The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Solving the Power Purchase Cost Optimization Problem with Improved DE AlgorithmIJEACS
Under the deregulation of generation market in China, all distributed generators will particular in electric power bidding. Therefore power purchase cost optimization (PPCO) problem has been getting more attention of power grid Company. However, under the competition principle, they can purchase power from several of power plants, therefor, there exist continuous and integral variables in purchase cost model, which is difficult to solve by classical linear optimization method. An improved differential evolution algorithm is proposed and employed to solve the PPCO problem, which targets on minimum purchase cost, considering the supply and demand balance, generation and transfer capability as constraints. It yields the global optimum solution of the PPCO problem. The numerical results show that the proposed algorithm can solve the PPCO problem and saves the costs of power purchase. It has a widely practical value of application.
A Hybrid Formulation between Differential Evolution and Simulated Annealing A...TELKOMNIKA JOURNAL
The aim of this paper is to solve the optimal reactive power dispatch (ORPD) problem.
Metaheuristic algorithms have been extensively used to solve optimization problems in a reasonable time
without requiring in-depth knowledge of the treated problem. The perform ance of a metaheuristic requires
a compromise between exploitation and exploration of the search space. However, it is rarely to have the
two characteristics in the same search method, where the current emergence of hybrid methods. This
paper presents a hybrid formulation between two different metaheuristics: differential evolution (based on a
population of solution) and simulated annealing (based on a unique solution) to solve ORPD. The first one
is characterized with the high capacity of exploration, while the second has a good exploitation of the
search space. For the control variables, a mixed representation (continuous/discrete), is proposed. The
robustness of the method is tested on the IEEE 30 bus test system.
Genetic algorithm based Different Re-dispatching Scheduling of Generator Unit...IDES Editor
Proper pricing of active power is an important issue
in deregulated power environment. This paper presents a
flexible formulation for determining short run marginal cost
of synchronous generators using genetic algorithm based
different re-dispatching scheduling considering economic load
dispatch as well as optimized loss condition. By integrating
genetic algorithm based solution, problem formulation became
easier. The solution obtained from this methodology is quite
encouraging and useful in the economic point of view and it
has been observed that for calculating short run marginal
cost, generator re-dispatching solution is better than classical
method solution. The proposed approach is efficient in the
real time application and allows for carrying out active power
pricing independently. The paper includes test result of IEEE
30 bus standard test system.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...paperpublications3
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dis...ijeei-iaes
In this paper, a novel approach Modified Monkey optimization (MMO) algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problemijeei-iaes
This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Implementation of an Effective Biogeography Based Algorithm
(EBBO) for Economic Load Dispatch (ELD) problems in power system in order to obtain optimal
economic dispatch with minimum generation cost. Approach: A viable methodology has been
implemented for a 20 unit generator system to minimize the fuel cost function considering the
transmission loss and system operating limit constraints and is compared with other approaches such as
BBO, Lambda Iteration and Hopfield Model. Results: Proposed algorithm has been applied to ELD
problems for verifying its feasibility and the comparison of results are tabulated and pictorial
visualization for convergence of EBBO is represented. Conclusion: Comparing with the other existing
techniques, the EBBO gives better result by considering the quality of the solution obtained. This
method could be an alternative approach for solving the ELD problems in practical power system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Solving the Power Purchase Cost Optimization Problem with Improved DE AlgorithmIJEACS
Under the deregulation of generation market in China, all distributed generators will particular in electric power bidding. Therefore power purchase cost optimization (PPCO) problem has been getting more attention of power grid Company. However, under the competition principle, they can purchase power from several of power plants, therefor, there exist continuous and integral variables in purchase cost model, which is difficult to solve by classical linear optimization method. An improved differential evolution algorithm is proposed and employed to solve the PPCO problem, which targets on minimum purchase cost, considering the supply and demand balance, generation and transfer capability as constraints. It yields the global optimum solution of the PPCO problem. The numerical results show that the proposed algorithm can solve the PPCO problem and saves the costs of power purchase. It has a widely practical value of application.
A Hybrid Formulation between Differential Evolution and Simulated Annealing A...TELKOMNIKA JOURNAL
The aim of this paper is to solve the optimal reactive power dispatch (ORPD) problem.
Metaheuristic algorithms have been extensively used to solve optimization problems in a reasonable time
without requiring in-depth knowledge of the treated problem. The perform ance of a metaheuristic requires
a compromise between exploitation and exploration of the search space. However, it is rarely to have the
two characteristics in the same search method, where the current emergence of hybrid methods. This
paper presents a hybrid formulation between two different metaheuristics: differential evolution (based on a
population of solution) and simulated annealing (based on a unique solution) to solve ORPD. The first one
is characterized with the high capacity of exploration, while the second has a good exploitation of the
search space. For the control variables, a mixed representation (continuous/discrete), is proposed. The
robustness of the method is tested on the IEEE 30 bus test system.
Genetic algorithm based Different Re-dispatching Scheduling of Generator Unit...IDES Editor
Proper pricing of active power is an important issue
in deregulated power environment. This paper presents a
flexible formulation for determining short run marginal cost
of synchronous generators using genetic algorithm based
different re-dispatching scheduling considering economic load
dispatch as well as optimized loss condition. By integrating
genetic algorithm based solution, problem formulation became
easier. The solution obtained from this methodology is quite
encouraging and useful in the economic point of view and it
has been observed that for calculating short run marginal
cost, generator re-dispatching solution is better than classical
method solution. The proposed approach is efficient in the
real time application and allows for carrying out active power
pricing independently. The paper includes test result of IEEE
30 bus standard test system.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...paperpublications3
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dis...ijeei-iaes
In this paper, a novel approach Modified Monkey optimization (MMO) algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases. The proposed (MMO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problemijeei-iaes
This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Implementation of an Effective Biogeography Based Algorithm
(EBBO) for Economic Load Dispatch (ELD) problems in power system in order to obtain optimal
economic dispatch with minimum generation cost. Approach: A viable methodology has been
implemented for a 20 unit generator system to minimize the fuel cost function considering the
transmission loss and system operating limit constraints and is compared with other approaches such as
BBO, Lambda Iteration and Hopfield Model. Results: Proposed algorithm has been applied to ELD
problems for verifying its feasibility and the comparison of results are tabulated and pictorial
visualization for convergence of EBBO is represented. Conclusion: Comparing with the other existing
techniques, the EBBO gives better result by considering the quality of the solution obtained. This
method could be an alternative approach for solving the ELD problems in practical power system.
