This document discusses various hybrid optimization techniques that have been proposed to solve economic load dispatch (ELD) problems. ELD problems aim to minimize the total fuel cost of generating units by considering constraints. The summary is:
1. Several hybrid optimization approaches combining techniques like particle swarm optimization, genetic algorithms, fuzzy logic, and artificial bee colony algorithms have been developed to solve ELD problems.
2. These hybrid methods are analyzed and shown to outperform traditional optimization techniques in terms of solution quality and computational time.
3. Case studies on standard test systems demonstrate that hybrid particle swarm optimization-direct search, chaotic particle swarm optimization-implicit filtering, and artificial bee colony-particle swarm optimization methods provide high quality solutions for the
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
This document presents a study that uses the Grey Wolf Optimizer (GWO) method to estimate the input-output parameters of the fuel cost curve for thermal power plants.
The fuel cost curve represents the relationship between a plant's fuel costs and power output, and needs to be periodically re-estimated due to temperature and aging effects. Accurately estimating the curve's parameters is important for economic dispatch calculations.
The study formulates parameter estimation as an optimization problem to minimize errors between actual and estimated fuel costs. It applies GWO to find the parameters for different fuel cost curve models using test data from three power plants. Simulation results show GWO provides better parameter estimates than other estimation methods.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
Relevance of Particle Swarm Optimization Technique for the Solution of Econom...IRJET Journal
This document presents the use of particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problem in power systems. The ELD problem aims to schedule power plant generation outputs to meet load demand at minimum operating cost while satisfying constraints. PSO is applied by initializing generator outputs as "particles" that fly through search space to find minimum cost. Results on 5-unit and 6-unit test systems show PSO able to determine optimal outputs to meet time-varying loads at lowest cost within constraints.
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- Solving Economic Load Dispatch Problem with Valve Point EffectIRJET Journal
This document presents a study on using Jaya Optimization (JO) to solve the economic load dispatch (ELD) problem considering valve point loading effects. ELD aims to minimize fuel costs while meeting demand, and involves constraints. JO is applied to a 13-unit system, minimizing costs while satisfying constraints. Results show JO finds the optimal solution of $17937.67/hr, outperforming other algorithms like SDE, IGA_MU, and HQPSO. JO is thus an effective technique for solving the non-linear, non-convex ELD problem with valve point effects.
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
GWO-based estimation of input-output parameters of thermal power plantsTELKOMNIKA JOURNAL
This document presents a study that uses the Grey Wolf Optimizer (GWO) method to estimate the input-output parameters of the fuel cost curve for thermal power plants.
The fuel cost curve represents the relationship between a plant's fuel costs and power output, and needs to be periodically re-estimated due to temperature and aging effects. Accurately estimating the curve's parameters is important for economic dispatch calculations.
The study formulates parameter estimation as an optimization problem to minimize errors between actual and estimated fuel costs. It applies GWO to find the parameters for different fuel cost curve models using test data from three power plants. Simulation results show GWO provides better parameter estimates than other estimation methods.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
Relevance of Particle Swarm Optimization Technique for the Solution of Econom...IRJET Journal
This document presents the use of particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problem in power systems. The ELD problem aims to schedule power plant generation outputs to meet load demand at minimum operating cost while satisfying constraints. PSO is applied by initializing generator outputs as "particles" that fly through search space to find minimum cost. Results on 5-unit and 6-unit test systems show PSO able to determine optimal outputs to meet time-varying loads at lowest cost within constraints.
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- Solving Economic Load Dispatch Problem with Valve Point EffectIRJET Journal
This document presents a study on using Jaya Optimization (JO) to solve the economic load dispatch (ELD) problem considering valve point loading effects. ELD aims to minimize fuel costs while meeting demand, and involves constraints. JO is applied to a 13-unit system, minimizing costs while satisfying constraints. Results show JO finds the optimal solution of $17937.67/hr, outperforming other algorithms like SDE, IGA_MU, and HQPSO. JO is thus an effective technique for solving the non-linear, non-convex ELD problem with valve point effects.
