The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
The problem of power system optimization has become a deciding factor in electrical power system engineering practice with emphasis on cost and emission reduction. The economic emission dispatch (EED) problem has been addressed in this paper using a Biogeography-based optimization (BBO). The BBO is inspired by geographical distribution of species within islands. This optimization algorithm works on the basis of two concepts-migration and mutation. In this paper a non-uniform mutation operator has been employed. The proposed technique shows better diversified search process and hence finds solutions more accurately with high convergence rate. The BBO with new mutation operator is tested on ten unit system. The comparison which is based on efficiency, reliability and accuracy shows that proposed mutation operator is competitive to the present one.
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.
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.
Congestion Management in Power System by Optimal Location And Sizing of UPFCIOSR Journals
The document presents a particle swarm optimization (PSO) algorithm to optimally place and size a unified power flow controller (UPFC) to alleviate congestion in a power system. The PSO algorithm is used to determine the optimal generator dispatch as well as the optimal location and size of a single UPFC. Simulations on a 5-bus test system show that the UPFC is effective at reducing congestion levels both before and after compensation by regulating voltage and controlling active and reactive power flows. The proposed approach minimizes total generation costs, voltage violations, and UPFC investment costs.
The document proposes an adaptive real coded biogeography based optimization (ARCBBO) algorithm to solve various power system operation problems. ARCBBO improves on the original biogeography-based optimization (BBO) algorithm by incorporating differential evolution mutation and Gaussian mutation to increase population diversity and exploration. ARCBBO is applied to economic load dispatch, optimal power flow, congestion management, and enhancing loadability limits. It demonstrates reliable convergence on standard test systems compared to BBO, differential evolution, and other algorithms. ARCBBO can effectively solve power system problems with single and multi-objective functions on large-scale systems.
An Application Jeevan – Kushalaiah Method to Find Lagrangian Multiplier in Ec...IOSR Journals
This document presents a Jeevan–Kushalaiah method for calculating the Lagrangian multiplier λ in economic load dispatch problems with and without transmission losses. The method uses a non-iterative approach to determine the optimal generation dispatch and associated λ value. It formulates the economic dispatch problem and derives equations to calculate the generation outputs based on an assumed λ. The total generation is set equal to demand to obtain a final equation for directly calculating λ without iterations. Flowcharts illustrate the algorithm for problems both with and without considering transmission losses in the optimization. The method is shown to satisfy operational constraints of the generators.
The document summarizes techniques for modeling and simulating power plants. It discusses object-oriented modeling of plant components and their interconnections. It also describes modeling components like boilers, turbines, pumps and analyzing thermal stresses and fault events. Parallel ordinary differential equation solvers are introduced to facilitate solving the large system of equations in power plant simulations on parallel processors, improving accuracy and reducing computation time.
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.
The problem of power system optimization has become a deciding factor in electrical power system engineering practice with emphasis on cost and emission reduction. The economic emission dispatch (EED) problem has been addressed in this paper using a Biogeography-based optimization (BBO). The BBO is inspired by geographical distribution of species within islands. This optimization algorithm works on the basis of two concepts-migration and mutation. In this paper a non-uniform mutation operator has been employed. The proposed technique shows better diversified search process and hence finds solutions more accurately with high convergence rate. The BBO with new mutation operator is tested on ten unit system. The comparison which is based on efficiency, reliability and accuracy shows that proposed mutation operator is competitive to the present one.
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.
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.
Congestion Management in Power System by Optimal Location And Sizing of UPFCIOSR Journals
The document presents a particle swarm optimization (PSO) algorithm to optimally place and size a unified power flow controller (UPFC) to alleviate congestion in a power system. The PSO algorithm is used to determine the optimal generator dispatch as well as the optimal location and size of a single UPFC. Simulations on a 5-bus test system show that the UPFC is effective at reducing congestion levels both before and after compensation by regulating voltage and controlling active and reactive power flows. The proposed approach minimizes total generation costs, voltage violations, and UPFC investment costs.
The document proposes an adaptive real coded biogeography based optimization (ARCBBO) algorithm to solve various power system operation problems. ARCBBO improves on the original biogeography-based optimization (BBO) algorithm by incorporating differential evolution mutation and Gaussian mutation to increase population diversity and exploration. ARCBBO is applied to economic load dispatch, optimal power flow, congestion management, and enhancing loadability limits. It demonstrates reliable convergence on standard test systems compared to BBO, differential evolution, and other algorithms. ARCBBO can effectively solve power system problems with single and multi-objective functions on large-scale systems.
An Application Jeevan – Kushalaiah Method to Find Lagrangian Multiplier in Ec...IOSR Journals
This document presents a Jeevan–Kushalaiah method for calculating the Lagrangian multiplier λ in economic load dispatch problems with and without transmission losses. The method uses a non-iterative approach to determine the optimal generation dispatch and associated λ value. It formulates the economic dispatch problem and derives equations to calculate the generation outputs based on an assumed λ. The total generation is set equal to demand to obtain a final equation for directly calculating λ without iterations. Flowcharts illustrate the algorithm for problems both with and without considering transmission losses in the optimization. The method is shown to satisfy operational constraints of the generators.
The document summarizes techniques for modeling and simulating power plants. It discusses object-oriented modeling of plant components and their interconnections. It also describes modeling components like boilers, turbines, pumps and analyzing thermal stresses and fault events. Parallel ordinary differential equation solvers are introduced to facilitate solving the large system of equations in power plant simulations on parallel processors, improving accuracy and reducing computation time.
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.
Sampling-Based Planning Algorithms for Multi-Objective MissionsMd Mahbubur Rahman
multiobjective path planning has Increasing demand in military missions, rescue operations, construction job-sites.