Determining optimal location and size of capacitors in radial distribution ne...IJECEIAES
In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.
An Improved Differential Evolution Algorithm for Congestion Management Consid...Suganthi Thangaraj
In deregulated electricity market, Congestion Management (CM) is one of the most significant issues in order to maintain
the system in secure state and to get the reliable system operation. While addressing Congestion Management voltage
stability should also be taken into account. This paper elucidates an Improved Differential Evolution (IDE) algorithm to
alleviate Congestion in transmission line by rescheduling of generators while considering voltage stability. Differential
Evolution (DE) is one of the heuristic, population based algorithm which is well suited for solving complex and non-linear
optimization problems. A Double Best Mutation Operator (DBMO) is proposed to improve DE algorithm’s convergence
rate. In order to validate suitability of the suggested approach, it has been evaluated on the IEEE-30 bus test system on
both base case loading as well as 10% increased load. The test system has been also examined under critical line outages.
The results and discussions clearly depicts the effectiveness of the projected approach in solving Congestion Management
Problem.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
FLOWER POLLINATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PRO...paperpublications3
Abstract: This paper proposes a Flower Pollination Algorithm for solving the multi-objective reactive power dispatch problem. Minimization of real power loss and enhancement voltage stability index margin is taken as objective. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The simulation results demonstrate better performance of the FPA in solving an optimal reactive power dispatch problem. In order to evaluate the performance of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms. Simulation results show that FPA is better than other algorithms in reducing the real power loss and enhancing the voltage stability.
Keywords: flower algorithm, optimization, metaheuristics, optimal reactive power, Transmission loss.
The presented approach is conceptually useful in
illustrating the alteration in motor units (MUs) for
neuromuscular disorders and discussed on the properties of
PDS & PSD of EMG signals. The proposed power spectral
density method comparatively analyzed the healthy &
neuropathy signals with Welch's PSD estimation method by
Hamming & Kaiser Window. The distributions of power over
frequency components for both the signals are significantly
compared. This analysis is intended to provide an automatic
diagnosis of an individual’s muscle condition.
Vibrational Behaviour of Composite Beams Based on Fiber Orientation with Piez...IJMERJOURNAL
ABSTRACT: A smart structure can sense the vibration and generate a controlled actuation, so that the vibration can be minimized. For this purpose, smart materials are used as actuators and sensors. Among all the smart materials Lead Zirconate Titanate (PZT) is used as smart material and the smart structures are taken as carbon-epoxy cantilever beams. In the present work an attempt has been made to study the effect of dimensions of PZT and position of PZT on the natural frequency of smart structure. In this work the simulation analysis and experimental analysis were carried out on the carbon epoxy cantilever beams for different fibre orientations like 00 ,300 and 600 with and without PZT patch at different positions. The simulation is carried out by using ANSYS and experimentation is carried out by using FFT analyser, accelerometer and impact hammer. Both the experimentation and simulation results show the effective control in the vibration of the structure, the required decrease in the natural frequency is observed with reference to the both patch dimension and position. Thus the results of this work conclude that the dimensions of the PZTand positioning of the PZT influences the natural frequency of the smart structure.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
call for paper 2012, hard copy of journal, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
Capacitor Placement Using Bat Algorithm for Maximum Annual Savings in Radial ...IJERA Editor
This paper presents a two stage approach that determines the optimal location and size of capacitors on radial distribution systems to improve voltage profile and to reduce the active power loss. In first stage, the capacitor locations can be found by using loss sensitivity method. Bat algorithm is used for finding the optimal capacitor sizes in radial distribution systems. The sizes of the capacitors corresponding to maximum annual savings are determined by considering the cost of the capacitors. The proposed method is tested on 15-bus, 33 bus, 34-bus, 69-bus and 85-bus test systems and the results are presented.
This paper introduces a solution of the economic load dispatch (ELD) problem using a hybrid approach of fuzzy logic and genetic algorithm (GA). The proposed method combines and extends the attractive features of both fuzzy logic and GA. The proposed approach is compared with lambda iteration method (LIM) and GA. The investigation reveals that the proposed approach can provide accurate solution with fast convergence characteristics and is superior to the GA and LIM.
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimizationijeei-iaes
This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.
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.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
Coordinated Placement and Setting of FACTS in Electrical Network based on Kal...IJECEIAES
To aid the decision maker, the optimal placement of FACTS in the electrical network is performed through very specific criteria. In this paper, a useful approach is followed; it is based particularly on the use of KalaiSmorodinsky bargaining solution for choosing the best compromise between the different objectives commonly posed to the network manager such as the cost of production, total transmission losses (Tloss), and voltage stability index (Lindex). In the case of many possible solutions, Voltage Profile Quality is added to select the best one. This approach has offered a balanced solution and has proven its effectiveness in finding the best placement and setting of two types of FACTS namely Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) in the power system. The test case under investigation is IEEE-14 bus system which has been simulated in MATLAB Environment.
Passerine swarm optimization algorithm for solving optimal reactive power dis...IJAAS Team
This paper presents Passerine Swarm Optimization Algorithm (PSOA) for solving optimal reactive power dispatch problem. This algorithm is based on behaviour of social communications of Passerine bird. Basically, Passerine bird has three common behaviours: search behaviour, adherence behaviour and expedition behaviour. Through the shared communications Passerine bird will search for the food and also run away from hunters. By using the Passerine bird communications and behaviour, five basic rules have been created in the PSOA approach to solve the optimal reactive power dispatch problem. Key aspect is to reduce the real power loss and also to keep the variables within the limits. Proposed Passerine Swarm Optimization Algorithm (PSOA) has been tested in standard IEEE 30 bus test system and simulations results reveal about the better performance of the proposed algorithm in reducing the real power loss and enhancing the static voltage stability margin.