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
Economic/Emission Load Dispatch Using Artificial Bee Colony AlgorithmIDES Editor
This paper presents an application of the
artificial bee colony (ABC) algorithm to multi-objective
optimization problems in power system. A new multiobjective
artificial bee colony (MOABC) algorithm to
solve the economic/ emission dispatch (EED) problem is
proposed in this paper. Non-dominated sorting is
employed to obtain a Pareto optimal set. Moreover, fuzzy
decision theory is employed to extract the best
compromise solution. A numerical result for IEEE 30-bus
test system is presented to demonstrate the capability of
the proposed approach to generate well-distributed
Pareto-optimal solutions of EED problem in one single
run. In addition, the EED problem is also solved using the
weighted sum method using ABC. Results obtained with
the proposed approach are compared with other
techniques available in the literature. Results obtained
show that the proposed MOABC has a great potential in
handling multi-objective optimization problem.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
IRJET - A Speculative Approximate Adder for Error Recovery UnitIRJET Journal
This document presents a speculative approximate adder for error recovery. The adder is partitioned into non-overlapping blocks whose carries are predicted based on input signals of the current and next blocks. This reduces the critical path delay on average to one block. An error recovery unit is also proposed to further reduce output error rates. Simulation results show the proposed adder achieves lower error rates and error metrics compared to state-of-the-art approximate adders, with only a small increase in delay and area due to the error recovery unit.
IRJET- A Review of Approximate Adders for Energy-Efficient Digital Signal Pro...IRJET Journal
The document reviews recent progress in approximate adders for energy-efficient digital signal processing. It summarizes various types of approximate adders that have been proposed, including speculative adders, segmented adders, carry select adders, and adders using approximate full adders. The document provides details on the design and operation of several specific approximate adder circuits. It also compares the delay and area complexity of different approximate adder designs.
The document describes an experiment to validate a novel controller called a Piecewise Predictive Estimator (PPE) that aims to increase the frequency response of an aerospace electro-mechanical actuator (EMA) by reducing phase lag. The experiment showed that combining a PID controller with PPE increased the EMA's bandwidth from 22Hz to 25Hz without increasing noise levels, validating that PPE successfully enhances EMA performance by reducing phase lag at higher frequencies. The document also provides background on EMA modeling and design challenges, and discusses PID, LQR, and PPE controller design approaches.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
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.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
This document presents a design for a simple accuracy reconfigurable adder (SARA) to improve the accuracy-power-delay efficiency of approximate adders. SARA is proposed as an alternative to existing accuracy configurable adders that require large areas due to redundancy and error correction circuitry. SARA uses a simple carry prediction approach without redundancy. It is evaluated as part of a 16-bit adder and shown to reduce delay compared to a ripple carry adder. SARA is also applied in an 8x8 Wallace multiplier, demonstrating reduced delay compared to using a ripple carry adder. The proposed SARA design achieves improvements in area, power, and delay efficiency for approximate arithmetic circuits.
The document summarizes a study on reducing CO2 emissions from thermal power plants through load dispatch scheduling. It presents equations to calculate CO2 emissions from power plants and describes using evolutionary algorithms to optimize load scheduling across three power plants. The results show evolutionary techniques achieved the lowest overall CO2 emissions of 8,426 tons compared to other methods, while maintaining the same total power output. The conclusion is that properly selecting which plants generate power through load scheduling can reduce CO2 emissions without additional equipment.
Multi-objective Optimization Scheme for PID-Controlled DC MotorIAES-IJPEDS
DC Motor is the most basic electro-mechanical equipment and well-known for its merit and simplicity. The performance of DC motor is assessed based on several qualities that are most-likely contradictory each other, i.e. settling time and overshoot percentage. Most of controller’s optimization problems are multi-objective in nature since they normally have several conflicting objectives that must be met simultaneously. In this study, the grey relational analysis (GRA) was combined with Taguchi method to search the optimum PID parameter for multi-objective problem. First, a L9 (33) orthogonal array was used to plan out the processing parameters that would affect the DC motor’s speed. Then GRA was applied to overcome the drawback of single quality characteristics in the Taguchi method, and then the optimized PID parameter combination was obtained for multiple quality characteristics from the response table and the response graph from GRA. Signal-to-noise ratio (S/N ratio) calculation and analysis of variance (ANOVA) would be performed to find out the significant factors. Lastly, the reliability and reproducibility of the experiment was verified by confirming a confidence interval (CI) of 95%.
IRJET- Parallelization of Definite IntegrationIRJET Journal
1. The document discusses parallelizing numerical integration methods to improve computational efficiency. It describes Simpson's rule and Gaussian quadrature algorithms for definite integration and presents their parallelized versions.
