In the recent years, power quality has been a research area of exponential increasing interest du... more In the recent years, power quality has been a research area of exponential increasing interest due to the wide utilization of power electronic devices. A high level of power quality is required to ensure the proper and continuous operation of the sensitive equipments such as power electronic drives, computers and microprocessor-based controllers. This necessitates the detection and monitoring of power quality problems. This paper presents a simple algorithm to detect and classify various categories of nonstationary power quality problems. The algorithm takes the sampled 3-phase instantaneous voltages which are measured at the point of common coupling and computes RMS and DC values. Based on the calculated values and number of samples, the power quality problem is classified. This algorithm is implemented using MATLAB programming and is tested for various categories of power quality problems such as sag, swell, interruption; under voltage, over voltage, unbalance and DC offset.
In this paper Ant Colony Search Algorithm (ACSA) is used for optimal allocation and sizing of dis... more In this paper Ant Colony Search Algorithm (ACSA) is used for optimal allocation and sizing of distributed generation in distributed networks. The aim of this paper is to have optimal allocation and sizing of distributed generation to reduce the losses and improve voltages at each bus in distribution network. In this paper, the results of power losses and voltages at each bus using ACSA are compared with the results of Genetic Algorithm (GA). MATLAB software is used for optimal allocation and sizing of Distributed Generation (DG) by using ACSA. The ACSA and GA methods are implemented on IEEE 85 Bus system and it shows that the ACSA method is better than the GA method.
This paper presents a better methodology for the optimal location and sizing of Distributed Gener... more This paper presents a better methodology for the optimal location and sizing of Distributed Generators (DG's) in distribution networks. Depending on the operating characteristics and locations, Distributed generators could have significant affect on the voltage profile, network losses and fault level in a distribution system. Since it is necessary to maintain voltages within a specified limit, the problem of the sitting and sizing of the DG has taken top priority as they affect the voltages and operations of the distribution power system. The appropriate combination of Load flow algorithm with GA has achieved acceptable results.A 15 bus radial distribution test system is considered and voltage profile improvement and reduction in distribution network losses are obtained in this paper.
In most of the industries, induction motors play very important role and that is the reason they ... more In most of the industries, induction motors play very important role and that is the reason they are manufactured in large numbers. Maximum torque and efficiency is obtained by the speed control of induction motor. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, Artificial Intelligent controllers like ANN, Fuzzy controller, ANFIS, Fuzzy Neural Controller, expert system & genetic algorithm are widely used in the industry. But, the main problem with the conventional, fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. Recently the concept of hybrid controller has been grown. To overcome this problem, ANN, ANFIS and Fuzzy Neuro are proposed in this paper. The comparison of dynamic performance of induction motor is also investigated by using Conventional, Fuzzy, Neural, ANFIS and Fuzzy Neural controllers. Index Terms-Fuzzy Logic Controller (FLC), Fuzzy Neural Network (FNN), Neural Network (NNW), Adaptive Neuro-Fuzzy Inference System (ANFIS).
In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance ... more In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance and robustness. Maximum torque and efficiency is obtained by the speed control of induction motor. Using Artificial Intelligence (AI) techniques, particularly the neural networks, performance & operation of induction motor drives is improved. This paper presents dynamic simulation of induction motor drive using neuro controller. The integrated environment allows users to compare simulation results between conventional, Fuzzy and Neural network controller (NNW).The performance of fuzzy logic and artificial neural network based controller's are compared with that of the conventional proportional integral controller. The dynamic Modelling and Simulation of Induction motor is done using MATLAB/SIMULINK and the dynamic performance of induction motor drive has been analyzed for artificial intelligent controller.
In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance ... more In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance and robustness. Maximum torque and efficiency is obtained by the speed control of induction motor. Using Artificial Intelligence (AI) techniques, particularly the neural networks, performance & operation of induction motor drives is improved. This paper presents dynamic simulation of induction motor drive using neuro controller. The integrated environment allows users to compare simulation results between conventional, Fuzzy and Neural Network controller (NNW).The performance of fuzzy logic and artificial neural network based controller's are compared with that of the conventional proportional integral controller. The dynamic modeling and simulation of Induction motor is done using MATLAB/SIMULINK and the dynamic performance of induction motor drive has been analyzed for artificial intelligent controller.