Voltage Profile Enhancement and Reduction of Real Power loss by Hybrid Biogeo...ijeei-iaes
This paper presents Hybrid Biogeography algorithm for solving the multi-objective reactive power dispatch problem in a power system. Real Power Loss minimization and maximization of voltage stability margin are taken as the objectives. Artificial bee colony optimization (ABC) is quick and forceful algorithm for global optimization. Biogeography-Based Optimization (BBO) is a new-fangled biogeography inspired algorithm. It mainly utilizes the biogeography-based relocation operator to share the information among solutions. In this work, a hybrid algorithm with BBO and ABC is projected, and named as HBBABC (Hybrid Biogeography based Artificial Bee Colony Optimization), for the universal numerical optimization problem. HBBABC merge the searching behavior of ABC with that of BBO. Both the algorithms have different solution probing tendency like ABC have good exploration probing tendency while BBO have good exploitation probing tendency. HBBABC used to solve the reactive power dispatch problem and the proposed technique has been tested in standard IEEE30 bus test system.
Determining optimal location and size of capacitors in radial distribution ne...IJECEIAES
In this study, the problem of optimal capacitor location and size determination (OCLSD) in radial distribution networks for reducing losses is unraveled by moth swarm algorithm (MSA). MSA is one of the most powerful meta-heuristic algorithm that is taken from the inspiration of the food source finding behavior of moths. Four study cases of installing different numbers of capacitors in the 15-bus radial distribution test system including two, three, four and five capacitors areemployed to run the applied MSA for an investigation of behavior and assessment of performances. Power loss and the improvement of voltage profile obtained by MSA are compared with those fromother methods. As a result, it can be concluded that MSA can give a good truthful and effective solution method for OCLSD problem.
An Improved Differential Evolution Algorithm for Congestion Management Consid...Suganthi Thangaraj
In deregulated electricity market, Congestion Management (CM) is one of the most significant issues in order to maintain
the system in secure state and to get the reliable system operation. While addressing Congestion Management voltage
stability should also be taken into account. This paper elucidates an Improved Differential Evolution (IDE) algorithm to
alleviate Congestion in transmission line by rescheduling of generators while considering voltage stability. Differential
Evolution (DE) is one of the heuristic, population based algorithm which is well suited for solving complex and non-linear
optimization problems. A Double Best Mutation Operator (DBMO) is proposed to improve DE algorithm’s convergence
rate. In order to validate suitability of the suggested approach, it has been evaluated on the IEEE-30 bus test system on
both base case loading as well as 10% increased load. The test system has been also examined under critical line outages.
The results and discussions clearly depicts the effectiveness of the projected approach in solving Congestion Management
Problem.
NOVEL PSO STRATEGY FOR TRANSMISSION CONGESTION MANAGEMENTelelijjournal
In post deregulated era of power system load characteristics become more erratic. Unplanned transactions
of electrical power through transmission lines of particular path may occur due to low cost offered by
generating companies. As a consequence those lines driven close to their operating limits and becomes
congested as the lines are originally designed for traditional vertically integrated structure of power
system. This congestion in transmission lines is unpredictable with deterministic load flow strategy.
Rescheduling active and reactive power output of generators is the promising way to manage congestion.
In this paper Particle Swarm Optimization (PSO) with varying inertia weight strategy, with two variants
e1-PSO and e-2 PSO is applied for optimal solution of active and reactive power rescheduling for
managing congestion. The generators sensitivity technique is opted for identifying participating generators
for managing congestion. Proposed algorithm is tested on IEEE 30 bus system. Comparison is made
between results obtained from proposed techniques to that of results reported in previous literature.
FLOWER POLLINATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PRO...paperpublications3
Abstract: This paper proposes a Flower Pollination Algorithm for solving the multi-objective reactive power dispatch problem. Minimization of real power loss and enhancement voltage stability index margin is taken as objective. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The simulation results demonstrate better performance of the FPA in solving an optimal reactive power dispatch problem. In order to evaluate the performance of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms. Simulation results show that FPA is better than other algorithms in reducing the real power loss and enhancing the voltage stability.
Keywords: flower algorithm, optimization, metaheuristics, optimal reactive power, Transmission loss.
The presented approach is conceptually useful in
illustrating the alteration in motor units (MUs) for
neuromuscular disorders and discussed on the properties of
PDS & PSD of EMG signals. The proposed power spectral
density method comparatively analyzed the healthy &
neuropathy signals with Welch's PSD estimation method by
Hamming & Kaiser Window. The distributions of power over
frequency components for both the signals are significantly
compared. This analysis is intended to provide an automatic
diagnosis of an individual’s muscle condition.
Vibrational Behaviour of Composite Beams Based on Fiber Orientation with Piez...IJMERJOURNAL
ABSTRACT: A smart structure can sense the vibration and generate a controlled actuation, so that the vibration can be minimized. For this purpose, smart materials are used as actuators and sensors. Among all the smart materials Lead Zirconate Titanate (PZT) is used as smart material and the smart structures are taken as carbon-epoxy cantilever beams. In the present work an attempt has been made to study the effect of dimensions of PZT and position of PZT on the natural frequency of smart structure. In this work the simulation analysis and experimental analysis were carried out on the carbon epoxy cantilever beams for different fibre orientations like 00 ,300 and 600 with and without PZT patch at different positions. The simulation is carried out by using ANSYS and experimentation is carried out by using FFT analyser, accelerometer and impact hammer. Both the experimentation and simulation results show the effective control in the vibration of the structure, the required decrease in the natural frequency is observed with reference to the both patch dimension and position. Thus the results of this work conclude that the dimensions of the PZTand positioning of the PZT influences the natural frequency of the smart structure.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
call for paper 2012, hard copy of journal, research paper publishing, where to publish research paper,
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
Capacitor Placement Using Bat Algorithm for Maximum Annual Savings in Radial ...IJERA Editor
This paper presents a two stage approach that determines the optimal location and size of capacitors on radial distribution systems to improve voltage profile and to reduce the active power loss. In first stage, the capacitor locations can be found by using loss sensitivity method. Bat algorithm is used for finding the optimal capacitor sizes in radial distribution systems. The sizes of the capacitors corresponding to maximum annual savings are determined by considering the cost of the capacitors. The proposed method is tested on 15-bus, 33 bus, 34-bus, 69-bus and 85-bus test systems and the results are presented.