2. The algorithms divide the integration interval into subintervals that can be computed independently, allowing parallel computation to evaluate the integral faster than serial computation for complex functions.
3. Testing showed Simpson's rule was faster than Gaussian quadrature and parallel computation was faster than serial for problems with many subintervals, demonstrating the benefit of parallelization for compute-intensive definite integration tasks.
This document provides details of a project to design an automated pick and place system for components of a CNC lathe machine. It includes sections on the objectives, literature review, methodology, modeling using Solidworks, fabrication, static and dynamic FE analysis, optimization, and conclusions. The objectives are to reduce lead time, optimize design for cost and productivity, and evaluate the new design using simulation. The literature review covers various papers on robotics, pick and place systems, dynamic analysis, and multi-robot coordination. The methodology describes the components to be used, cycle time calculations, and assembly. FE analysis and optimization are performed to validate the design meets requirements. The conclusions are that automation increased productivity and reduced cycle times.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
IRJET- FPGA Implementation of Low Power Configurable Adder for Approximate Co...IRJET Journal
The document proposes a configurable and low-power approximate adder for approximate computing applications. Existing adders have drawbacks like increased area overhead and power wastage to achieve accuracy configurability. The proposed adder is based on a carry look-ahead adder structure with carry propagation masked at runtime to produce approximate sums. Experimental results on a 16-bit implementation show the proposed adder achieves significant power savings and speedup compared to a conventional carry look-ahead adder, while maintaining a small area overhead. It also outperforms previously studied configurable adders in optimizing power and delay without sacrificing accuracy.
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
An Experimental Study of Ion Motion Optimization for Constraint Economic Load...Mohit Dhiman
This article implements the Ion-Motion Optimization (IMO) optimizer to solve non-convex economic load dispatch (EcLD) problem in power system. The concept of Ion motion optimization is modeled from the attraction and repulsion forces among anions and cations in the real world. The mathematical model of IMO is quiet simple and very easy to implement. The liquid phase of IMO performs exploration and crystal phase simulates the exploitation. To handle the power balance equality constraint, exterior penalty method is used. Finally, EcLD problem having 13-generators is solved using ion motion optimization.
Optimum designing of a transformer considering lay out constraints by penalty...INFOGAIN PUBLICATION
Optimum designing of power electrical equipment and devices play a leading role in attaining optimal performance and price of equipments in electric power industry. Optimum transformer design considering multiple constraints is acquired using optimal determination of geometric parameters of transformer with respect to its magnetic and electric properties. As it is well known, every optimization problem requires an objective function to be minimized. In this paper optimum transformer design problem comprises minimization of transformers mean core mass and its windings by satisfying multiple constraints according to transformers ratings and international standards using a penalty-based method. Hybrid big bang-big crunch algorithm is applied to solve the optimization problem and results are compared to other methods. Proposed method has provided a reliable optimization solution and has guaranteed access to a global optimum. Simulation result indicates that using the proposed algorithm, transformer parameters such as core mass, efficiency and dimensions are remarkably improved. Moreover simulation time using this algorithm is quit less in comparison to other approaches.
IRJET- A New Approach to Economic Load Dispatch by using Improved QEMA ba...IRJET Journal
This document proposes an improved Quantum behaved electro-magnetism algorithm particle swarm optimization (QEMAPSO) approach to solve the economic load dispatch (ELD) problem. The objective is to minimize the total generation cost while considering constraints like generator limits, transmission losses, and valve point effects. It formulates the ELD problem and describes the QEMA-PSO algorithm which uses QEMA to determine an initial solution that is then optimized using PSO. Results on a 6-generator IEEE 30-bus test system show that the proposed QEMA-PSO approach improves upon other methods like genetic algorithm and dance bee colony optimization in minimizing costs and emissions.