There is Lack of robotic path planning algorithm that compromises multiple
objectives. Commonly no solution that optimizes all the objective functions. Here we modify RRT, RRT* sampling based algorithm.
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.
Economic Dispatch of Generated Power Using Modified Lambda-Iteration MethodIOSR Journals
This document proposes a modified lambda-iteration method for solving economic dispatch problems and minimizing fuel costs. It involves determining the optimal power output of each generator given constraints like load demand and transmission losses. The method is implemented in MATLAB and tested on a 6 generator system. Results found the total power was 1263.0074MW at an incremental cost of 13.2539$/MWh, close to those from a genetic algorithm solution. The proposed method provides a fast, easy to use approach for economic dispatch optimization problems.
A Fuzzy Logic Based Switching Methodology for a Cascaded H-Bridge Multilevel ...Asoka Technologies
This document describes a new switching technique for a cascaded H-bridge multilevel inverter that uses fuzzy logic. The proposed technique eliminates the need for traditional logic gate design by using a fuzzy logic pulse generator and controlled membership functions. The technique was evaluated using a 7-level cascaded multilevel inverter with symmetric and asymmetric operations. Experimental results showed the output voltage and current waveforms at different modulation indexes as well as the total harmonic distortion, validating the proposed fuzzy logic switching technique.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
Power Optimized Multiplexer Based 1 Bit Full Adder Cell Using .18 µm CMOS Tec...iosrjce
In this paper, a multiplexer based 1 bit full adder cell using 10 transistors is reported ( MBFA-10T).
In addition to higher speed , low power and reduced transition activity, this design has no direct power supply
connections, results in reduced consumption of short circuit current. The design was implemented using
Cadence Virtuoso tools in 180-nm CMOS technology. Performance parameters like layout area, power delay
product(PDP), transistor count, average power and delay were compared with the existing logic design styles
like static CMOS logic, pass transistor logic( TFA-16T, 14 T) , transmission gate logic and so on. The intensive
simulation shows improved operation speeds and power savings compare to the conventional design styles.
For 1.8-V supply at 180-nm CMOS technology, the average power consumption (3.9230μW) ,delay (196.8ps)
,the power delay product (PDP) (0.772fJ) and lay out area(175.79 µm2) was found to be extremely low, when
compared with other potential design styles.
How to use R in different professions: R for Car Insurance Product (Speaker: ...Zurich_R_User_Group
This document discusses different statistical modeling approaches for pricing motor third party liability insurance. It begins by introducing the theoretical framework for pricing risk premiums based on expected claim frequency and severity. It then describes moving from a technical tariff to a commercial tariff by adjusting for safety and loading rates. The rest of the document applies generalized linear models (GLM), generalized non-linear models (GNM), and generalized additive models (GAM) to an Australian private motor insurance dataset to model stochastic risk premiums. It compares the results of the different modeling approaches based on metrics like the mean commercial tariff, loss ratio, explained deviance, and number of risk coefficients.
My first presentation as a PhD student in which I outline the background to my research project. This presentation was given as part of the University of Southampton Transportation Research Group seminar programme.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Comparative Analysis on Sodium-Based and Polyethylene-Based Greases as Anti-F...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Producing Bi- Layer Sportswear Using Bamboo And Polypropylene Knitted Fabrictheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
This document summarizes the Replicate and Bundle (RnB) approach for improving the performance and scalability of RAM-based storage systems. RnB involves two key techniques: 1) replicating data objects across multiple servers using a pseudo-random mapping, and 2) bundling requests for replicated objects located on the same server into a single transaction. By choosing replica locations and bundled transactions to minimize the number of servers accessed per request, RnB can significantly reduce the transactions per request compared to alternatives like consistent hashing. RnB allows improved throughput without adding CPUs. It can be implemented in a distributed manner without extra communication overhead compared to consistent hashing approaches. Simulation results show RnB performs well for workloads like those from
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
The document evaluates the preliminary phytochemical and antibacterial activity of Ageratum conyzoides (L) on some clinical bacterial isolates. Phytochemical screening revealed the presence of tannins, alkaloids, steroids, saponins, phenols, flavonoids, triterpenes glycosides and carbohydrates in the ethanolic extract of A. conyzoides. The extract showed antibacterial activity against Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Shigella dysenteriae at concentrations of ≥50mg/ml. The minimum inhibitory concentration and minimum bactericidal concentration of the extract was 120mg/ml for S.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Preliminary Field Measurement of the Uniaxial Compressive Strength of Migmati...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Sampling-Based Planning Algorithms for Multi-Objective MissionsMd Mahbubur Rahman
multiobjective path planning has Increasing demand in military missions, rescue operations, construction job-sites.
There is Lack of robotic path planning algorithm that compromises multiple
objectives. Commonly no solution that optimizes all the objective functions. Here we modify RRT, RRT* sampling based algorithm.
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.
Economic Dispatch of Generated Power Using Modified Lambda-Iteration MethodIOSR Journals
This document proposes a modified lambda-iteration method for solving economic dispatch problems and minimizing fuel costs. It involves determining the optimal power output of each generator given constraints like load demand and transmission losses. The method is implemented in MATLAB and tested on a 6 generator system. Results found the total power was 1263.0074MW at an incremental cost of 13.2539$/MWh, close to those from a genetic algorithm solution. The proposed method provides a fast, easy to use approach for economic dispatch optimization problems.
