In this paper, A novel modified optimization method was used to find the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired results were analyzed and compared to other recent optimization methods applied to the same test feeders to ensure the effectiveness of the used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique found the most minimized total power loss in system, the best improved voltage profile and most reduction in costs due power loss compared to other methods.
Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.
Network Reconfiguration in Distribution Systems Using Harmony Search AlgorithmIOSRJEEE
This manuscript explores feeder reconfiguration in distribution networks and presents an efficient method to optimize the radial distribution system by means of simultaneous reconfiguration. Network Reconfiguration of radial distribution system is a significant way of altering the power flow through the lines. This assessment presents a modern method to solve the network reconfiguration problem with an objective of minimizing real power loss and improving the voltage profile in radial distribution system (RDS). A precise and load flow algorithm is applied and the objective function is formulated to solve the problem which includes power loss minimization. HSA Algorithm is utilized to restructure and identify the optimal strap switches for minimization of real power loss in a distribution network.. The strategy has been tested on IEEE 33-bus and 69- bus systems to show the accomplishment and the adequacy of the proposed technique. The results demonstrate that a significant reduction in real power losses and improvement of voltage profiles.
Network Reconfiguration of Distribution System for Loss Reduction Using GWO A...IJECEIAES
This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfiguration problem which includes minimization of real power loss. A nature inspired Grey Wolf Optimization Algorithm is utilized to restructure the power distribution system and identify the optimal switches corresponding minimum power loss in the distribution network. The GWO technique has tested on standard IEEE 33-bus and 69-bus systems and the results are presented.
Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.
Network Reconfiguration in Distribution Systems Using Harmony Search AlgorithmIOSRJEEE
This manuscript explores feeder reconfiguration in distribution networks and presents an efficient method to optimize the radial distribution system by means of simultaneous reconfiguration. Network Reconfiguration of radial distribution system is a significant way of altering the power flow through the lines. This assessment presents a modern method to solve the network reconfiguration problem with an objective of minimizing real power loss and improving the voltage profile in radial distribution system (RDS). A precise and load flow algorithm is applied and the objective function is formulated to solve the problem which includes power loss minimization. HSA Algorithm is utilized to restructure and identify the optimal strap switches for minimization of real power loss in a distribution network.. The strategy has been tested on IEEE 33-bus and 69- bus systems to show the accomplishment and the adequacy of the proposed technique. The results demonstrate that a significant reduction in real power losses and improvement of voltage profiles.
Network Reconfiguration of Distribution System for Loss Reduction Using GWO A...IJECEIAES
This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfiguration problem which includes minimization of real power loss. A nature inspired Grey Wolf Optimization Algorithm is utilized to restructure the power distribution system and identify the optimal switches corresponding minimum power loss in the distribution network. The GWO technique has tested on standard IEEE 33-bus and 69-bus systems and the results are presented.
Robust Evolutionary Approach to Mitigate Low Frequency Oscillation in a Multi...IDES Editor
This paper proposes a new optimization algorithm
known as Modified Shuffled Frog Leaping Algorithm (MSFLA)
for optimal designing of PSSs controller. The design problem
of the proposed controller is formulated as an optimization
problem and MSFLA is employed to search for optimal
controller parameters. An eigenvalue based objective function
reflecting the combination of damping factor and damping
ratio is optimized for different operating conditions. The
proposed approach is applied to optimal design of multimachine
power system stabilizers. Three different power
systems, A Single Machine Infinite Bus (SMIB), four-machine
of Kundur and ten-machine New England systems are
considered. The obtained results are evaluated and compared
with other results obtained by Genetic Algorithm (GA).
Eigenvalue analysis and nonlinear system simulations assure
the effectiveness and robustness of the proposed controller in
providing good damping characteristic to system oscillations
and enhancing the system dynamic stability under different
operating conditions and disturbances.
Optimal Siting of Distributed Generators in a Distribution Network using Arti...IJECEIAES
Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
Estimation of Weekly Reference Evapotranspiration using Linear Regression and...IDES Editor
The study investigates the applicability of linear
regression and ANN models for estimating weekly reference
evapotranspiration (ET0) at Tirupati, Nellore, Rajahmundry,
Anakapalli and Rajendranagar regions of Andhra Pradesh.