Today's Power system is more complex and consequently it would lead to less security. To meet the... more Today's Power system is more complex and consequently it would lead to less security. To meet the demand and better security levels with existing transmission lines, the Flexible AC Transmission System (FACTS) devices are one of the alternates. In this paper a Newton Raphson(NR) algorithm was developed to find out the best operating point of a Static Var Compensator(SVC) for the enhancement of system security. The proposed algorithm minimizes the security index iteratively.
In this paper, reduced sensor switching control strategy has been proposed for shunt active power... more In this paper, reduced sensor switching control strategy has been proposed for shunt active power filter (APFs) in distribution systems. Conventional control strategies require ten feedback sensors and where as the proposed control strategy uses only five feedback sensors. This control strategy improves dynamic performance, harmonic suppression, load balancing, power factor correction and also reduces cost of voltage and current sensors. The advantage of using non-isolated zigzag transformer is to convert three-phase three-wire to three-phase four-wire for neutral current compensation. The shunt active power filter is modeled and simulated using MATLAB along with simpower system blockset (SPB) toolboxes and simulation results are presented to demonstrate the performance feeding threephase four-wire linear/nonlinear loads.
In the industrial sector especially in the field of electric drives & control, induction motors p... more In the industrial sector especially in the field of electric drives & control, induction motors play a vital role. Without proper controlling of the speed, it is virtually impossible to achieve the desired task for a specific application. Basically AC motors, such as Induction Motors are of Squirrel-Cage type. They are simple, reliable, low cost and virtually maintenance-free electrical drives. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, artificial intelligent based controllers are widely used in the industry like ANN, Fuzzy controller, ANFIS, expert system, genetic algorithm. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy controller is proposed in this paper. The comparison between Conventional PI, Fuzzy Controller and Adaptive neuro fuzzy controller based dynamic performance of induction motor drive has been presented. Adaptive Neuro Fuzzy based control of induction motor will prove to be more reliable than other control methods.
In the industrial sector especially in the field of electric drives & control, induction motors p... more In the industrial sector especially in the field of electric drives & control, induction motors play a vital role. Without proper controlling of the speed, it is virtually impossible to achieve the desired task for a specific application. Basically AC motors, such as Induction Motors are of Squirrel-Cage type. They are simple, reliable, low cost and virtually maintenance-free electrical drives. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, artificial intelligent based controllers are widely used in the industry like ANN, Fuzzy controller, ANFIS, expert system, genetic algorithm. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy controller is proposed in this paper. The comparison between Conventional PI, Fuzzy Controller and Adaptive neuro fuzzy controller based dynamic performance of induction motor drive has been presented. Adaptive Neuro Fuzzy based control of induction motor will prove to be more reliable than other control methods.
Optimization of Generator output tends to increase the supply capability of generators at differe... more Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switchable
With the improvement in the technology of Microprocessor and Power Electronics, Induction motor d... more With the improvement in the technology of Microprocessor and Power Electronics, Induction motor drives with digital control have become more popular. Artificial intelligent controller (AIC) could be the best candidate for Induction Motor control. Over the last two decades researchers have been working to apply AIC for induction motor drives. This is because that AIC possesses advantages as compared to the conventional PI, PID and their adaptive versions. The main advantages are that the designs of these controllers do not depend on accurate system mathematical model and their performances are robust. In recent years, scientists and researchers have acquired significant development on various sorts of control theories and methods. Among these control technologies, intelligent control methods, which are generally regarded as the aggregation of Fuzzy Logic Control, Neural Network Control , Genetic Algorithm, and Expert S ystem, have exhibited particular superiorities. The artificial neural network controller introduced to the system for keeping the motor speed to be constant when the load varies. The speed control scheme of vector controlle d induction motor drive involves decoupling of the speed and ref speed into torque and flux producing components. The performance of artificial neural network based controller's is compared with that of the conventional proportional integral controller. The dynamic modeling of Induction motor is done and the performance of the Induction motor drive has been analyzed for constant and variable loads. By using neuro controller the transient response of induction machine has been improved greatly and the dynamic response of the same has been made faster.