A Fuzzy Logic Based Switching Methodology for a Cascaded H-Bridge Multilevel ...Asoka Technologies
This document describes a new switching technique for a cascaded H-bridge multilevel inverter that uses fuzzy logic. The proposed technique eliminates the need for traditional logic gate design by using a fuzzy logic pulse generator and controlled membership functions. The technique was evaluated using a 7-level cascaded multilevel inverter with symmetric and asymmetric operations. Experimental results showed the output voltage and current waveforms at different modulation indexes as well as the total harmonic distortion, validating the proposed fuzzy logic switching technique.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
Power Optimized Multiplexer Based 1 Bit Full Adder Cell Using .18 µm CMOS Tec...iosrjce
In this paper, a multiplexer based 1 bit full adder cell using 10 transistors is reported ( MBFA-10T).
In addition to higher speed , low power and reduced transition activity, this design has no direct power supply
connections, results in reduced consumption of short circuit current. The design was implemented using
Cadence Virtuoso tools in 180-nm CMOS technology. Performance parameters like layout area, power delay
product(PDP), transistor count, average power and delay were compared with the existing logic design styles
like static CMOS logic, pass transistor logic( TFA-16T, 14 T) , transmission gate logic and so on. The intensive
simulation shows improved operation speeds and power savings compare to the conventional design styles.
For 1.8-V supply at 180-nm CMOS technology, the average power consumption (3.9230μW) ,delay (196.8ps)
,the power delay product (PDP) (0.772fJ) and lay out area(175.79 µm2) was found to be extremely low, when
compared with other potential design styles.
How to use R in different professions: R for Car Insurance Product (Speaker: ...Zurich_R_User_Group
This document discusses different statistical modeling approaches for pricing motor third party liability insurance. It begins by introducing the theoretical framework for pricing risk premiums based on expected claim frequency and severity. It then describes moving from a technical tariff to a commercial tariff by adjusting for safety and loading rates. The rest of the document applies generalized linear models (GLM), generalized non-linear models (GNM), and generalized additive models (GAM) to an Australian private motor insurance dataset to model stochastic risk premiums. It compares the results of the different modeling approaches based on metrics like the mean commercial tariff, loss ratio, explained deviance, and number of risk coefficients.
My first presentation as a PhD student in which I outline the background to my research project. This presentation was given as part of the University of Southampton Transportation Research Group seminar programme.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Comparative Analysis on Sodium-Based and Polyethylene-Based Greases as Anti-F...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Producing Bi- Layer Sportswear Using Bamboo And Polypropylene Knitted Fabrictheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
This document summarizes the Replicate and Bundle (RnB) approach for improving the performance and scalability of RAM-based storage systems. RnB involves two key techniques: 1) replicating data objects across multiple servers using a pseudo-random mapping, and 2) bundling requests for replicated objects located on the same server into a single transaction. By choosing replica locations and bundled transactions to minimize the number of servers accessed per request, RnB can significantly reduce the transactions per request compared to alternatives like consistent hashing. RnB allows improved throughput without adding CPUs. It can be implemented in a distributed manner without extra communication overhead compared to consistent hashing approaches. Simulation results show RnB performs well for workloads like those from
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
The document evaluates the preliminary phytochemical and antibacterial activity of Ageratum conyzoides (L) on some clinical bacterial isolates. Phytochemical screening revealed the presence of tannins, alkaloids, steroids, saponins, phenols, flavonoids, triterpenes glycosides and carbohydrates in the ethanolic extract of A. conyzoides. The extract showed antibacterial activity against Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Shigella dysenteriae at concentrations of ≥50mg/ml. The minimum inhibitory concentration and minimum bactericidal concentration of the extract was 120mg/ml for S.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Preliminary Field Measurement of the Uniaxial Compressive Strength of Migmati...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Design of a Digital Baseband Processor for UWB Transceiver on RFID Tagtheijes
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International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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Differential Evolution Algorithm for Optimal Power Flow and Economic Load Dispatch with Valve Point Effects
1. The International Journal Of Engineering And Science (IJES)
|| Volume || 3 || Issue || 10 || Pages || 15-25|| 2014 ||
ISSN (e): 2319 – 1813 ISSN (p): 2319 – 1805
www.theijes.com The IJES Page 15
Differential Evolution Algorithm for Optimal Power Flow and Economic Load Dispatch with Valve Point Effects Ngo Cao Cuong HUTECH High Technology Research Instituite, Viet nam --------------------------------------------------------ABSTRACT----------------------------------------------------------- In this paper, we present a Differential Evolution (DE) method and apply it to two problems of optimal power flow (OPF) and the economic load dispatch (ELD) with Valve-Point effects in Power Systems. In the first case, the standard IEEE 30-bus network is tested and its solution is compared to the ones solved by Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO) methods. For the second one, the NPSO is tested on 13-unit, 40-unit system and validated by comparing results with classical evolutionary programming (CEP), improved fast evolutionary programming (IFEP), improved particle swarm optimization (IPSO) and efficient particle swarm optimization (EPSO) methods. The numerical results are illustrated in many Figures and Tables. It has shown that the proposed method is better than the others in terms of total fuel costs, total loss and computational times.
KEYWORDS: Index Terms-Differential Evolution, Optimal Power Flow, Economic Load Dispatch.
-------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 26 September 2014 Date of Publication: 10 October 2014 --------------------------------------------------------------------------------------------------------------------------------------
I. INTRODUCTION
Optimal Power Flow (OPF) and Economic Load Dispatch (ELD) problems are the important fundamental issues in power system operation. In essence, they are the optimization problems and their main objective is to reduce the total generation cost of units, while satisfying constraints. Previous efforts on solving OPF and ELD problems have employed various mathematical programming methods and optimization techniques.Recently, differential evolution (DE) algorithm has been proposed and introduced [1, 2]. The algorithm is inspired by biological and sociological motivations and can take care of optimality on rough, discontinuous and multi-modal surfaces. The DE has three main advantages: it can find near optimal solution regardless the initial parameter values, its convergence is fast and it uses few number of control parameters. In addition, DE is simple in coding and easy to use. It can handle integer and discrete optimization [1, 2]. In this paper, the DE is proposed for solving optimal power flow (OPF) problem. The proposed method has been tested on the standard IEEE 30-bus test systems [17]. The obtain results from the proposed method are compared to those ones from PSO [16], GA [17], ACO [19] methods. Besides, DE method is also proposed for solving ELD problem with valve point effects. This method has tested on 13-unit and 40-unit network. The obtained results are compared to those from Classical Evolutionary Programming (CEP) [4], Improved Fast Evolutionary Programming (IFEP) [4], Improved Particle Swarm Optimization (IPSO) [6] and Efficient Particle Swarm Optimization (EPSO) [5] methods.