A new technique near minimum material zone, to reduce the weight of the com...eSAT Journals
Abstract Customers buy a product when the quality of the product is high. So manufacturers produce their components to high quality. The product such as aircraft, automobile, motorcycle, etc. not only need to be produced at high quality but also at reduced weight. This is because these products performance is depend on weight of the product. A component could consist of several components. So all relevant component weights are reduced, then the overall weight of the component could be reduced. This paper introduces as new technique called "near minimum material zone" where not only the weight of the component could be reduced but also helps to increase the quality. To demonstrate this technique, two sets of experiments with 20 samples were conducted using Deckel Maho CTX310 ECO VI CNC machine. The first experiment was conducted under normal machining condition. The second experiment was conducted under this new technique. Several tools such as process capability analysis (Cp, Cpk), cause and effect diagram, X Hi/Lo and R-charts were used to analyze the case study data. The paper outcome suggests that this new technique not only helped to control the weight of the components but also improved the desired quality by minimizing the dispersion of the component dimensions to obtain higher sigma level. Keywords: Near Minimum Material Zone, Process Capability, Cpk, Cause and Effect diagram, X Hi/Lo chart, R chart, Quality.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
This document summarizes the optimization of electronics system thermal management using finite element analysis and the Nelder-Mead optimization method. A test sample with 3 components was modeled and optimized to minimize average temperature and area of the printed circuit board (PCB). The results showed temperature reductions of up to 4-8% and a 34% reduction in PCB area. Comparative analyses were also performed on samples from other studies, achieving temperature reductions of up to 23% and area reductions of up to 26%. Overall, the optimization approach significantly improved thermal management and performance while reducing PCB size.
This document presents a multi-objective optimization method for economic emission load dispatch (EELD) that considers economy, emissions, and transmission line security as objectives. The problem is formulated to minimize total fuel costs and emissions while maximizing line security for a power system. The multi-objective problem is converted to a single objective using goal attainment and then solved using simulated annealing. Results are presented for a 30-bus and 57-bus IEEE test case system to demonstrate the proposed method.
IRJET- Optimal Placement and Size of DG and DER for Minimizing Power Loss and...IRJET Journal
This document summarizes research on optimizing the placement and sizing of distributed generation (DG) and distributed energy resources (DER) in a 33-bus distribution system to minimize power losses. Two optimization techniques are evaluated: Grasshopper Optimization Algorithm (GOA) and Moth Flame Optimization (MFO). MFO shows better results, identifying bus 13, 24 and 30 as optimal locations for DG, reducing losses from 0.2027 MW to 0.0715 MW at normal load. For DER, optimal locations are DG at buses 13, 25, 30 and capacitors at buses 7, 13, 30, further reducing losses to 0.0144 MW. Graphs and tables show MFO placement
IRJET - A Speculative Approximate Adder for Error Recovery UnitIRJET Journal
This document presents a speculative approximate adder for error recovery. The adder is partitioned into non-overlapping blocks whose carries are predicted based on input signals of the current and next blocks. This reduces the critical path delay on average to one block. An error recovery unit is also proposed to further reduce output error rates. Simulation results show the proposed adder achieves lower error rates and error metrics compared to state-of-the-art approximate adders, with only a small increase in delay and area due to the error recovery unit.
IRJET- A Review of Approximate Adders for Energy-Efficient Digital Signal Pro...IRJET Journal
The document reviews recent progress in approximate adders for energy-efficient digital signal processing. It summarizes various types of approximate adders that have been proposed, including speculative adders, segmented adders, carry select adders, and adders using approximate full adders. The document provides details on the design and operation of several specific approximate adder circuits. It also compares the delay and area complexity of different approximate adder designs.
The document describes an experiment to validate a novel controller called a Piecewise Predictive Estimator (PPE) that aims to increase the frequency response of an aerospace electro-mechanical actuator (EMA) by reducing phase lag. The experiment showed that combining a PID controller with PPE increased the EMA's bandwidth from 22Hz to 25Hz without increasing noise levels, validating that PPE successfully enhances EMA performance by reducing phase lag at higher frequencies. The document also provides background on EMA modeling and design challenges, and discusses PID, LQR, and PPE controller design approaches.
Dynamic economic load dispatch a review of solution methodologies48jiten2k13
This document discusses various solution techniques for the economic load dispatch (ELD) problem in power systems. It first defines ELD and explains why it is important for minimizing generation costs while meeting load demands. The document then outlines different ELD formulation and solution methods like invasive weed optimization, particle swarm optimization, genetic algorithms, and simulated annealing. It provides flowcharts to illustrate the processes. The document also discusses the limitations of classical optimization methods for dynamic ELD problems and concludes with references used.
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Publishing House
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.