This paper introduces a solution of the economic load dispatch (ELD) problem using a hybrid approach of fuzzy logic and genetic algorithm (GA). The proposed method combines and extends the attractive features of both fuzzy logic and GA. The proposed approach is compared with lambda iteration method (LIM) and GA. The investigation reveals that the proposed approach can provide accurate solution with fast convergence characteristics and is superior to the GA and LIM.
Reduction of Active Power Loss byUsing Adaptive Cat Swarm Optimizationijeei-iaes
This paper presents, an Adaptive Cat Swarm Optimization (ACSO) for solving reactive power dispatch problem. Cat Swarm Optimization (CSO) is one of the new-fangled swarm intelligence algorithms for finding the most excellent global solution. Because of complication, sometimes conventional CSO takes a lengthy time to converge and cannot attain the precise solution. For solving reactive power dispatch problem and to improve the convergence accuracy level, we propose a new adaptive CSO namely ‘Adaptive Cat Swarm Optimization’ (ACSO). First, we take account of a new-fangled adaptive inertia weight to velocity equation and then employ an adaptive acceleration coefficient. Second, by utilizing the information of two previous or next dimensions and applying a new-fangled factor, we attain to a new position update equation composing the average of position and velocity information. The projected ACSO has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the high-quality performance of the planned algorithm in tumbling the real power loss.
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.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
Coordinated Placement and Setting of FACTS in Electrical Network based on Kal...IJECEIAES
To aid the decision maker, the optimal placement of FACTS in the electrical network is performed through very specific criteria. In this paper, a useful approach is followed; it is based particularly on the use of KalaiSmorodinsky bargaining solution for choosing the best compromise between the different objectives commonly posed to the network manager such as the cost of production, total transmission losses (Tloss), and voltage stability index (Lindex). In the case of many possible solutions, Voltage Profile Quality is added to select the best one. This approach has offered a balanced solution and has proven its effectiveness in finding the best placement and setting of two types of FACTS namely Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) in the power system. The test case under investigation is IEEE-14 bus system which has been simulated in MATLAB Environment.
Passerine swarm optimization algorithm for solving optimal reactive power dis...IJAAS Team
This paper presents Passerine Swarm Optimization Algorithm (PSOA) for solving optimal reactive power dispatch problem. This algorithm is based on behaviour of social communications of Passerine bird. Basically, Passerine bird has three common behaviours: search behaviour, adherence behaviour and expedition behaviour. Through the shared communications Passerine bird will search for the food and also run away from hunters. By using the Passerine bird communications and behaviour, five basic rules have been created in the PSOA approach to solve the optimal reactive power dispatch problem. Key aspect is to reduce the real power loss and also to keep the variables within the limits. Proposed Passerine Swarm Optimization Algorithm (PSOA) has been tested in standard IEEE 30 bus test system and simulations results reveal about the better performance of the proposed algorithm in reducing the real power loss and enhancing the static voltage stability margin.
Voltage Profile Enhancement and Reduction of Real Power loss by Hybrid Biogeo...ijeei-iaes
This paper presents Hybrid Biogeography algorithm for solving the multi-objective reactive power dispatch problem in a power system. Real Power Loss minimization and maximization of voltage stability margin are taken as the objectives. Artificial bee colony optimization (ABC) is quick and forceful algorithm for global optimization. Biogeography-Based Optimization (BBO) is a new-fangled biogeography inspired algorithm. It mainly utilizes the biogeography-based relocation operator to share the information among solutions. In this work, a hybrid algorithm with BBO and ABC is projected, and named as HBBABC (Hybrid Biogeography based Artificial Bee Colony Optimization), for the universal numerical optimization problem. HBBABC merge the searching behavior of ABC with that of BBO. Both the algorithms have different solution probing tendency like ABC have good exploration probing tendency while BBO have good exploitation probing tendency. HBBABC used to solve the reactive power dispatch problem and the proposed technique has been tested in standard IEEE30 bus test system.
Comparative study of methods for optimal reactive power dispatchelelijjournal
Reactive power dispatch plays a main role in order to provide good facility secure and economic operation
in the power system. In a power system optimal reactive power dispatch is supported to improve the voltage
profile, to reduce losses, to improve voltage stability, to reduce cost etc. This paper presents a brief literature survey of reactive power dispatch and also discusses a comparative study of conventional and evolutionary computation techniques applied for reactive power dispatch. The paper is useful for researchers for further research and study so that it can apply in the various areas of power system
Hybrid Particle Swarm Optimization for Multi-objective Reactive Power Optimiz...IDES Editor
This paper presents a new hybrid particle swarm
optimization (HPSO) method for solving multi-objective real
power optimization problem. The objectives of the
optimization problem are to minimize the losses and to
maximize the voltage stability margin. The proposed method
expands the original GA and PSO to tackle the mixed –integer
non- linear optimization problem and achieves the voltage
stability enhancement with continuous and discrete control
variables such as generator terminal voltages, tap position of
transformers and reactive power sources. A comparison is made
with conventional, GA and PSO methods for the real power
losses and this method is found to be effective than other
methods. It is evaluated on the IEEE 30 and 57 bus test system,
and the simulation results show the effectiveness of this
approach for improving voltage stability of the system.
A Particle Swarm Optimization for Reactive Power Optimizationijceronline
This paper presents implementation of new algorithm Particle Swarm Optimization (PSO) for Energy Saving through minimizing power losses. The PSO Algorithm Solution is tested in standard IEEE 30 Bus system. The objective is to optimize the reactive power dispatch with optimal setting of control variables without violating inequality constraints and satisfying equality constraint. Control Variables are of both types: Continuous and Discrete. The continuous control variables are generator bus voltage magnitudes;whereas the discrete variables are transformer tap settings and reactive power of shunt compensators (Capacitor banks) .