II. OPTIMAL POWER FLOW PROBLEM
The OPF problem can be described as an optimization (minimization) process with nonlinear objective function and nonlinear constraints. The general OPF problem can be expressed as Minimize F(x) (1) subject to g(x) = 0 (2) h(x) 0 (3) where F(x) the objective function, g(x) represents the equality constraints, h(x) represents the inequality constraints and is x is the vector of the control variables, that is those which can be varied by a control center operator (generated active and reactive powers, generation bus voltage magnitudes, transformers taps, etc.). The essence of the optimal power flow problem resides in reducing the objective function and simultaneously satisfying the load flow equations (equality constraints) without violating the inequality constraints.
2. Differential Evolution Algorithm for…
www.theijes.com The IJES Page 16
The fuel cost function is given by
2
1
( ) ( )
G N
i i G i i G i
i
F x a b P c P
(4)
Where, NG is the number of generation including the slack bus. PG is the generated active power at bus i. ai, bi
and ci
are the unit costs curve for ith generator.
While minimizing the cost function, it is necessary to make sure that the generation still supplies the load
demands plus losses in transmission lines. Usually the power flow equations are used as equality constraints [5].
( , ) ( )
0
( , ) ( )
i i
i i
i i G D
i i G D
P P V P P
Q Q V Q Q
(5)
Where active and reactive power injection at bus i are defined in the following equation
1
( , ) co s s in
B N
i i j i j i j i j i j
j
P V V V G B
(6)
1
( , ) s in co s
B N
i i j i j i j i j i j
j
Q V V V G B
(7)
The inequality constraints of the OPF reflect the limits on physical devices in power systems as well as the
limits created to ensure system security. The most usual types of inequality constraints are upper bus voltage
limits at generations and load buses, lower bus voltage limits at load buses, reactive power limits at generation
buses, maximum active power limits corresponding to lower limits at some generators, maximum line loading
limits and limits on tap setting. The inequality constraints on the problem variables considered include
Generation constraint: Generator voltages, real power outputs and reactive power outputs are restricted by their
upper and lower bounds as follows
G i ,m in G i G i ,m a x P P P
for i = 1, 2, . . . . . , NG (8)
G i ,m in G i G i ,m a x Q Q Q for i = 1, 2, . . . . . , NG (9)
G i ,m in G i G i ,m a x V V V for i = 1, 2, . . . . . , NG (10)
Shunt VAR constraint: Shunt VAR compensations are restricted by their upper and lower bounds as follows
C i ,m in C i C i ,m a x Q Q Q
for i = 1, 2, . . . . . , NC (11)
where NC is the number of shunt compensator.
Transformer constraint: Transformer tap settings are restricted by their upper and lower bounds as follows
i ,m in i i ,m a x T T T
for i = 1, 2, . . . . . , NT (12)
where NT is the number of transformer tap.
Security constraint: Voltages at load bus are restricted by their upper and lower bounds as follows
L i ,m in L i L i ,m a x V V V
for i = 1, 2, . . . . . , NL (13)
where NL is the number of load bus.
III. ECONOMIC LOAD DISPATCH PROBLEM
The same as OPF, the economic load dispatch problem can be also described as the optimization
(minimization) process with the following objective function
1
( )
N
i i
i
C F P
(14)
where ( ) i i F P is the fuel cost function of the ith unit and Pi is the power generated by the ith unit.
Subject to power balance constraints
3. Differential Evolution Algorithm for…
www.theijes.com The IJES Page 17
1
N
i D L o s s
i
P P P
(15)
where PD is the system load demand and PLoss is the transmission loss. One approach to estimate losses is by
modeling them as a function of outputs of the system generator using Kron’s loss formula of (16).
0 0 0
1 1 1
G G G
i i i
N N N
L G i j G G i
i j j
P P B P P B B
(16)
where Bij, Bi0, B00 are known as the losses or B-coefficients.
and generating capacity constrains
i ,m in i i ,m ax P P P for i = 1, 2, . . . . . , N (17)
where Pi,min and Pi,max are the minimum and maximum power outputs of the ith unit.
The smooth quadratic fuel cost function without valve point loadings of the generating units are given by (4),
where the valve-point effects are ignored. The generating units with multi-valve steam turbines exhibit a greater
variation in the fuel-cost functions. Since the valve point results in the ripples, a cost function contains higher
order nonlinearity. Therefore, the equation (4) should be replaced by (18) for considering the valve-point
effects.
The sinusoidal functions are thus added to the quadratic cost functions as follows [6]
2
,m in ( ) s in ( ( ) ) i i i i i i i i i i i F P a b P c P e f P P (18)
where ai, bi, ci are the fuel cost coefficients of the ith unit and ei and fi are the fuel cost coefficients of the ith unit
with valve point effects.