Optimization of Economic Load Dispatch with Unit Commitment on Multi MachineIJAPEJOURNAL
Economic load dispatch (ELD) and Unit Commitment (UC) are significant research applications in power systems that optimize the total production cost of the predicted load demand. The UC problem determines a turn-on and turn-off schedule for a given combination of generating units, thus satisfying a set of dynamic operational constraints. ELD optimizes the operation cost for all scheduled generating units with respect to the load demands of customers. The first phase in this project is to economically schedule the distribution of generating units using Gauss seidal and the second phase is to determine optimal load distribution for the scheduled units using dynamic programming method is applied to select and choose the combination of generating units that commit and de-commit during each hour. These precommitted schedules are optimized by dynamic programming method thus producing a global optimum solution with feasible and effective solution quality, minimal cost and time and higher precision. The effectiveness of the proposed techniques is investigated on two test systems consisting of five generating units and the experiments are carried out using MATLAB R2010b software. Experimental results prove that the proposed method is capable of yielding higher quality solution including mathematical simplicity, fast convergence, diversity maintenance, robustness and scalability for the complex ELD-UC problem.
This document presents a design for a simple accuracy reconfigurable adder (SARA) to improve the accuracy-power-delay efficiency of approximate adders. SARA is proposed as an alternative to existing accuracy configurable adders that require large areas due to redundancy and error correction circuitry. SARA uses a simple carry prediction approach without redundancy. It is evaluated as part of a 16-bit adder and shown to reduce delay compared to a ripple carry adder. SARA is also applied in an 8x8 Wallace multiplier, demonstrating reduced delay compared to using a ripple carry adder. The proposed SARA design achieves improvements in area, power, and delay efficiency for approximate arithmetic circuits.
The document summarizes a study on reducing CO2 emissions from thermal power plants through load dispatch scheduling. It presents equations to calculate CO2 emissions from power plants and describes using evolutionary algorithms to optimize load scheduling across three power plants. The results show evolutionary techniques achieved the lowest overall CO2 emissions of 8,426 tons compared to other methods, while maintaining the same total power output. The conclusion is that properly selecting which plants generate power through load scheduling can reduce CO2 emissions without additional equipment.
Multi-objective Optimization Scheme for PID-Controlled DC MotorIAES-IJPEDS
DC Motor is the most basic electro-mechanical equipment and well-known for its merit and simplicity. The performance of DC motor is assessed based on several qualities that are most-likely contradictory each other, i.e. settling time and overshoot percentage. Most of controller’s optimization problems are multi-objective in nature since they normally have several conflicting objectives that must be met simultaneously. In this study, the grey relational analysis (GRA) was combined with Taguchi method to search the optimum PID parameter for multi-objective problem. First, a L9 (33) orthogonal array was used to plan out the processing parameters that would affect the DC motor’s speed. Then GRA was applied to overcome the drawback of single quality characteristics in the Taguchi method, and then the optimized PID parameter combination was obtained for multiple quality characteristics from the response table and the response graph from GRA. Signal-to-noise ratio (S/N ratio) calculation and analysis of variance (ANOVA) would be performed to find out the significant factors. Lastly, the reliability and reproducibility of the experiment was verified by confirming a confidence interval (CI) of 95%.
IRJET- Parallelization of Definite IntegrationIRJET Journal
1. The document discusses parallelizing numerical integration methods to improve computational efficiency. It describes Simpson's rule and Gaussian quadrature algorithms for definite integration and presents their parallelized versions.
2. The algorithms divide the integration interval into subintervals that can be computed independently, allowing parallel computation to evaluate the integral faster than serial computation for complex functions.
3. Testing showed Simpson's rule was faster than Gaussian quadrature and parallel computation was faster than serial for problems with many subintervals, demonstrating the benefit of parallelization for compute-intensive definite integration tasks.