The climatic parameters influencing ET0 were identified
through multiple and partial correlation analysis. The
sunshine, temperature, wind velocity and relative humidity
mostly influenced the study area in the weekly ET0 estimation.
Linear regression models in terms of the climatic parameters
influencing the regions and, optimal neural network
architectures considering these climatic parameters as inputs
were developed. The models’ performance was evaluated with
respect to ET0 estimated by FAO-56 Penman-Monteith method.
The linear regression models showed a satisfactory
performance in the weekly ET0 estimation in the regions
selected for the present study. The ANN (4,4,1) models,
however, consistently showed a slightly improved performance
over linear regression models.
Optimal planning of RDGs in electrical distribution networks using hybrid SAP...IJECEIAES
The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA and PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA and PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
Harmonic enhancement in microgrid with applications on sensitive loadsIJECEIAES
Power quality issues are an important and growing problem in microgrid. There are two reasons; the more active consumer is participating in the power sector, the use of renewable energy which having a great impact on voltage variation. This paper discusses power quality disturbance and especially harmonic distortion issues in microgrid, and suggests a solution to maintain the operation of the distribution system within power quality standard. To protect sensitive loads from harmonics produced by the grid and by renewable energy sources, passive harmonic filter has been proposed in this paper. The electrical system of a nuclear research reactor as sensitive loads is designed by using Electrical Transient Analyzer Program (ETAP) software. The results show these technical issues are presented with their influence on electrical voltage and harmonic specter.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
This paper presents the design and analysis of a relatively new wireless power transfer technique using capacitive coupling, named Capacitive power transfer (CPT). In general, CPT system has been introduced as an attractive alternative to the former inductive coupling method. This is because CPT uses lesser number of components, simpler topology, enhanced EMI performance and better strength to surrounding metallic elements. In this work, aluminium sheet is used as a capacitive coupling at transmitter and receiver side. Moreover, a Class-E resonant inverter together with π1a impedance matching network has been proposed because of its ability to perform the dc-to-ac inversion well. It helps the CPT system to achieve maximum power transfer. The CPT system is designed and simulated by using MATLAB/Simulink software. The validity of the proposed concept is then verified by conducting a laboratory experimental of CPT system. The proposed system able to generate a 9.5W output power through a combined interface capacitance of 2.44nF, at an operating frequency of 1MHz, with 95.10% efficiency. The proposed CPT system with impedance matching network also allows load variation in the range of 20% from its nominal value while maintaining the efficiency over 90%.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
Performance comparison of distributed generation installation arrangement in ...journalBEEI
Placing Distributed Generation (DG) into a power network should be planned wisely. In this paper, the comparison of having different installation arrangement of real-power DGs in transmission system for loss control is presented. Immune-brainstorm-evolutionary programme (IBSEP) was chosen as the optimization technique. It is found that optimizing fixed-size DGs locations gives the highest loss reduction percentage. Apart from that, scattered small-sized DGs throughout a network minimizes transmission loss more than allocating one biger-sized DG at a location.
Robust Evolutionary Approach to Mitigate Low Frequency Oscillation in a Multi...IDES Editor
This paper proposes a new optimization algorithm
known as Modified Shuffled Frog Leaping Algorithm (MSFLA)
for optimal designing of PSSs controller. The design problem
of the proposed controller is formulated as an optimization
problem and MSFLA is employed to search for optimal
controller parameters. An eigenvalue based objective function
reflecting the combination of damping factor and damping
ratio is optimized for different operating conditions. The
proposed approach is applied to optimal design of multimachine
power system stabilizers. Three different power
systems, A Single Machine Infinite Bus (SMIB), four-machine
of Kundur and ten-machine New England systems are
considered. The obtained results are evaluated and compared
with other results obtained by Genetic Algorithm (GA).