Fig.1: Example cost function with 6 valves [5]
IV. DIFFERENTIAL EVOLUTION
A. Overview of the DE
In 1995, Storn and Price proposed a new floating point encoded evolutionary algorithm for global
optimization and named it differential evolution (DE) algorithm owing to a special kind of differential operator,
which they invoked to create new off-spring from parent chromosomes instead of classical crossover or
mutation [1].
Similar to GAs, DE algorithm is a population based algorithm that uses crossover, mutation and selection
operators. The main differences between the genetic algorithm and DE algorithm are the selection process and
the mutation scheme that makes DE self adaptive. In DE, all solutions have the same chance of being selected
as parents. DE employs a greedy selection process that is the best new solution and its parent wins the
competition providing significant advantage of converging performance over genetic algorithms.
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Fig.2: DE cycle of stages
B. Differential Evolution Algorithm
DE algorithm is a population based algorithm using three operators; crossover, mutation and selection.
Several optimization parameters must also be tuned. These parameters have joined together under the common
name control parameters. In fact, there are only three real control parameters in the algorithm, which are
differentiation (or mutation) constant F, crossover constant CR, and size of population NP. The rest of the
parameters are dimension of problem D that scales the difficulty of the optimization task; maximum number of
generations (or iterations) GEN, which may serve as a stopping condition; and low and high boundary
constraints of variables that limit the feasible area [1, 2].The proper setting of NP is largely dependent on the
size of the problem. Storn and Price [1] remarked that for real-world engineering problems with D control
variables, NP=20D will probably be more than adequate, NP as small as 5D is often possible, although optimal
solutions using NP<2D should not be expected. In [24], Storn and Price set the size of population less than the
recommended NP=10D in many of their test tasks. In [25], it is recommended using of NP≥4D. In [26], NP=5D
is a good choice for a first try, and then increase or decrease it by discretion. So, as a rough principle, several
tries before solving the problem may be sufficient to choose the suitable number of the individuals.
The DE algorithm works through a simple cycle of stages, presented in Fig. 2.
These stages can be cleared as follow:
1. Initialization
At the very beginning of a DE run, problem independent variables are initialized in their feasible
numerical range. Therefore, if the jth variable of the given problem has its lower and upper bound as xj
L and xj
u
, respectively, then the jth component of the ith population members may be initialized as
, (0 ) (0 ,1) .( )
L u L
i j j j j x x r a n d x x (19)
where rand(0,1) is a uniformly distributed random number between 0 and 1.
2. Mutation
In each generation to change each population member Xi(t), a donor vector vi(t) is created. It is the method of
creating this donor vector, which demarcates between the various DE schemes. However, in this paper, one
such specific mutation strategy known as DE/rand/1 is discussed.
Fig.3: Mutation operator
To create a donor vector vi(t) for each ith member, three parameter vectors xr1, xr2 and xr3 are chosen randomly
from the current population and not coinciding with the current xi. Next, a scalar number F scales the difference
of any two of the three vectors and the scaled difference is added to the third one whence the donor vector vi(t)
is obtained. The usual choice for F is a number between 0.4 and 1.0. So, the process for the jth component of
each vector can be expressed as,
, 1, 2 , 3 , ( 1) ( ) .( ( ) ( )) i j r j r j r j v t x t F x t x t (20)
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3. Crossover
To increase the diversity of the population, crossover operator is carried out in which the donor vector
exchanges its components with those of the current member Xi(t).
Two types of crossover schemes can be used with DE technique. These are exponential crossover and binomial
crossover. Although the exponential crossover was proposed in the original work of Storn and Price [1], the
binomial variant was much more used in recent applications [25]. In exponential type, the crossover is
performed on the D variables in one loop as far as it is within the CR bound. The first time a randomly picked
number between 0 and 1 goes beyond the CR value, no crossover is performed and the remaining variables are
left intact. In binomial type, the crossover is performed on all D variables as far as a randomly picked number
between 0 and 1 is within the CR value. So for high values of CR, the exponential and binomial crossovers
yield similar results. Moreover, in the case of exponential crossover one has to be aware of the fact that there is
a small range of CR values (typically [0.9, 1]) to which the DE is sensitive. This could explain the rule of
thumb derived for the original variant of DE. On the other hand, for the same value of CR, the exponential
variant needs a larger value for the scaling parameter F in order to avoid premature convergence [26].
In this paper, binomial crossover scheme is used which is performed on all D variables and can be expressed as
,
,
,
( ) (0 ,1)
( )
( )
i j
i j
i j
v t i f r a n d C R
u t
x t e ls e
(21)
ui,j(t) represents the child that will compete with the parent xi,j(t).
4. Selection
To keep the population size constant over subsequent generations, the selection process is carried out to
determine which one of the child and the parent will survive in the next generation, i.e., at time t=t+1. DE
actually involves the Survival of the fittest principle in its selection process. The selection process can be
expressed as,
( ) f ( ( ) ) f ( ( ) )
( 1)
( ) if f ( ( ) )< f ( ( ) )
i i i
i
i i i
U t i f U t X t
X t
X t X t U t
(22)
where, f () is the function to be minimized. From Eq. (10) we noticed that:
• If ui(t) yields a better value of the fitness function, it replaces its target Xi(t) in the next generation.
• Otherwise, Xi(t) is retained in the population.
Hence, the population either gets better in terms of the fitness function or remains constant but never
deteriorates.
C. Differential Evolution Implementation
The proposed DE-based approach has been developed and implemented using the MATLAB software.