This document provides details of a project to design an automated pick and place system for components of a CNC lathe machine. It includes sections on the objectives, literature review, methodology, modeling using Solidworks, fabrication, static and dynamic FE analysis, optimization, and conclusions. The objectives are to reduce lead time, optimize design for cost and productivity, and evaluate the new design using simulation. The literature review covers various papers on robotics, pick and place systems, dynamic analysis, and multi-robot coordination. The methodology describes the components to be used, cycle time calculations, and assembly. FE analysis and optimization are performed to validate the design meets requirements. The conclusions are that automation increased productivity and reduced cycle times.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
IRJET- FPGA Implementation of Low Power Configurable Adder for Approximate Co...IRJET Journal
The document proposes a configurable and low-power approximate adder for approximate computing applications. Existing adders have drawbacks like increased area overhead and power wastage to achieve accuracy configurability. The proposed adder is based on a carry look-ahead adder structure with carry propagation masked at runtime to produce approximate sums. Experimental results on a 16-bit implementation show the proposed adder achieves significant power savings and speedup compared to a conventional carry look-ahead adder, while maintaining a small area overhead. It also outperforms previously studied configurable adders in optimizing power and delay without sacrificing accuracy.
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
An Experimental Study of Ion Motion Optimization for Constraint Economic Load...Mohit Dhiman
This article implements the Ion-Motion Optimization (IMO) optimizer to solve non-convex economic load dispatch (EcLD) problem in power system. The concept of Ion motion optimization is modeled from the attraction and repulsion forces among anions and cations in the real world. The mathematical model of IMO is quiet simple and very easy to implement. The liquid phase of IMO performs exploration and crystal phase simulates the exploitation. To handle the power balance equality constraint, exterior penalty method is used. Finally, EcLD problem having 13-generators is solved using ion motion optimization.
Optimum designing of a transformer considering lay out constraints by penalty...INFOGAIN PUBLICATION
Optimum designing of power electrical equipment and devices play a leading role in attaining optimal performance and price of equipments in electric power industry. Optimum transformer design considering multiple constraints is acquired using optimal determination of geometric parameters of transformer with respect to its magnetic and electric properties. As it is well known, every optimization problem requires an objective function to be minimized. In this paper optimum transformer design problem comprises minimization of transformers mean core mass and its windings by satisfying multiple constraints according to transformers ratings and international standards using a penalty-based method. Hybrid big bang-big crunch algorithm is applied to solve the optimization problem and results are compared to other methods. Proposed method has provided a reliable optimization solution and has guaranteed access to a global optimum. Simulation result indicates that using the proposed algorithm, transformer parameters such as core mass, efficiency and dimensions are remarkably improved. Moreover simulation time using this algorithm is quit less in comparison to other approaches.
IRJET- A New Approach to Economic Load Dispatch by using Improved QEMA ba...IRJET Journal
This document proposes an improved Quantum behaved electro-magnetism algorithm particle swarm optimization (QEMAPSO) approach to solve the economic load dispatch (ELD) problem. The objective is to minimize the total generation cost while considering constraints like generator limits, transmission losses, and valve point effects. It formulates the ELD problem and describes the QEMA-PSO algorithm which uses QEMA to determine an initial solution that is then optimized using PSO. Results on a 6-generator IEEE 30-bus test system show that the proposed QEMA-PSO approach improves upon other methods like genetic algorithm and dance bee colony optimization in minimizing costs and emissions.
A new technique near minimum material zone, to reduce the weight of the com...eSAT Journals
Abstract Customers buy a product when the quality of the product is high. So manufacturers produce their components to high quality. The product such as aircraft, automobile, motorcycle, etc. not only need to be produced at high quality but also at reduced weight. This is because these products performance is depend on weight of the product. A component could consist of several components. So all relevant component weights are reduced, then the overall weight of the component could be reduced. This paper introduces as new technique called "near minimum material zone" where not only the weight of the component could be reduced but also helps to increase the quality. To demonstrate this technique, two sets of experiments with 20 samples were conducted using Deckel Maho CTX310 ECO VI CNC machine. The first experiment was conducted under normal machining condition. The second experiment was conducted under this new technique. Several tools such as process capability analysis (Cp, Cpk), cause and effect diagram, X Hi/Lo and R-charts were used to analyze the case study data. The paper outcome suggests that this new technique not only helped to control the weight of the components but also improved the desired quality by minimizing the dispersion of the component dimensions to obtain higher sigma level. Keywords: Near Minimum Material Zone, Process Capability, Cpk, Cause and Effect diagram, X Hi/Lo chart, R chart, Quality.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
This document summarizes the optimization of electronics system thermal management using finite element analysis and the Nelder-Mead optimization method. A test sample with 3 components was modeled and optimized to minimize average temperature and area of the printed circuit board (PCB). The results showed temperature reductions of up to 4-8% and a 34% reduction in PCB area. Comparative analyses were also performed on samples from other studies, achieving temperature reductions of up to 23% and area reductions of up to 26%. Overall, the optimization approach significantly improved thermal management and performance while reducing PCB size.