Security constrained optimal load dispatch using hpso technique for thermal s...eSAT Journals
Abstract This paper presents Hybrid Particle Swarm Optimization (HPSO) technique to solve the Optimal Load Dispatch (OLD) problems with line flow constrain, bus voltage limits and generator operating constraints. In the proposed HPSO method both features of EP and PSO are incorporated, so the combined HPSO algorithm may become more effective to find the optimal solutions. In this paper, the proposed Hybrid PSO, PSO and EP techniques have been tested on IEEE14, 30 bus systems. Numerical simulation results show that the Hybrid PSO algorithm outperformed standard PSO algorithm and Evolution Programming method on the same problem and can save considerable cost of Optimal Load Dispatch.
Optimal siting and sizing of unified power flow controller using sensitivity...IJECEIAES
This paper presents Sensitivity constrained placement of unified power flow controller (UPFC) considering active-power flow sensitive index (APFSI) and static voltage stability index (STATIC-VSI) to minimize active-power losses and to improve power transmission capacity. The sensitive factors are derived with respect to voltage, phase angle and current to formulate APFSI. Transmission line impedance parameters along with active and reactivepower flow measurements are considered to formulate static-VSI. Sensitivity constrained differential evolutionary (SCDE) algorithm is proposed for parameter setting through which power control and minimization of losses in system can be achieved. Testing is performed on IEEE-5, 14 and 30-bus networks in MATLAB and results indicate that SCDE is robust optimization technique compared to conventional method and genetic algorithm (GA).
FLOWER POLLINATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER DISPATCH PROBLEMpaperpublications3
Abstract: This paper proposes a Flower Pollination Algorithm for solving the multi-objective reactive power dispatch problem. Minimization of real power loss and enhancement voltage stability index margin is taken as objective. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The simulation results demonstrate better performance of the FPA in solving an optimal reactive power dispatch problem. In order to evaluate the performance of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms. Simulation results show that FPA is better than other algorithms in reducing the real power loss and enhancing the voltage stability.
Combination of Immune Genetic Particle Swarm Optimization algorithm with BP a...paperpublications3
Abstract:In this paper, merging Immune Genetic Particle Swarm Optimization algorithm (IGPSO) with BP algorithm to optimize BP Neural Network parameter i.e., BPIGPSO amalgamation to solve optimal reactive power dispatch algorithm. The basic perception is that first training BP neural network with IGPSO to find out a comparatively optimal solution, then take the network parameter at this time as the preliminary parameter of BP algorithm to carry out the training, finally searching the optimal solution. The proposed BPIGPSO has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Keywords:BP neural network, Immune Genetic Particle Swarm Optimization algorithm, Optimal Reactive Power, Transmission loss.
The new energy source utilization and development, gradual rise of distributed power grid miniaturization, intelligence, control has become a trend. In order to make microgrid reliable and efficiently run, control technology of microgrid has become a top priority and an inverter as microgrid basic unit, its control has become the most important part in microgrid. In this paper, three inverters are operated in parallel using an P-V/Q-F droop control is investigated. Mathematical model of three phase inverter with LC filter is derived, which is based on the voltage and current dual control loop. Parallel control strategy based on P-V/Q-F droop control, does not require a real time communications between the inverters and more suitable for microgrid applications. To verify the feasibility and validity of the droop control scheme, simulation is done in Matlab/Simulink and results indicate droop control has significant effect on power sharing and balancing the voltage magnitude, frequency.
SOLVING A MULTI-OBJECTIVE REACTIVE POWER MARKET CLEARING MODEL USING NSGA-IIijait
This paper presents an application of elitist non-dominated sorting genetic algorithm (NSGA-II) for solving a multi-objective reactive power market clearing (MO-RPMC) model. In this MO-RPMC model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and voltage stability enhancement index (VSEI) are optimized
simultaneously while satisfying various system equality and inequality constraints in competitive electricity markets which forms a complex mixed integer nonlinear optimization problem with binary variables. The proposed NSGA-II based MO-RPMC model is tested on standard IEEE 24 bus reliability test system. The results obtained in NSGA-II based MO- RPMC model are also compared with the results obtained in real coded genetic algorithm (RCGA) based single-objective RPMC models.
Combination of Immune Genetic Particle Swarm Optimization algorithm with BP a...paperpublications3
Abstract:In this paper, merging Immune Genetic Particle Swarm Optimization algorithm (IGPSO) with BP algorithm to optimize BP Neural Network parameter i.e., BPIGPSO amalgamation to solve optimal reactive power dispatch algorithm. The basic perception is that first training BP neural network with IGPSO to find out a comparatively optimal solution, then take the network parameter at this time as the preliminary parameter of BP algorithm to carry out the training, finally searching the optimal solution. The proposed BPIGPSO has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
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has been examined and tested on the standard IEEE 30-bus, 57-bus and 118-bus test system [24]-[26]. The
prospective and effectiveness of the proposed approach is demonstrated and the results are compared with
those cited in the literature.
2. ORPD PROBLEM FORMULATION
In the present work the ORPD problem is formulated as a multi-objective optimization problem
which is listed below:
2.1. Minimization of real power loss
The objective of ORPD problem is minimization of real power loss while satisfying its various
equality and inequality constraints.
))]cos(2[( 22
1
1 jijiji
N
i
k VVVVgFMinimize
L
(1)
where NL represents the number of transmission lines, gk is the conductance of ith
transmission line, Vi and Vj
is the voltage magnitudes of ith
and jth
buses, i and j is the voltage phase angle of ith
and jth
buses. The state
variables for ORPD problem are,
1 1 1[ , ... , ... ]PQ G
T
G L LN G GNx P V V Q Q (2)
where PG1 denotes the slack bus power, VL denotes the load bus voltages, QG denote the reactive power
output of the generators, NG denotes the number of voltage controlled buses, NPQ denotes the number of load
buses. The control variables for ORPD problem are,
]...,...,...[ 111 TCG NCNCGNG
T
TTQQVVu (3)
where NT and NC denotes the number of tap changing transformers and shunt VAR compensators. VG
denotes the voltages of voltage controlled bus and T denotes the transformer tap ratio and QC denotes the
reactive power output of shunt VAR compensators.