In lieu of the advances in power electronics and microprocessors, digitally controlled induction ... more In lieu of the advances in power electronics and microprocessors, digitally controlled induction motor drives have become increasingly popular. Artificial intelligent controller (AIC) could be the best candidate for Induction Motor control. Over the last two decades researchers have been working to apply AIC for induction motor drives. This is because that AIC possesses advantages as compared to the conventional PI, PID and their adaptive versions. The main advantages are that the designs of these controllers do not depend on accurate system mathematical model and their performances are robust. In recent years, scientists and researchers have acquired significant development on various sorts of control theories and methods. Among these control technologies, intelligent control methods, which are generally regarded as the aggregation of Fuzzy Logic Control, Neural Network Control, Genetic Algorithm, and Expert System, have exhibited particular superiorities. The fuzzy logic controller (FLC) method can be utilized in systems that have vagueness or uncertainty. In this paper, fuzzy logic controller (FLC) based induction motor drive is presented In order to prove the superiority of the proposed FLC, the simulation results for the proposed controller are also compared to those obtained by conventional and FLC controllers.
Distributed Generators (DGs) are now commonly used in distribution systems to reduce the power di... more Distributed Generators (DGs) are now commonly used in distribution systems to reduce the power disruption in the power system network. Due to the installation of DGs in the system, the total power loss can be reduced and voltage profile of the buses and reliability of the system can be improved. The significant process to decrease the total power loss and to improve the power quality of the system is to identify the optimal number of DGs and their suitable locations in the system. To accomplish the aforementioned process and to evaluate the amount of power to be generated, a new method is proposed using Particle Swarm Optimization. The proposed method is tested for IEEE 30 bus system, by connecting optimal number of DGs in the system. The results showed a considerable reduction in the total power loss in the system and improved voltage profiles of the buses and reliability indices.
The Distributed Generators (DGs) are connected in distribution system to reduce the power losses ... more The Distributed Generators (DGs) are connected in distribution system to reduce the power losses and to improve the reliability of the distribution system. The most important process to decrease the total power loss and to improve the reliability of the system is to identify the proper placement of DG units and also to find the amount of power to be generated by them. A hybrid technique is proposed which includes Particle Swarm Optimization (PSO) and Neural Network. By fixing DGs in suitable optimal locations and by generating power based on the load conditions, the total power loss in the system can be reduced and the system reliability can be improved. The proposed method is tested for different load conditions on IEEE 30 bus system, by connecting one DG, two DGs, three DGs and four DGs in the system. The results obtained show the improved voltage profiles and reliability indices like EENS and ECOST.
In the recent years, power quality has been a research area of exponential increasing interest du... more In the recent years, power quality has been a research area of exponential increasing interest due to the wide utilization of power electronic devices. A high level of power quality is required to ensure the proper and continuous operation of the sensitive equipments such as power electronic drives, computers and microprocessor-based controllers. This necessitates the detection and monitoring of power quality problems. This paper presents a simple algorithm to detect and classify various categories of nonstationary power quality problems. The algorithm takes the sampled 3-phase instantaneous voltages which are measured at the point of common coupling and computes RMS and DC values. Based on the calculated values and number of samples, the power quality problem is classified. This algorithm is implemented using MATLAB programming and is tested for various categories of power quality problems such as sag, swell, interruption; under voltage, over voltage, unbalance and DC offset.
In this paper Ant Colony Search Algorithm (ACSA) is used for optimal allocation and sizing of dis... more In this paper Ant Colony Search Algorithm (ACSA) is used for optimal allocation and sizing of distributed generation in distributed networks. The aim of this paper is to have optimal allocation and sizing of distributed generation to reduce the losses and improve voltages at each bus in distribution network. In this paper, the results of power losses and voltages at each bus using ACSA are compared with the results of Genetic Algorithm (GA). MATLAB software is used for optimal allocation and sizing of Distributed Generation (DG) by using ACSA. The ACSA and GA methods are implemented on IEEE 85 Bus system and it shows that the ACSA method is better than the GA method.
This paper presents a better methodology for the optimal location and sizing of Distributed Gener... more This paper presents a better methodology for the optimal location and sizing of Distributed Generators (DG's) in distribution networks. Depending on the operating characteristics and locations, Distributed generators could have significant affect on the voltage profile, network losses and fault level in a distribution system. Since it is necessary to maintain voltages within a specified limit, the problem of the sitting and sizing of the DG has taken top priority as they affect the voltages and operations of the distribution power system. The appropriate combination of Load flow algorithm with GA has achieved acceptable results.A 15 bus radial distribution test system is considered and voltage profile improvement and reduction in distribution network losses are obtained in this paper.