This document presents a multi-objective optimization method for economic emission load dispatch (EELD) that considers economy, emissions, and transmission line security as objectives. The problem is formulated to minimize total fuel costs and emissions while maximizing line security for a power system. The multi-objective problem is converted to a single objective using goal attainment and then solved using simulated annealing. Results are presented for a 30-bus and 57-bus IEEE test case system to demonstrate the proposed method.
IRJET- Optimal Placement and Size of DG and DER for Minimizing Power Loss and...IRJET Journal
This document summarizes research on optimizing the placement and sizing of distributed generation (DG) and distributed energy resources (DER) in a 33-bus distribution system to minimize power losses. Two optimization techniques are evaluated: Grasshopper Optimization Algorithm (GOA) and Moth Flame Optimization (MFO). MFO shows better results, identifying bus 13, 24 and 30 as optimal locations for DG, reducing losses from 0.2027 MW to 0.0715 MW at normal load. For DER, optimal locations are DG at buses 13, 25, 30 and capacitors at buses 7, 13, 30, further reducing losses to 0.0144 MW. Graphs and tables show MFO placement
COMPARITIVE STUDY OF PARTICLE SWARM OPTIMISATION & GREY WOLF OPTIMIZATION IN ...IRJET Journal
This document compares the performance of particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms for solving the economic load dispatch problem in power systems. The economic load dispatch problem involves distributing load between generation units in a way that minimizes production costs while meeting system constraints. PSO and GWO are implemented on standard 14-bus and 30-bus test power systems. Results show that both algorithms find solutions that minimize fuel costs and emissions while satisfying operational constraints like bus voltages and transmission losses. GWO provides slightly better performance than PSO in terms of lower costs and emissions. Overall, the study demonstrates that metaheuristic optimization techniques like PSO and GWO can effectively solve the non-convex economic load dispatch problem.
ECONOMIC LOAD DISPATCH USING PARTICLE SWARM OPTIMIZATIONMln Phaneendra
In this ppt particle swarm optimization (PSO) is applied to allot the active power among the generating stations satisfying the system constraints and minimizing the cost of power generated.The viability of the method is analyzed for its accuracy and rate of convergence. The economic load dispatch problem is solved for three and six unit system using PSO and conventional method for both cases of neglecting and including transmission losses. The results of PSO method were compared with conventional method and were found to be superior.
IRJET- Comparison of GA and PSO Optimization Techniques to Optimal Planning o...IRJET Journal
This document presents a comparison of genetic algorithm (GA) and particle swarm optimization (PSO) techniques for optimally placing electric vehicle charging stations in a local distribution system. It describes using GA and PSO in MATLAB simulations to determine charging station locations that minimize real and reactive power losses. The results found that PSO requires fewer iterations and less time to achieve optimal solutions compared to GA, though GA may find solutions with slightly lower losses. Overall, both techniques provide effective methods for optimizing charging station placement to support electric vehicles.
Hybrid method for achieving Pareto front on economic emission dispatch IJECEIAES
In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multiobjective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.
IRJET- Fuel Cost Reduction for Thermal Power Generator by using G.A, PSO, QPS...IRJET Journal
This document discusses using optimization techniques like genetic algorithm (GA), particle swarm optimization (PSO), and quantum behaved particle swarm optimization (QPSO) to solve the economic load dispatch (ELD) problem for thermal power generators. The objective is to minimize fuel costs while meeting demand, subject to generator constraints. QPSO is shown to find lower cost solutions than GA and PSO for both 3-generator and 6-generator test systems, reducing costs by up to $6/hour. QPSO works by having particles search for the optimal solution by following the particle with the best fitness value, converging faster than PSO. Tables show solutions found for different demand levels using the three algorithms.
Economic Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
The document describes the economic environmental dispatch (EED) problem, which aims to minimize both the fuel cost and emissions of fossil fuel power plants simultaneously while satisfying operational constraints. The EED problem is formulated as a multi-objective optimization problem with conflicting cost and emission objectives and equality and inequality constraints. Multi-objective differential evolution is proposed to solve the EED problem and find the Pareto optimal solutions. Test results show the proposed approach performs comparably or better than other multi-objective evolutionary algorithms for the EED problem.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
Economic dispatch by optimization techniquesIJECEIAES
The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system.