2.2. Minimization of total voltage deviation
The minimization of voltage deviation improves the voltage profile of the system, thereby
enhancing the security and quality of the system. The objective function is given as,
2 | |
PQ
ref
i i
i N
Minimize F V V
(4)
where Vi
ref
is the reference value of ith
bus voltage magnitude which is usually 1.0p.u.
2.3. Enhancement of voltage stability
Voltage stability is the ability of the system to maintain its voltages within its permissible limits.
Voltage instability occurs only when a system is subjected to disturbances in the system. Voltage stability
can be improvised by minimizing the voltage stability indicator L-index at all buses. L-index is usually in the
range of 0 to 1 for all load buses. The L-index at a bus denotes the chances of the voltage collapse condition
of that bus. L-index Lj of the jth
bus is given as,
PVN
i j
i
jij
V
V
FL
1
1
Where j = 1,…, NPQ (5)
2
1
1 YYFji
(6)
where NPV denotes number of PV buses. Y1 and Y2 are the sub-matrices that are obtained after separating PQ
and PV bus parameters,
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1425
3.
1 2
3 4
PQ PQ
PV PV
I Y Y V
I Y Y V
(7)
L-index is calculated for all PQ buses. The L-index value can be described as,
)max(max jLL , where j = 1,..., NPQ (8)
A lower value of L denotes a stable system. In order to improve the voltage stability and to move the
system from voltage collapse point, the objective can be described as,
3 maxMinimize F L (9)
where Lmax is the maximum value of L-index.
2.4. Constraints
The objective functions are subject to both Equality and Inequality constraints as below:
2.4.1. Equality constraints
1
[ cos( ) sin( )] 0 1,2, ,
Nb
Gi Di i j ij i j ij i j
j
P P VV G B i Nb
(10)
1
[ sin( ) cos( )] 0 1,2, ,
Nb
Gi Di i j ij i j ij i j
j
Q Q VV G B i Nb
(11)
where NB is the number of buses, PGi and QGi are generated active and reactive power, PDi and QDi are active
and reactive power of load, Gij is the transfer conductance and Bij is the transfer susceptance between ith
and
jth
bus.
2.4.2. Generator constraints
Generator voltages and reactive power output have to be within its permissible limits described as
follows,
maxmin
GiGiGi VVV , i = 1,...,NG (12)
maxmin
GiGiGi QQQ , i=1,...,NG (13)
2.4.3. Transformer constraints
The transformer tap settings have to be within its lower and upper limits as follows,
maxmin
iii TTT ,
i=1,..., NT (14)
2.4.4. Shunt VAR compensator constraints
Shunt VAR compensators should be within its lower and upper limits as follows,
maxmin
CiCiCi QQQ
,
i=1,..., NC (15)
2.4.5. Security constraints
The load bus voltages and transmission line loadings have to be within its prescribed limits,
maxmin
LiLiLi VVV i = 1,...,NPQ (16)
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1426
maxmin
LiLi SS i=1,...,NL (17)
Thus the generalized objective function can be formulated as,
2min
1
max2lim
1
2lim
1
)()()( Li
NL
i
LiLGi
NG
i
GiQLi
NPQ
i
LiVobj SSQQVVFObjMin
(18)
where Fobj is the objective function, λV, λL and λQ are the penalty factors.
3. CROW SEARCH ALGORITHM
Crows or Corvids are intellectual omnivores; natural history books remain to be an evidence for it.
Crows have remarkable abilities like problem-solving skills, communication skills and adaptability. Crows
are known for its excellence in memory, certain vital researches show that crows don’t forget a face and
hence alerts other crows how to identify the individuals. Certain behavior of crows is enlisted [23],
a. Crows live in groups
b. Crows have excellent memory on their position of hidden places
c. Crows follows each other to perform acts of thievishness
d. Crows hide their collectives that have been theft
Crow Search Algorithm (CSA) is developed based on the above nature and behavior of crows. The
algorithm has d-dimensional environment with N number of crows and the position of crows ( k
iX ) which can
be specified by a vector,
],....,,[ ,2,1, dk
i
k
i
k
i
k
i XXXX (19)
where 1,2,...,i N ; max
1,2,...,k iter ; max
iter is the maximum number of iterations
In accordance with its memory capacity, the algorithm proceeds as, at kth
iteration, the position of
hiding place of ith
crow is given by, Mi
k
. For better illustration, assume that jth
crow wants to visit its hiding
place at kth
iteration, at this instant of iteration, ith
crow follows jth
crow to know its hidden place, here there
are two possibilities,
Possibility 1: The crow j being unaware of crow i, shows its hidden place, hence at this instant the new
position of crow i become,
)(1 iter
i
iter
i
iter
ii
iter
i
iter
i XMflrXX
(20)
where ri is a random number with uniform distribution between 0 and 1, fli
iter
denotes the flight length of
crow i at iteration iter. The value of fl has great impact on the search space of the algorithm, if fl is a smaller
value than it results in local search and if fl is a larger value it results in global search.
Possibility 2: The crow j aware of crow i that it is following it, in order, hence to protect its collect from crow
i, crow j will move to another position to divert crow j, then the new position is thus given by,
otherwisepositionrandoma
APrXMflrX
X
iter
jj
iter
i
iter
j
iter
ii
iter
iiter
i
)(1 (21)
where APj
iter
denotes the awareness probability of crow j at iteration iter. This factor decides whether the
search space is intensified or diversified. When AP is increased, the search space gets increased thereby,
results in global optimal and vice versa.
4. APPLICATION OF CROW SEARCH ALGORITHM FOR ORPD PROBLEM
The sequence of steps that ought to be followed in the implementation of the CSA is given in this
section.
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Step 1: Initialization of algorithm parameters and constraints
The algorithm parameters comprises of population size (N), maximum number of iterations (itermax
),
flight length (fl) and awareness probability (AP) and the constraints include power balance equality
constraints, line flow and voltage constraints.
Step 2: Initialization of the position and memory of crows
The N population of crows is randomly positioned in a d-dimensional search space. Each crow
denotes a possibility of feasible solution of the problem and d is the number of control variables which
includes generator voltages, transformer tap settings and reactive power output of shunt capacitor. The
memory of each crow is initialized. At the beginning of iteration iter, it is assumed that the crows have
hidden their foods at their initial positions.