In most of the industries, induction motors play very important role and that is the reason they ... more In most of the industries, induction motors play very important role and that is the reason they are manufactured in large numbers. Maximum torque and efficiency is obtained by the speed control of induction motor. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, Artificial Intelligent controllers like ANN, Fuzzy controller, ANFIS, Fuzzy Neural Controller, expert system & genetic algorithm are widely used in the industry. But, the main problem with the conventional, fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. Recently the concept of hybrid controller has been grown. To overcome this problem, ANN, ANFIS and Fuzzy Neuro are proposed in this paper. The comparison of dynamic performance of induction motor is also investigated by using Conventional, Fuzzy, Neural, ANFIS and Fuzzy Neural controllers. Index Terms-Fuzzy Logic Controller (FLC), Fuzzy Neural Network (FNN), Neural Network (NNW), Adaptive Neuro-Fuzzy Inference System (ANFIS).
In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance ... more In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance and robustness. Maximum torque and efficiency is obtained by the speed control of induction motor. Using Artificial Intelligence (AI) techniques, particularly the neural networks, performance & operation of induction motor drives is improved. This paper presents dynamic simulation of induction motor drive using neuro controller. The integrated environment allows users to compare simulation results between conventional, Fuzzy and Neural network controller (NNW).The performance of fuzzy logic and artificial neural network based controller's are compared with that of the conventional proportional integral controller. The dynamic Modelling and Simulation of Induction motor is done using MATLAB/SIMULINK and the dynamic performance of induction motor drive has been analyzed for artificial intelligent controller.
In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance ... more In industries, more than 85 % of the motors are Induction Motors, because of the low maintenance and robustness. Maximum torque and efficiency is obtained by the speed control of induction motor. Using Artificial Intelligence (AI) techniques, particularly the neural networks, performance & operation of induction motor drives is improved. This paper presents dynamic simulation of induction motor drive using neuro controller. The integrated environment allows users to compare simulation results between conventional, Fuzzy and Neural Network controller (NNW).The performance of fuzzy logic and artificial neural network based controller's are compared with that of the conventional proportional integral controller. The dynamic modeling and simulation of Induction motor is done using MATLAB/SIMULINK and the dynamic performance of induction motor drive has been analyzed for artificial intelligent controller.
Today's Power system is more complex and consequently it would lead to less security. To meet the... more Today's Power system is more complex and consequently it would lead to less security. To meet the demand and better security levels with existing transmission lines, the Flexible AC Transmission System (FACTS) devices are one of the alternates. In this paper a Newton Raphson(NR) algorithm was developed to find out the best operating point of a Static Var Compensator(SVC) for the enhancement of system security. The proposed algorithm minimizes the security index iteratively.
In this paper, reduced sensor switching control strategy has been proposed for shunt active power... more In this paper, reduced sensor switching control strategy has been proposed for shunt active power filter (APFs) in distribution systems. Conventional control strategies require ten feedback sensors and where as the proposed control strategy uses only five feedback sensors. This control strategy improves dynamic performance, harmonic suppression, load balancing, power factor correction and also reduces cost of voltage and current sensors. The advantage of using non-isolated zigzag transformer is to convert three-phase three-wire to three-phase four-wire for neutral current compensation. The shunt active power filter is modeled and simulated using MATLAB along with simpower system blockset (SPB) toolboxes and simulation results are presented to demonstrate the performance feeding threephase four-wire linear/nonlinear loads.
In the industrial sector especially in the field of electric drives & control, induction motors p... more In the industrial sector especially in the field of electric drives & control, induction motors play a vital role. Without proper controlling of the speed, it is virtually impossible to achieve the desired task for a specific application. Basically AC motors, such as Induction Motors are of Squirrel-Cage type. They are simple, reliable, low cost and virtually maintenance-free electrical drives. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, artificial intelligent based controllers are widely used in the industry like ANN, Fuzzy controller, ANFIS, expert system, genetic algorithm. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy controller is proposed in this paper. The comparison between Conventional PI, Fuzzy Controller and Adaptive neuro fuzzy controller based dynamic performance of induction motor drive has been presented. Adaptive Neuro Fuzzy based control of induction motor will prove to be more reliable than other control methods.
In the industrial sector especially in the field of electric drives & control, induction motors p... more In the industrial sector especially in the field of electric drives & control, induction motors play a vital role. Without proper controlling of the speed, it is virtually impossible to achieve the desired task for a specific application. Basically AC motors, such as Induction Motors are of Squirrel-Cage type. They are simple, reliable, low cost and virtually maintenance-free electrical drives. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, artificial intelligent based controllers are widely used in the industry like ANN, Fuzzy controller, ANFIS, expert system, genetic algorithm. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy controller is proposed in this paper. The comparison between Conventional PI, Fuzzy Controller and Adaptive neuro fuzzy controller based dynamic performance of induction motor drive has been presented. Adaptive Neuro Fuzzy based control of induction motor will prove to be more reliable than other control methods.