Eigenvalue analysis and nonlinear system simulations assure
the effectiveness and robustness of the proposed controller in
providing good damping characteristic to system oscillations
and enhancing the system dynamic stability under different
operating conditions and disturbances.
Optimal Siting of Distributed Generators in a Distribution Network using Arti...IJECEIAES
Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
Estimation of Weekly Reference Evapotranspiration using Linear Regression and...IDES Editor
The study investigates the applicability of linear
regression and ANN models for estimating weekly reference
evapotranspiration (ET0) at Tirupati, Nellore, Rajahmundry,
Anakapalli and Rajendranagar regions of Andhra Pradesh.
The climatic parameters influencing ET0 were identified
through multiple and partial correlation analysis. The
sunshine, temperature, wind velocity and relative humidity
mostly influenced the study area in the weekly ET0 estimation.
Linear regression models in terms of the climatic parameters
influencing the regions and, optimal neural network
architectures considering these climatic parameters as inputs
were developed. The models’ performance was evaluated with
respect to ET0 estimated by FAO-56 Penman-Monteith method.
The linear regression models showed a satisfactory
performance in the weekly ET0 estimation in the regions
selected for the present study. The ANN (4,4,1) models,
however, consistently showed a slightly improved performance
over linear regression models.
Optimal planning of RDGs in electrical distribution networks using hybrid SAP...IJECEIAES
The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA and PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA and PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
Harmonic enhancement in microgrid with applications on sensitive loadsIJECEIAES
Power quality issues are an important and growing problem in microgrid. There are two reasons; the more active consumer is participating in the power sector, the use of renewable energy which having a great impact on voltage variation. This paper discusses power quality disturbance and especially harmonic distortion issues in microgrid, and suggests a solution to maintain the operation of the distribution system within power quality standard. To protect sensitive loads from harmonics produced by the grid and by renewable energy sources, passive harmonic filter has been proposed in this paper. The electrical system of a nuclear research reactor as sensitive loads is designed by using Electrical Transient Analyzer Program (ETAP) software. The results show these technical issues are presented with their influence on electrical voltage and harmonic specter.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
This paper presents the design and analysis of a relatively new wireless power transfer technique using capacitive coupling, named Capacitive power transfer (CPT). In general, CPT system has been introduced as an attractive alternative to the former inductive coupling method. This is because CPT uses lesser number of components, simpler topology, enhanced EMI performance and better strength to surrounding metallic elements. In this work, aluminium sheet is used as a capacitive coupling at transmitter and receiver side. Moreover, a Class-E resonant inverter together with π1a impedance matching network has been proposed because of its ability to perform the dc-to-ac inversion well. It helps the CPT system to achieve maximum power transfer. The CPT system is designed and simulated by using MATLAB/Simulink software. The validity of the proposed concept is then verified by conducting a laboratory experimental of CPT system. The proposed system able to generate a 9.5W output power through a combined interface capacitance of 2.44nF, at an operating frequency of 1MHz, with 95.10% efficiency. The proposed CPT system with impedance matching network also allows load variation in the range of 20% from its nominal value while maintaining the efficiency over 90%.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
Performance comparison of distributed generation installation arrangement in ...journalBEEI
Placing Distributed Generation (DG) into a power network should be planned wisely. In this paper, the comparison of having different installation arrangement of real-power DGs in transmission system for loss control is presented. Immune-brainstorm-evolutionary programme (IBSEP) was chosen as the optimization technique. It is found that optimizing fixed-size DGs locations gives the highest loss reduction percentage. Apart from that, scattered small-sized DGs throughout a network minimizes transmission loss more than allocating one biger-sized DG at a location.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
Machine learning for prediction models to mitigate the voltage deviation in ...IJECEIAES
The voltage deviation is one of the most crucial power quality issues that occur in electrical power systems. Renewable energy plays a vital role in electrical distribution networks due to the high economic returns. However, the presence of photovoltaic systems changes the nature of the energy flow in the grid and causes many problems such as voltage deviation. In this work, several predictive models are examined for voltage regulation in the Jordanian Sabha distribution network equipped with photovoltaic farms. The augmented grey wolf optimizer is used to train the different predictive models. To evaluate the performance of models, a value of one for regression factor and a low value for root mean square error, mean square error, and mean absolute error are used as standards. In addition, a comparison between nineteen predictive models has been made. The results have proved the capability of linear regression and the gaussian process to restore the bus voltages in the distribution network accurately and quickly and to solve the shortening in the voltage dynamic response caused by the iterative nature of the heuristic algorithm.
