The scheduling problem is complex with many generating units and constraints to consider. Traditional methods cannot solve large, real-world problems due to computational limitations. The document proposes using metaheuristic techniques like genetic algorithms, particle swarm optimization, and simulated annealing to find near-optimal schedules efficiently for large power systems over long time horizons. These evolutionary algorithms are better suited than traditional methods at handling complex, constrained optimization problems.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
IRJET- Optimum Design of PSO based Tuning using PID Controller for an Automat...IRJET Journal
This document discusses using particle swarm optimization (PSO) to tune the parameters of a PID controller for an automatic voltage regulator (AVR) system. The goal is to improve the system's transient performance by minimizing overshoot and steady state error. PSO is applied to optimize the proportional, integral, and derivative parameters of the PID controller. Simulation results show the PSO-tuned PID controller provides significantly better control of the AVR system compared to a traditionally tuned PID controller. The tuned controller gives faster response, lower overshoot, and improved stability when subjected to disturbances and parameter variations.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMAEIJjournal2
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its
exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is
equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the
optimization of the generative units to minimize the full action cost regarding problem constraints. In this
article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in
a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power
system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
Advanced Energy: An International Journal (AEIJ)AEIJjournal2
A modified ant colony optimization algorithm is proposed to solve the unit commitment problem in power systems. The unit commitment problem aims to minimize generation costs while meeting demand and operational constraints of generation units. The modified ant colony optimization algorithm uses multiple pheromone matrices, one for each hour, to represent the problem. It also uses discrete power levels for units and considers their minimum up and down times. The algorithm evaluates solutions based on generation costs while ensuring demand is met and system reserves are maintained at each step. The algorithm is tested on 4 and 10 unit systems and shows improvements over previous ant colony optimization methods for unit commitment.
A MODIFIED ANT COLONY ALGORITHM FOR SOLVING THE UNIT COMMITMENT PROBLEMAEIJjournal2
Solving the unit commitment (UC) problem is one of the most complicated issues in power systems that its exact solving can be calculated by perfect counting of entire possible compounds of generative units. UC is equated as a nonlinear optimization with huge size. Purpose of solving this problem is to programming the optimization of the generative units to minimize the full action cost regarding problem constraints. In this article, a modified version of ant colony optimization (MACO) is introduced for solving the UC problem in a power system. ACO algorithm is a powerful optimization method which has the capability of fleeing from
local minimums by performing flexible memory system. The efficiency of proposed method in two power system containing 4 and 10 generative units is indicated. Comparison of obtained results from the proposed
method with results of the past well-known methods is a proof for suitability of performing the introduced
algorithm in economic input and output of generative units.
This document summarizes a research paper that proposes using a Real-Coded Genetic Algorithm to design Unified Power Flow Controller (UPFC) damping controllers. The goal is to damp low frequency oscillations in power systems. The paper models a single-machine infinite-bus power system installed with a UPFC. It linearizes the system equations and formulates the controller design as an optimization problem to minimize oscillations. Simulation results comparing the proposed RCGA approach to conventional tuning are presented to demonstrate its effectiveness and robustness in damping power system oscillations.
International Journal of Engineering (IJE) Volume (3) Issue (1)CSCJournals
This document discusses the implementation of artificial intelligence techniques for steady state security assessment in deregulated power system markets. It proposes using neural networks, decision trees, and adaptive neuro-fuzzy inference systems to analyze power transactions between generators and customers in deregulated systems. Data from load flow analysis is used to train and test the AI models. The techniques are tested on various standard power system test cases. The results show that neural networks provide more accurate and faster assessments compared to decision trees and neuro-fuzzy systems, but the latter two may be easier to implement for practical applications. The new methods could help improve security in planning and operating deregulated power system markets.
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.