Step 3: Evaluate fitness (objective) function
For each crow, the position is determined by fitting the control variable values into the objective
function (minimization of real power loss, total voltage deviation and voltage stability indicator).
Step 4: Generate new position
Crows finds a new position in the d-dimensional search space by as follows: suppose crow i wants
to find a new position. For this, the crow randomly selects one of the crows, let that be crow j and follows it
to discover the Position of collecting hidden by this crow (mj). The new position of crow i is given by
Equations (20) and (21).
Step 5: Check the feasibility of new positions
The viability of the new position of each crow thus obtained is checked and the position is updated
based on it. If the new position, thus obtained is not viable, then the crowd stays in the current position and
does not move to the new position found.
Step 6: Evaluate the fitness function of new positions
The fitness function i.e. objective function value for the new position of each crow is evaluated.
Step 7: Update memory
The crows update their memory as follows:
, 1 , 1 ,
, 1
,
( ) ( )i iter i iter i iter
i iter
i iter
x f x is better than f m
m
m otherwise
(22)
where fobj denotes the objective function value.
It is seen that if the fitness function value of the new position of a crow is better than the fitness
function value of the memorized position, the crow updates its memory by the new position.
Step 8: Check termination criterion
Steps 4 to 7 are repeated until maximum iteration is reached. When the termination criterion is met,
the best position of the memory in terms of the objective function value is reported as the solution of the
optimization problem.
5. RESULTS AND DISCUSSION
The present work is being tested on standard IEEE-30, 57 and 118 bus systems and the results are
obtained. The description of these studied test systems is depicted below. The software is written in
MATLAB R2015 computing environment. The various algorithm parameters are initialized and are set to be
as: The value of flock size (population) is set to 75, the awareness probability index determines whether the
search space is intensified or diversified and is set to 0.5, the flight length is assumed to be 2 and the
maximum number of iterations performed is set to 200 for all the test cases considered. The results of interest
are boldfaced in the respective tables to indicate the optimization capability of the proposed algorithm.
5.1. Case-1: Minimization real power loss
In this case, the proposed algorithm is executed considering the minimization of real power loss
alone as the objective function. The convergence characteristic of the algorithm considering the real power
loss is shown in Figure 1, which indicates fast and smooth convergence of CSA. The superiority of the
aforesaid CSA based approach for solving ORPD problem can be witnessed from the comparison made
between other optimization techniques from Table 1, Table 2 and Table 3. The best power loss obtained
using CSA for IEEE 30, 57 and 118 bus systems are 2.8507 MW, 15.1934 MW and 76.7783 MW
respectively, which is lesser than result reported in [12], [14], [19], [21].
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Table 1. Comparison of results for minimization of active power loss for IEEE-30 bus system
Methodology CSA CLPSO [14] GSA [21]
Power loss (MW) 2.8507 4.5615 4.5143
Table 2. Comparison of results for IEEE 57-bus system
Methodology CSA CLPSO [14] SOA [19] GSA [21]
Power loss (MW) 15.1934 24.5152 24.2654 23.4611
Table 3. Comparison of results for IEEE 118-bus system
Methodology CSA PSO [12] SOA [19] GSA [21]
Power loss (MW) 76.7783 131.99 114.9501 127.7603
Figure 1. Convergence characteristics considering the real power loss as objective
5.2. Case-2: Minimization of total voltage deviation
The proposed CSA approach is also applied for minimization of total voltage deviation of IEEE-30
bus test network and the result yielded from this approach is illustrated in Table 4 and are compared with
those reported in the literature. The minimum total voltage deviation obtained by the proposed method is
0.0907, which is lesser than results reported in [12], [14]. The convergence characteristic of voltage deviation
versus number of iterations is depicted in Figure 2.
Figure 2. Convergence characteristics considering voltage deviation as objective
Table 4. Comparisons of results for voltage profile improvement IEEE-30 bus system
Methodology CSA PSO [12] CLPSO [14]
Σ Voltage deviation (p.u) 0.0907 0.2450 0.2577
0 20 40 60 80 100 120 140 160 180 200
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
Iteration
PowerLoss(MW)
0 20 40 60 80 100 120 140 160 180 200
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Iteration
VoltageDeviation
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5.3. Case-3: Enhancement of voltage stability
In this case the enhancement of voltage Stability is taken as objective function. The solution
obtained by the proposed method and reported in literature by other methods is illustrated in Table 5. The
voltage stability indicator obtained by the CSA is 0.1180, which is lesser than results reported in [20], [21]
and which is proving the excellence of the aforesaid CSA algorithm over other optimization techniques. The
convergence characteristic of L-index versus number of iterations are depicted in Figure 3, which shows fast
and smooth convergence characteristics of CSA.
Table 5. Comparison of results for enhancement of voltage stability IEEE-30 bus system
Methodology CSA DE [20] GSA [21]
L-index (p.u) 0.1180 0.1246 0.1368
Figure 3. Convergence characteristics considering voltage stability indicator as objective
The optimal setting of the control variables for the IEEE-30 bus system is illustrated in Table 6. The
optimal control variable setting for IEEE-57 and IEEE-118 bus system for case-1 (minimization of real
power loss) is illustrated in Table 7 and Table 8 respectively.