Simultaneous network reconfiguration and capacitor allocations using a novel ...IJECEIAES
Power loss and voltage magnitude fluctuations are two major issues in distribution networks that have drawn a lot of attention. Combining two of the numerous strategies for solving these problems and dealing with them simultaneously to get more effective outcomes is essential. Therefore, this study hybridizes the network reconfiguration and capacitor allocation strategies, proposing a novel dingo optimization algorithm (DOA) to solve the optimization problems. The optimization problems for simultaneous network reconfiguration and capacitor allocations were formulated and solved using a novel DOA. To demonstrate its effectiveness, DOA’s results were contrasted with those of the other optimization techniques. The methodology was validated on the IEEE 33-bus network and implemented in the MATLAB program. The results demonstrated that the best network reconfiguration was accomplished with switches 7, 11, 17, 27, and 34 open, and buses 8, 29, and 30 were the best places for capacitors with ideal sizes of 512, 714, and 495 kVAr, respectively. The network voltage profile was significantly improved as the least voltage at bus 18 was increased to 0.9530 p.u. Furthermore, the overall real power loss was significantly mitigated by 48.87%, which, when compared to the results of other methods, was superior.
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.
Convergence Parameter Analysis for Different Metaheuristic Methods Control Co...IJPEDS-IAES
This paper is an extension of our previous work, which discussed the
difficulty in implementing different methods of resistance emulation
techniques on the hardware due to its control constant estimation delay. In
order to get rid of the delay this paper attempts to include the meta-heuristic
methods for the control constants of the controller. To achieve the minimum
Total Harmonic Disturbance (THD) in the AC side of the converter modern
meta-heuristic methods are compared with the traditional methods. The
convergence parameters, which are primary for the earlier estimation of the
control constants, are compared with the measured parameters, tabulated and
tradeoff inference is done among the methods. This kind of implementation
does not need the mathematical model of the system under study for finding
the control constants. The parameters considered for estimation are
population size, maximum number of epochs, and global best solution of the
control constants, best THD value and execution time. MatlabTM /Simulink
based simulation is optimized with the M-file based optimization techniques
like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo
Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm
and Bat Algorithm.
Multi-objective distributed generation integration in radial distribution sy...IJECEIAES
This paper introduces a new approach based on a chaotic strategy and a neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in the radial distribution system (RDS). This consists of determining the optimal locations and sizes of one or several distributed generations (DGs) to be inserted into the RDS to minimize one or multiple objectives while meeting a set of security limits. The robustness of the proposed method is demonstrated by applying it to two different typical RDSs, namely IEEE 33bus and 69-bus. In this regard, simulations are performed for three DGs in the cases of unity power factor (UPF) and optimal power factor (OPF), considering single and multi-objective optimization, by minimizing the total active losses and improving the voltage profile, voltage deviation (VD) and voltage stability index (VSI). Compared to its original version and recently reported methods, the CNNA solutions are more competitive without increasing the complexity of the optimization algorithm, especially when the RDS size and problem dimension are extended.
Fuzzy expert system based optimal capacitor allocation in distribution system-2IAEME Publication
One of the most popular image denoising methods based on self-similarity is called nonlocal
means (NLM). Though it can achieve remarkable performance, this method has a few shortcomings,
e.g., the computationally expensive calculation of the similarity measure, and the lack of reliable
candidates for some non repetitive patches. In this paper, we propose to improve NLM by integrating
Gaussian blur, clustering, and row image weighted averaging into the NLM framework.