Several runs have been done with different values of DE key parameters such as differentiation (or mutation)
constant F, crossover constant CR, size of population NP, and maximum number of generations GEN which is
used here as a stopping criteria to find the optimal DE key parameters. In this paper, the following values of DE
key parameters are selected for the optimization of power losses and voltage stability enhancement:
F = 0.2; CR = 0.6; NP = 150; GEN = 300
and DE key parameters for the optimization of voltage deviations are selected as:
F = 0.2; CR = 0.6; NP = 50; GEN = 300
The first step in the algorithm is creating an initial population. All the independent variables which include
generator voltages, transformer tap settings and shunt VAR compensations have to be generated according to
Eq. (19), where each independent parameter of each individual in the population is assigned a value inside its
given feasible region. This creates parent vectors of independent variables for the first generation.
After, finding the independent variables, dependent variables will be found from a load flow solution. These
ependent variables include generators reactive power, voltages at load buses and transmission line loadings. It
should be mentioned that, the real power settings of the generators are taken from [4].
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V. NUMERICAL RESULTS
A. Case of DE problem
To verify the feasibility of the proposed DE method, the standard IEEE 30-bus system [17] has been used to
test the OPF problem. The system line and bus data are given in [20]. The system has six generators at buses 1,
2, 5, 8, 11, 13 and four transformers with off-nominal tap ratio in lines 6-9, 6-10, 4-12, and 28-27. The cost
coefficients in (4) are given in TABLE.I.. The obtained results of the DE are compared with those of other
methods as in TABLE.II.
TABLE I.
GENERATOR COST COEFFICIENTS OF IEEE 30-BUS SYSTEM
Bus a b c
1
2
5
8
11
13
0
0
0
0
0
0
2.00
1.75
1.00
3.25
3.00
3.00
0.00375
0.01750
0.06250
0.00834
0.02500
0.02500
0 50 100 150 200 250 300
795
800
805
810
815
820
825
Iterations
Total cost($)
GA
PSO
DE
Fig.4: Convergence nature of GA, PSO and DE
in IEEE 30-bus system
0 5 10 15 20 25 30
0.9
0.95
1
1.05
1.1
1.15
Fig. 5: System voltage profile of IEEE 30-bus system
The obtained results for the IEEE 30-bus system using the DE are given in Table II and the results are
compared with those from PSO [16], GA [17] and ACO [19]. From the compared results in TABLE.II, It shows
that the DE has succeeded in finding a global optimal solution. As visualized from the Fig.4 and Table III, it
gives that the proposed DE method of optimization is more efficient when compared with other optimization
methods. The optimum active power is in their secure values and is far from the min and max limits. It is also
clear from the optimum solution that the DE easily prevent the violation of all the active constraints. The
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security constraints are also checked for voltage magnitudes in Fig.5. The voltage magnitudes are between their minimum and maximum values. No load bus was at the lower limit of the voltage magnitudes.
TABLE II.
COMPARISON OF RESULTS OF IEEE-30 BUS SYSTEM
B. Case of Economic Load Dispatch problem
1. Case of thirteen-unit system
Consider a thirteen generators case. The cost coefficients of these generators are given in [7]. The demanded load PD of this problem is 1800MW.
TABLE III.
COMPARISON OF RESULTS OF 13-UNIT SYSTEM CONSIDERING VALVE-POINT EFFECTS
Method
CPU time (sec.)
Mean cost ($/h)
Maximum cost ($/h)
Minimum cost ($/h)
CEP
293.41
18190.32
18404.04
18048.21
IFEP
156.81
18127.06
18267.42
17994.07
FEP
166.43
18200.79
18453.82
18018.00
MFEP
315.98
18192.00
18416.89
18028.09
APPSO
–
18014.61
18291.92
17978.89
DPSO
–
18084.99
18310.43
17976.31
EP-SQP
–
18106.93
–
17991.03
PSO-SQP
–
18029.99
–
17969.93
DE
4.45
17968.97
17969.02
17968.94
TABLE IV.
OPTIMAL DISPATCH AND THE CORRESPONDING COST IN 13-UNIT SYSTEM
Unit
Pi,min
Pi,max
Generation (MW)
Cost ($)
1
0
680
538.5587405
4993.5385438
Variable
Optimization Methods
PSO
GA
ACO
DE
P1
176.96
179.367
177.863
177.1567
P2
48.98
44.24
43.8366
48.6905
P5
21.30
24.61
20.8930
21.3013
P8
21.19
19.90
23.1231
20.9714
P11
11.97
10.71
14.0255
11.9314
P13
12.00
14.09
13.1199
12.0078
Q1
-
-3.156
-
-11.3708
Q2
-
42.543
-
32.6600
Q5
-
26.292
-
30.9043
Q8
-
22.768
-
34.1242
Q11
-
29.923
-
18.0076
Q13
-
32.346
-
9.1585
Qc10
3.35
-
-
4.9759
Qc12
2.20
-
-
4.9773
Qc15
1.98
-
-
4.8419
Qc17
3.15
-
-
4.2934
Qc20
4.54
-
-
3.8339
Qc21
3.81
-
-
4.9725
Qc23
3.98
-
-
3.2182
Qc24
5.00
-
-
4.9978
Qc29
2.51
-
-
3.0210
n11
1.0702
-
-
1.0657
n12
0.9557
-
-
0.9211
n15
0.9724
-
-
1.0012
n36
0.9728
-
-
0.9728
V1
1.0855
-
-
1.100
PLoss
-
9.5177
9.4616
8.66
Cost ($/h)
800.41
803.699
803.123
799.194
Time (s)
-
315
20
14.213
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2 0 360 150.4425834 1547.3385496
3 0 360 224.3995664 2152.8361465
4 60 180 109.8665500 1129.4760320
5 60 180 109.8665500 1129.4760320
6 60 180 109.8665502 1129.4760359
7 60 180 109.8665516 1129.4760597
8 60 180 109.8665500 1129.4760321
9 60 180 109.8665500 1129.4760321
10 40 120 77.3999125 808.6529682
11 40 120 40.0000017 474.5440299
12 55 120 55.0000000 607.5910000
13 55 120 55.0000000 607.5910000
Total Generation & Cost DE 1800.0000 17968.95667
0 20 40 60 80 100 120 140 160 180 200
1.75
1.8
1.85
1.9
1.95
2
x 10
4
Iterations
Total cost($)
SPSO
PC-PSO
SOH-PSO
DE
Fig. 6: Convergence nature of SPSO, PC_PSO, SOH_PSO and DE in tested case of 13-unit system considering valve-point effects
TABLE.III shows the minimum, mean, maximum cost achieved by the DE algorithm in 100 runs. Obviously,
the minimum costs acquired by the proposed methods are all lower than that obtained by CEP [4], FEP [4],
IFEP [4], MFEP [4], APPSO [7], DPSO [7], EP-SQP [21], PSO-SQP [21]. The maximum costs of DE are lower
than the minimum costs of other method. The standard deviation of proposed methods is also lower than other
method. These results show that the proposed methods are feasible and indeed capable of acquiring better
solution. The optimal dispatches of the generators are listed in TABLE IV. Also note that all outputs of
generator are within its permissible limits.