This document summarizes the application of computational intelligence techniques like genetic algorithms and particle swarm optimization for solving economic load dispatch problems. It first applies a real-coded genetic algorithm to minimize generation costs for a 6-generator test system with continuous fuel cost equations, showing superiority over quadratic programming. It then uses particle swarm optimization to minimize costs for a 10-generator system with each generator having discontinuous fuel options, showing better results than other published methods. The document provides background on economic load dispatch problems and optimization techniques like quadratic programming, genetic algorithms, and particle swarm optimization.
Economic Load Dispatch Optimization of Six Interconnected Generating Units Us...IOSR Journals
This document describes using particle swarm optimization (PSO) to solve the economic load dispatch (ELD) problem of optimizing the operation of six interconnected generating units. ELD aims to minimize total generation costs while satisfying constraints. PSO is applied to find optimal unit outputs that minimize cost, accounting for transmission losses. The proposed PSO approach is compared to genetic algorithms and conventional methods on a test system, showing PSO provides better solutions faster. Key steps of the PSO algorithm for ELD are initializing particles, evaluating fitness at each iteration, and updating personal and global best positions to iteratively improve solutions.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document presents an efficient approach for solving the dynamic economic load dispatch problem with transmission losses using multi-objective particle swarm optimization. The objective is to determine the most economic dispatch of generating units to meet load demand over time at minimum operating cost while satisfying constraints. The proposed MOPSO algorithm evaluates Pareto optimal solutions and preserves diversity better than standard PSO. It is tested on 6-unit and 15-unit systems and shows improved total fuel cost savings compared to the Brent method. The results demonstrate the effectiveness and superiority of the MOPSO approach for dynamic economic dispatch problems.
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
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
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.
A Simple Approach for Optimal Generation Scheduling to Maximize GENCOs Profit...IJAPEJOURNAL
In this paper an attempt has been made to solve the profit based unit commitment problem (PBUC) using pre-prepared power demand (PPD) table with an artificial bee colony (ABC) algorithm. The PPD-ABC algorithm appears to be a robust and reliable optimization algorithm for the solution of PBUC problem. The profit based unit commitment problem is considered as a stochastic optimization problem in which the objective is to maximize their own profit and the decisions are needed to satisfy the standard operating constraints. The PBUC problem is solved by the proposed methodology in two stages. In the first step, the unit commitment scheduling is performed by considering the pre-prepared power demand (PPD) table and then the problem of fuel cost and revenue function is solved using ABC Algorithm. The PPD table suggests the operator to decide the units to be put into generation there by reducing the complexity of the problem. The proposed approach is demonstrated on 10 units 24 hour and 50 units 24 hour test systems and numerical results are tabulated. Simulation result shows that this approach effectively maximizes the GENCO’s profit than those obtained by other optimizing methods.
ECONOMIC LOAD DISPATCH USING GENETIC ALGORITHMIJARIIT
This paper present the application of Genetic Algorithm (GA) to Economic Load Dispatch problem of the power system. Economic Load Dispatch is one of the major optimization problems dealing with the modern power systems.ELD determines the electrical power to be generated by the committed generating units in a power system so that the total generation cost of the system is minimized, while satisfactory the load demand. The objective is to minimize the total generation fuel cost and maintain the power flow within safety limits. The introduced algorithm has been demonstrated for the given test systems considering the transmission line losses.
Similar to Hybrid Optimization Approaches to Economic Load Dispatch Problems – A Comparative Study (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Determination of Equivalent Circuit parameters and performance characteristic...pvpriya2
Includes the testing of induction motor to draw the circle diagram of induction motor with step wise procedure and calculation for the same. Also explains the working and application of Induction generator
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.
Open Channel Flow: fluid flow with a free surfaceIndrajeet sahu
Open Channel Flow: This topic focuses on fluid flow with a free surface, such as in rivers, canals, and drainage ditches. Key concepts include the classification of flow types (steady vs. unsteady, uniform vs. non-uniform), hydraulic radius, flow resistance, Manning's equation, critical flow conditions, and energy and momentum principles. It also covers flow measurement techniques, gradually varied flow analysis, and the design of open channels. Understanding these principles is vital for effective water resource management and engineering applications.