Experimental results show that the proposed technique can perform denoising better than the original
NLM both quantitatively and visually, especially when the noise level is high.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
Optimal Reactive Power Scheduling Using Cuckoo Search AlgorithmIJECEIAES
The article describes multidisciplinary design process of high-performance electric generator for advanced aircrafts by analytical methods and computer modeling techniques (electromagnetic, thermal and mechanical calculations). New technical solutions used in its development are described. The main ideas are revealed of the method of EG voltage stabilization we used. To improve the heat dissipation efficiency, we have developed a new cooling system, and provide its study and description in this paper. The advantages of this cooling system include the fact that EG is made with dry, uncooled rotor. This allowed eliminating additional pumps, and significantly reducing tThis paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.he size of CSD. According to the results of our study, we created an experimental full capacity layout, and its studies are also provided in this paper.
Optimized placement of multiple FACTS devices using PSO and CSA algorithms IJECEIAES
This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.
Congestion Management using Optimal Choice and Allocation of FACTS Controllersidescitation
This paper concerns the optimal choice and
allocation of FACTS (Flexible AC Transmission Systems)
devices in multi-machine power system using genetic
algorithm. The objective is to improve the system loadability
and the voltage stability. Using the proposed method, the
locations of the FACTS devices, their types and rated values
are optimized simultaneously. Different kinds of FACTS
devices are simulated in this study: Thyristor Controlled
Series Compensator (TCSC) and Static Var Compensator
(SVC). The proposed algorithm is an effective and practical
method for the choice and allocation of FACTS devices in
large power systems.
This paper deals with various power issues such as voltage sag, swell, harmonics, and surges using static synchronous compensator (STATCOM).The conventional controller suffers from uncertain parameters and non-linear qualities. However they are computationally inefficient extending to optimize the fuzzy controller (FC) parameters, since they exhaustively search the optimal values to optimize the objective functions. To overcome this drawback, a genetic algorithm (GA) based Fuzzy controller parameter optimization is presented in this paper. The GA algorithm is used to find the optimal fuzzy parameters for minimizing the objective functions. The feasibility of the proposed GA technique for distribution systems to improve the sag and total harmonic distortion (THD) as major power quality indices in sensitive loads at fault conditions has been simulated and tested. Therefore, the multi-objective optimization algorithm is considered in order to attain a better performance in solving the related problems.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
Optimal Location of Multi-types of FACTS Devices using Genetic Algorithm IJORCS
The problem of improving the voltage profile and reducing power loss in electrical networks is a task that must be solved in an optimal manner. Therefore, placement of FACTS devices in suitable location can lead to control in-line flow and maintain bus voltages in desired level and reducing losses is required. This paper presents one of the heuristic methods i.e. a Genetic Algorithm to seek the optimal location of FACTS devices in a power system. Proposed algorithm is tested on IEEE 30 bus power system for optimal location of multi-type FACTS devices and results are presented.
Identification study of solar cell/module using recent optimization techniquesIJECEIAES
This paper proposes the application of a novel metaphor-free population optimization based on the mathematics of the Runge Kutta method (RUN) for parameter extraction of a double-diode model of the unknown solar cell and photovoltaic (PV) module parameters. The RUN optimizer is employed to determine the seven unknown parameters of the two-diode model. Fitting the experimental data is the main objective of the extracted unknown parameters to develop a generic PV model. Consequently, the root means squared error (RMSE) between the measured and estimated data is considered as the primary objective function. The suggested objective function achieves the closeness degree between the estimated and experimental data. For getting the generic model, applications of the proposed RUN are carried out on two different commercial PV cells. To assess the proposed algorithm, a comprehensive comparison study is employed and compared with several well-matured optimization algorithms reported in the literature. Numerical simulations prove the high precision and fast response of the proposed RUN algorithm for solving multiple PV models. Added to that, the RUN can be considered as a good alternative optimization method for solving power systems optimization problems.
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
Similar to Enhancing radial distribution system performance by optimal placement of DSTATCOM (20)
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.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
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.
2. Int J Elec & Comp Eng ISSN: 2088-8708
Enhancing radial distribution system performance by optimal placement of DSTATCOM (S. F. Mekhamer)
2851
(DSTATCOM) has many features, such as less harmonic production, low power losses, low cost, high
regulatory capability and compact size [5, 6].