Optimization of Generator output tends to increase the supply capability of generators at differe... more Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switchable
With the improvement in the technology of Microprocessor and Power Electronics, Induction motor d... more With the improvement in the technology of Microprocessor and Power Electronics, Induction motor drives with digital control have become more popular. Artificial intelligent controller (AIC) could be the best candidate for Induction Motor control. Over the last two decades researchers have been working to apply AIC for induction motor drives. This is because that AIC possesses advantages as compared to the conventional PI, PID and their adaptive versions. The main advantages are that the designs of these controllers do not depend on accurate system mathematical model and their performances are robust. In recent years, scientists and researchers have acquired significant development on various sorts of control theories and methods. Among these control technologies, intelligent control methods, which are generally regarded as the aggregation of Fuzzy Logic Control, Neural Network Control , Genetic Algorithm, and Expert S ystem, have exhibited particular superiorities. The artificial neural network controller introduced to the system for keeping the motor speed to be constant when the load varies. The speed control scheme of vector controlle d induction motor drive involves decoupling of the speed and ref speed into torque and flux producing components. The performance of artificial neural network based controller's is compared with that of the conventional proportional integral controller. The dynamic modeling of Induction motor is done and the performance of the Induction motor drive has been analyzed for constant and variable loads. By using neuro controller the transient response of induction machine has been improved greatly and the dynamic response of the same has been made faster.
In lieu of the advances in power electronics and microprocessors, digitally controlled induction ... more In lieu of the advances in power electronics and microprocessors, digitally controlled induction motor drives have become increasingly popular. Artificial intelligent controller (AIC) could be the best candidate for Induction Motor control. Over the last two decades researchers have been working to apply AIC for induction motor drives. This is because that AIC possesses advantages as compared to the conventional PI, PID and their adaptive versions. The main advantages are that the designs of these controllers do not depend on accurate system mathematical model and their performances are robust. In recent years, scientists and researchers have acquired significant development on various sorts of control theories and methods. Among these control technologies, intelligent control methods, which are generally regarded as the aggregation of Fuzzy Logic Control, Neural Network Control, Genetic Algorithm, and Expert System, have exhibited particular superiorities. The fuzzy logic controller (FLC) method can be utilized in systems that have vagueness or uncertainty. In this paper, fuzzy logic controller (FLC) based induction motor drive is presented In order to prove the superiority of the proposed FLC, the simulation results for the proposed controller are also compared to those obtained by conventional and FLC controllers.
Distributed Generators (DGs) are now commonly used in distribution systems to reduce the power di... more Distributed Generators (DGs) are now commonly used in distribution systems to reduce the power disruption in the power system network. Due to the installation of DGs in the system, the total power loss can be reduced and voltage profile of the buses and reliability of the system can be improved. The significant process to decrease the total power loss and to improve the power quality of the system is to identify the optimal number of DGs and their suitable locations in the system. To accomplish the aforementioned process and to evaluate the amount of power to be generated, a new method is proposed using Particle Swarm Optimization. The proposed method is tested for IEEE 30 bus system, by connecting optimal number of DGs in the system. The results showed a considerable reduction in the total power loss in the system and improved voltage profiles of the buses and reliability indices.
The Distributed Generators (DGs) are connected in distribution system to reduce the power losses ... more The Distributed Generators (DGs) are connected in distribution system to reduce the power losses and to improve the reliability of the distribution system. The most important process to decrease the total power loss and to improve the reliability of the system is to identify the proper placement of DG units and also to find the amount of power to be generated by them. A hybrid technique is proposed which includes Particle Swarm Optimization (PSO) and Neural Network. By fixing DGs in suitable optimal locations and by generating power based on the load conditions, the total power loss in the system can be reduced and the system reliability can be improved. The proposed method is tested for different load conditions on IEEE 30 bus system, by connecting one DG, two DGs, three DGs and four DGs in the system. The results obtained show the improved voltage profiles and reliability indices like EENS and ECOST.
This paper presents a contingency analysis study of Embedded Generation (EG) deployment in distri... more This paper presents a contingency analysis study of Embedded Generation (EG) deployment in distribution network.
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