2. Case of forty-unit system
To verify the feasibility of the proposed DE method, the forty-unit system [7] were tested. The input data and
the cost coefficients for 40-generating units are given in [7]. The total demanded load PD of this problem is
10500 MW. The results obtained from the DE are compared with those as in TABLE.V.
TABLE V.
COMPARISON OF RESULTS OF 40-UNIT SYSTEM CONSIDERING VALVE-POINT EFFECTS
Method
CPU time
(sec.)
Mean cost
($/h)
Maximum
cost ($/h)
Minimum cost
($/h)
CEP 1955.20 124793.48 126902.89 123488.29
IFEP 1165.70 123382.00 125740.63 122624.35
APPSO - 123985.15 126259.11 122044.63
DPSO - 123647.81 125295.98 122159.99
IPSO - 121699.30 122168.11 121495.70
EPSO - NA NA 124577.27
MPSO - NA NA 122252.26
ESO - 122524.07 123143.07 122122.16
PSO-LRS - 122558.46 123461.68 122035.79
NPSO - 122221.37 122995.09 122221.37
NPSO-LRS - 122209.32 122981.60 121664.43
SOH_PSO - 121853.57 122446.30 121501.14
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DE
7.47
121467.99
121773.89
121416.42
TABLE.V shows the best solution time, maximum cost, mean cost, and minimum cost achieved by the DE algorithms in 100 runs. The DE required the least solution time. The minimum cost achieved by DE was the best. The maximum costs of DE are lower than the minimum costs that obtained by CEP [4], IFEP [4], IPSO [6], APPSO [7], DPSO [7], EPSO [5], MPSO [23], ESO [22], PSO-LRS [24], NPSO [24], NPSO-LRS [24], SPSO [9], PC_PSO [9], SOH_PSO [9]. The standard deviation of proposed methods is also lower than other method. The generation outputs and the corresponding costs of the best solution are provided in TABLE.VI. The DE has provided better solutions compared with other methods. We have also observed that the solutions obtained by DE always satisfy the equality and inequality constraints.
TABLE VI. DISPATCH AND THE CORRESPONDING COST IN 40-UNIT SYSTEM
Unit
Pi,min
Pi,max
Generation (MW)
Cost ($)
1
36
114
110.7998
925.0964
2
36
114
110.7998
925.0963
3
60
120
97.3999
1190.5485
4
80
190
179.7330
2143.5503
5
47
97
87.7999
706.5001
6
68
140
142.7998
1604.7428
7
110
300
259.5996
2612.8845
8
135
300
284.5996
2779.8366
9
135
300
284.5996
2798.2302
10
130
300
130.0000
2502.0650
11
94
375
93.9998
1893.3043
12
94
375
93.9944
1908.1362
13
125
500
304.5195
5110.2971
14
125
500
304.5195
5149.6989
15
125
500
394.2793
6436.5862
16
125
500
394.2793
6436.5862
17
220
500
489.2793
5296.7107
18
220
500
489.2793
5288.7651
19
242
550
511.2793
5540.9292
20
242
550
505.0000
5627.7512
21
254
550
523.2793
5071.2897
22
254
550
523.2793
5071.2896
23
254
550
523.2793
5057.2231
24
254
550
523.2793
5057.2230
25
254
550
523.2793
5275.0885
26
254
550
523.2793
5275.0885
27
10
150
11.0000
1164.0309
28
10
150
10.0000
1140.5240
29
10
150
10.0000
1140.5240
30
47
97
95.0000
823.1977
31
60
190
197.9999
1658.9037
32
60
190
197.9999
1658.9037
33
60
190
197.9999
1658.9037
34
90
200
180.0000
1841.2934
35
90
200
164.7998
1539.8703
36
90
200
205.6835
2091.6657
37
25
110
109.9995
1220.1637
38
25
110
108.0000
1207.1644
39
25
110
100.0000
1126.5035
40
242
550
503.2792
5534.6712
Total Generation & Cost DE
10500.00
121417.31
SPSO
10500.000
122049.6600
PC-PSO
10500.000
121767.8900
SOH-PSO
10500.000
121501.1400
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0 50 100 150 200 250 300
1.214
1.216
1.218
1.22
1.222
1.224
1.226
x 10
5
Iterations
Total cost($)
DE
SPSO
SOH-PSO
SPSO
Fig.7. Convergence nature of SPSO, PC_PSO, SOH_PSO and DE in tested case of 40-unit system considering valve-point effects
VI. CONCLUSION
In this paper, the differential evolution method has been presented to solve the OPF and non-smooth
ELD problems. From the obtained results of OPF and ELD are tested to IEEE 30-bus, 13-unit and 40-unit
networks, we can present the some following conclusions + The differential evolution method has increased
the convergence speed of our algorithm. It also means that the iterative numbers are decreased as in Fig.4.