Naseer M., et al., [7] proposes the use of genetic algorithm to find the appropriate size and location
of STATCOM in a power system considering the power factor correction limits. The proposed method is
applied to IEEE 5 bus, IEEE 30 bus test systems and Iraqi national grid to show the results. However,
the proposed technique needs to be applied to larger test radial systems to ensure its effectiveness. Also,
the voltage profile status after placement of the statcom in IEEE 30 bus and Iraqi national grid is not shown.
Yuvaraja, et al., [8] discusses the use of harmony search algorithm for the optimal sizing and location of
DSTATCOM in RDS. The method is tested only on IEEE 33 bus to ensure its effectiveness and the demerit
in this study that it only used one test radial distribution system and the voltage profile was not optimally
improved when compared to other optimization techniques applied to the same test feeder as in.
Taher, et al., [9] presents a biological inspired algorithm called Immune Algorithm which is used to
optimally allocate the DSTATCOM in the radial distribution feeder. The proposed technique is tested on two
test systems IEEE 33 bus and IEEE 69 bus. The results were promising but in the case of testing IEEE 33 bus
radial distribution feeder when compared to the results obtained using the harmony search algorithm
technique in [8] are better regarding the total power loss reduction of the RDS and the total annual costs.
Guptaa, et al., [10] uses sensitive method to determine the best locations for placing
the DSTATCOM in the tested IEEE 33 bus radial distribution feeder. After selecting one of the two sensitive
methods proposed in this study, the variational technique is used in order to select the proper size of
the DSTATCOM. The disadvantage in this work that it only tested the technique on single RDS and also
regarding the tested IEEE 33 bus RDS total annual energy saving obtained by other methods as in [9] is
better than the one reached in this work.
Yuvaraj, et al., [11] introduces the bat algoritm which is used to find the optimal size of
DSTATCOM to be placed in RDS and the placement of the sized DSTATCOM is decided by voltage
stability index method. To valiade the proposed technique for optimal location and sizing of DSTATCOM.
It is tested using two test systems IEEE 33 bus and IEEE 69 bus radial distribution systems.The obtained
results for the tested IEEE 33 bus RDS show that the size of the installed DSTATCOM is larger than the size
used by other optimization methods applied to the same test feeder. Shah, et al., [12] presents the effect of
optimal placement of STATCOM for voltage stability purposes by using load sensitivity factors. By varying
the loads on each load bus, the effect of STATCOM is realized. The implementation is done on two test RDS
systems IEEE 5 bus and IEEE 14 bus. But the status of active and reactive power losses is not presented and
also the implementation should have included larger test feeders.
In this paper, the improved grey wolf optimization algorithm is applied to two different IEEE radial
distribution feeders. This proposed technique is intended to find the optimal solutions to allocate and size
DSTATCOM in any RDS. The algorithm follows a set of predetermined steps to find the global optimal
solution for those kind optimization problems. The novelity factor in this study that the proposed technique is
used for the first time to find a solution for this kind of optimization problems which includes determining
the optimal location and size of DSTATCOM in any radial distribution feeder. This new algorithm could find
the optimal solution regarding the lowest system minimum power losses accompanied by voltage profile
improvement within the predefined optimiztion problem limits such as power balance constraints,
bus voltage constraints and reactive power compenstation constraints. The rest of the paper is divided as
follows: Section 2 (Research method) introduces the grey wolf optimization algorithm and its modifications.
Also, the algorithm steps taken to approach and solve the problem of optimal placement of DTATCOM in
RDS are explained. Section 3 (Results and Analysis) introduces the implementation and simulation results
applied to two test systems. Also, comparison of the results to other optimization techniques applied to
the same test feeders. Finally, Section 4 includes the conclusions of this study.
2. RESEARCH METHOD
2.1. Grey wolf optimization algorithm (GWOA)
GWOA is nature inspired algorithm that mimcs the behavior of the real grey wolves in nature by
applying their techniques in searching, leadership and hunting the preys. The algorithm was introduced for
the first time in [13]. From the study in [13-17]. Grey wolves are predators, in other words they are at
the peak of the food chain. It is recorded that they live in a group. In most cases the group contains 5-12
individuals. GWO technique is a meta-heuristic algorithm which belongs to the swarm intelligence family.