Table 6. Control variable settings for IEEE-30 Bus System
Control variable Case-1 Case-2 Case-3
VG1 (p.u) 1.1000 1.0152 1.1000
VG2 (p.u) 1.0975 1.0006 1.0882
VG5 (p.u) 1.0796 1.0173 1.1000
VG8 (p.u) 1.0867 1.0027 1.0885
VG11 (p.u) 1.1000 1.0736 1.1000
VG13 (p.u) 1.1000 1.0172 1.1000
T6-9 1.0665 1.0961 1.0025
T6-10 0.9000 0.9000 0.9000
T4-12 0.9880 0.9972 0.9675
T28-27 0.9738 0.9692 0.9078
QC10 (MVAR) 5.0000 4.0381 5.0000
QC12 (MVAR) 5.0000 4.7556 5.0000
QC15 (MVAR) 5.0000 4.9998 4.3599
QC17 (MVAR) 5.0000 0.0006 4.9892
QC20 (MVAR) 4.0451 4.9979 4.8982
QC21 (MVAR) 5.0000 4.9785 0
QC23 (MVAR) 2.6117 5.0000 0
QC24 (MVAR) 5.0000 5.0000 0
QC29 (MVAR) 2.2796 2.8054 0
Power loss (MW) 2.8507 10.3406 9.0087
Σ Voltage
deviation
2.0447 0.0907 2.3063
L-index 0.1261 0.1489 0.1180
0 20 40 60 80 100 120 140 160 180 200
0.118
0.12
0.122
0.124
0.126
0.128
0.13
0.132
0.134
Iteration
Lindex
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Table 7. Optimal settings of control variables for IEEE 57-bus system
Table 8. Optimal settings of control variables for IEEE 118-bus system
Control
variables
Value
Control
variable
Value
Control
variables
Value
Control
variables
Value
Control
variables
Value
VG1 (p.u) 1.0238 VG34 (p.u) 1.0175 VG70 (p.u) 1.0259 VG103 (p.u) 1.0307 QC79 (MVAR) 39.3480
VG4 (p.u) 1.0380 VG36 (p.u) 1.0143 VG72 (p.u) 1.0332 VG104 (p.u) 1.0160 QC82 (MVAR) 31.2706
VG6 (p.u) 1.0287 VG40 (p.u) 1.0098 VG73 (p.u) 1.0250 VG105 (p.u) 1.0154 QC83 (MVAR) 8.6446
VG8 (p.u) 1.0764 VG42 (p.u) 1.0149 VG74 (p.u) 1.0146 VG107 (p.u) 1.0114 QC105 (MVAR) 0.6263
VG10 (p.u) 1.0946 VG46 (p.u) 1.0262 VG76 (p.u) 1.0121 VG110 (p.u) 1.0181 QC107 (MVAR) 26.8462
VG12 (p.u) 1.0247 VG49 (p.u) 1.0410 VG77 (p.u) 1.0314 VG111 (p.u) 1.0246 QC110 (MVAR) 13.4358
VG15 (p.u) 1.0207 VG54 (p.u) 1.0237 VG80 (p.u) 1.0452 VG112 (p.u) 1.0145 T5-8 1.0150
VG18 (p.u) 1.0239 VG55 (p.u) 1.0249 VG85 (p.u) 1.0564 VG113(p.u) 1.0322 T25-26 1.0500
VG19 (p.u) 1.0181 VG56 (p.u) 1.0234 VG87 (p.u) 1.0581 VG116 (p.u) 1.0299 T17-30 1.0354
VG24 (p.u) 1.0474 VG59 (p.u) 1.0413 VG89 (p.u) 1.0722 QC34 (MVAR) 6.8484 T37-38 1.0137
VG25 (p.u) 1.0765 VG61 (p.u) 1.0345 VG90 (p.u) 1.0479 QC44 (MVAR) 2.2374 T59-63 0.9791
VG26 (p.u) 1.1000 VG62 (p.u) 1.0327 VG91 (p.u) 1.0465 QC45 (MVAR) 23.4731 T61-64 0.9991
VG27 (p.u) 1.0345 VG65 (p.u) 1.0354 VG92 (p.u) 1.0550 QC46 (MVAR) 0 T65-66 0.9668
VG31 (p.u) 1.0221 VG66 (p.u) 1.0517 VG99 (p.u) 1.0368 QC48 (MVAR) 9.6476 T68-69 0.9380
VG32 (p.u) 1.0296 VG69 (p.u) 1.0546 VG100 (p.u) 1.0411 QC74 (MVAR) 11.7550 T80-81 0.9742
PL (MW) 76.7783
6. CONCLUSION
In this work, the CSA algorithm was proposed for solving optimal reactive power dispatch problem
and successfully implemented in IEEE 30, 57 and 118 bus systems. The results obtained from the CSA
approach were compared with those reported in recent literature and hence the CSA algorithm proves its
capability of solving ORPD more efficiently in terms of its search capability and robustness. The supremacy
of CSA over the other approaches was observed. In accordance with the results obtained, the CSA algorithm
has a simple structure and quick convergence characteristics and therefore can be used to solve ORPD in
large scale power systems and may be recommended as a very promising algorithm for solving complex
engineering optimization problems.
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Control
variables
Value
Control
variables
Value
Control
variables
Value
Control
variables
Value
Control
variables
Value
VG1 (p.u) 1.0468 VG13 (p.u) 1.0290 QC3 (MVAR) 13.8328 T11-41 0.9001 T11-43 0.9564
VG2 (p.u) 1.0457 T4-18 0.9964 T24-25 1.1000 T15-45 0.9634 T40-56 0.9874
VG3 (p.u) 1.0423 T4-18 0.9708 T24-25 0.9922 T14-46 0.9573 T39-57 0.9801
VG6 (p.u) 1.0550 T21-20 1.0018 T24-26 1.0281 T10-51 0.9667 T9-55 0.9987
VG8 (p.u) 1.0638 QC1 (MVAR) 9.0156 T7-29 0.9924 T13-49 0.9239
VG9 (p.u) 1.0346 QC2 (MVAR) 17.3349 T34-32 0.9705 Power loss (MW) 15.1934
9. Int J Elec & Comp Eng ISSN: 2088-8708
Optimal Reactive Power Dispatch using Crow Search Algorithm (Lakshmi M)
1431
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BIOGRAPHIES OF AUTHORS
Lakshmi M received her B.E Degree in Electrical and Electronics Engineering from Panimalar
Engineering College and M.E degree in Power System Engineering from St.Joseph’s College of
Engineering. Her research interests are power system optimization and flexible AC transmission
systems.
Ramesh Kumar A received his B.E degree in Electrical and Electronics Engineering from
Dr.Sivanthi Aditanar College of Engineering, M.E degree in Power System Engineering from
Annamalai University and Ph.D degree from Faculty of Electrical Engineering, Anna University. His
research interests are power system optimization, deregulated power system and flexible AC
transmission systems.