The proposed algorithms have the capability to obtain better solutions than various other methods in terms of
total costs and computational times. Therefore, this algorithm is effective and efficient solving the OPF and
ELD problems of large-scale power systems with valve point effects and FACTS devices.With the advantages of
DE, we can use it for calculating some problems in power systems such as the OPF of AC/DC power systems,
the OPF of interconnected systems, the FACTS location optimization, etc. All will be done in next works.
REFERENCES
[1]. R. Storn, K. Price, Differential Evolution, “A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces,”
Technical Report TR-95-012, ICSI, 1995.
[2]. S. Das, A. Abraham, A. Konar, “Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and
Hybridization Perspectives,” Available at www.softcomputing.net/aciis.pdf.
[3]. Nidul Sinha, R. Chakrabarti and P. K. Chattopadhyay, “Evolutionary Programming Techniques for Economic Load Dispatch,” IEEE
Transactions on Evolutionary Computation, Vol. 7 No.1, pp. 83-94, 2003.
[4]. Dr. K. Thanushkodi, S. Muthu Vijaya Pandian, R.S.Dhivy Apragash, M. Jothikumar, S.sriramnivas and K.Vindoh, “An Efficient Particle
Swarm Optimization for Economic Dispatch Problems With Non-smooth cost functions,” WSEAS Transactions on Power Systems, Issue 4,
Volume 3, pp. 257-266, April 2008.
[5]. Jong-Bae Park, Member, IEEE, Yun-Won Jeong, Woo-Nam Lee, and Joong-Rin Shin, “An Improved Particle Swarm Optimization for
Economic Dispatch Problems with Non-Smooth Cost Functions,” IEEE Power Engineering Society General Meeting, 2006.
[6]. C. H. Chen, and S. N. Yeh, “Particle Swarm Optimization for Economic Power Dispatch with Valve-Point Effects,” 2006 IEEE PES
Transmission and Distribution Conference and Exposition Latin America, Venezuela, 15-18 Aug. 2006.
[7]. K. S. Swarup, “Swarm intelligence approach to the solution of optimal power flow,” Indian Institute of Science, pp. 439–455, Oct. 2006.
[8]. K. T. Chaturvedi, Manjaree Pandit Member IEEE, and Laxmi Srivastava Member IEEE, “Self-Organizing Hierarchical Particle Swarm
Optimization for Nonconvex Economic Dispatch,” IEEE Transactions on Power Systems, Vol. 23, No. 3, pp. 1079-1087, August 2008.
[9]. Hirotaka Yoshida, Kenichi Kawata, Yoshikazu Fukuyama, Yosuke Nakanishi, “A Particle Swarm Optimization for Reactive Power and
Voltage control considering Voltage security assessment,” IEEE Trans. on Power Systems, Vol.15, No.4, pp.1232-1239, November 2001.
[10]. G. Krost, G. K. Venayagamoorthy, L. Grant, “Swarm Intelligence and Evolutionary Approaches for Reactive Power and Voltage Control,”
2008 IEEE Swarm Intelligence Symposium, September 21-23, 2008.
[11]. N. Mo, Z.Y. Zou, K.W. Chan and T.Y.G. Pong, “Transient stability constrained optimal power flow using particle swarm optimisation,” IEEE
Generation, Transmission & Distribution, Volume 1, Issue 3, pp. 476–483, May 2007.
[12]. Bo Zhao, Quanyuan Jiang, Chuangxin Guo, Yijia Cao, “A novel particle swarm optimization approach for optimal reactive power dispatch,”
15th PSCC, Liege, Session 21, 22-26 August 2005.
[13]. Adel Ali Abou El-Ela, Ragab Abdel-Aziz El-Sehiemy “Optimized Generation Costs Using Modified Particle Swarm Optimization Version,”
Wseas Transactions on Power Systems, pp. 225-232, Oct. 20, 2007.
[14]. S. Sutha, and N. Kamaraj, “Optimal Location of Multi Type Facts Devices for Multiple Contingencies Using Particle Swarm Optimization,”
International Journal of Electrical Systems Science and Engineering, Volume 1, Number 1, pp. 16-22.
[15]. M.A. Abido, “Optimal Power Flow Using Particle Swarm Optimization,” Elsevier Science, Electrical Power and Energy Systems, 24 (2002),
pp. 563-571, 2002.
[16]. Tarek Bouktir, Linda Slimani, M. Belkacemi, “A Genetic Algorithm for Solving the Optimal Power Flow Problem,” Leonardo Journal of
Sciences, Issue 4, pp. 44-58, January-June 2004.
11. Differential Evolution Algorithm for…
www.theijes.com The IJES Page 25
[17]. Musrrat Ali, Millie Pant, and V. P. Singh, “An Improved Differential Evolution Algorithm for Real Parameter Optimization Problems,” International Journal of Recent Trends in Engineering, Vol. 1, No. 5, May 2009.
[18]. Boumediène Allaoua, Abdellah Laoufi, “Optimal Power Flow Solution Using Ant Manners for Electrical Network,” Advances in Electrical and Computer Engineering, Volume 9, Number 1, pp. 34-40, 2009.
[19]. Hadi Saadat, Milwaukee School of engineering, “Power System analysis,” second edition, Mc GrawHill, 2002.
[20]. T.A.A. Victoire, A.E. Jeyakumar, Hybrid PSO-SQP for economic dispatch with valve-point effect, Electric Power Syst. Res. 71 (1), pp. 51–59, 2004.