In the hunting process grey wolves divide themselves into packs. Figure 1 classifies them according to
domination and power. There are four categories of grey wolves. The first one is leaders, which are called
alpha (a) wolves and they are the most powerful and lead the whole pack in feeding, migration and hunting.
The second levels are the beta (b) wolves; they help the leaders in decision making and replace the alpha
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 3, June 2020 : 2850 - 2860
2852
wolves in case of death or illness. The least types of grey wolves are delta (d) and omega (x) wolves.
Interestingly, the alpha is not necessarily the strongest member of the pack but thebest in terms of managing
the pack. Gery wolves during the hunting process follow a set of well-known procedures: chasing, encircling,
harassing and attacking. This makes them hunt large preys. GWO algorithm applies the same mechanism in
nature, where it follows the pack hierarchy for organizing the different functions in the wolves’ pack. Also,
as in nature in the hunting process each wolf performs its role where the GWO pack’s members are divided
into four groups based on the category of the wolf’s function. The four groups are alpha, beta, delta and
omega, where the Alpha represents the best candidate solution found for hunting so far. Consequently, beta
and delta represent the second and third best candidate solutions where omega is the least probable solution
to the problem.
Figure 1. Grey wolves’ social hierarchy
2.1.1. Mathematical modeling
2.1.1.1. Encircling prey
In order to mathematically model encircling behavior of the grey wolves the following equations are
presented in [13-14]:
𝐷⃗⃗ = |𝐶. 𝑋 𝑝
⃗⃗⃗⃗ (𝑡) − 𝑋(𝑡)| (1)
𝑋(𝑡 + 1) = 𝑋 𝑝
⃗⃗⃗⃗ (𝑡) − 𝐴. 𝐷⃗⃗ (2)
where:
t indicates the current iteration,
𝐴 and 𝐶 are coefficient vectors,
𝑋 𝑝
⃗⃗⃗⃗ (𝑡) is the position vector of the prey,
𝑋(𝑡) indicates the position vector of a grey wolf.
The vectors 𝐴 and 𝐶 are calculated as follows:
𝐴 = 2 𝑎. 𝑟1⃗⃗⃗ − 𝑎 (3)
𝐶 = 2. 𝑟2⃗⃗⃗ (4)
where:
components of 𝑎 are linearly decreased from 2 to 0 over the course of iterations 𝑟1⃗⃗⃗ and 𝑟2⃗⃗⃗ are random vectors
in the range of [0,1]. From the above equations, a grey wolf in the position of (X,Y) in the search space can
update its position according to the position of the prey (X*,Y*) different locations around the best agent can
be reached with respect to the current position by varying the values of the vectors 𝐴 and 𝐶. So, a grey wolf
can update its position inside the space around the prey in any random place by using the above
mentioned equations.
4. Int J Elec & Comp Eng ISSN: 2088-8708
Enhancing radial distribution system performance by optimal placement of DSTATCOM (S. F. Mekhamer)
2853
2.1.1.2. Hunting
During the hunting process, Grey wolves have the capability to find the prey and encircle them.
The leader of the hunting is the alpha wolf. The beta and delta wolves may also contribute in the hunting
process occasionally. However, in an abstract search space there is no clue about the location of the optimum
prey. In order to model mathematically the hunting behavior of grey wolves, suggest that the alpha
(best candidate solution) beta and delta have better knowledge about the potential location of prey. Therefore,
store the first three best solutions found so far and force all the other search agents to change their positions
according to the position of the best search agent. The following formulas and equations are presented in this
regard to represent the previous explained behavior:
𝐷 𝛼
⃗⃗⃗⃗⃗ = 𝐶1
⃗⃗⃗⃗ . 𝑋 𝛼
⃗⃗⃗⃗⃗ − 𝑋 (5)
𝐷𝛽
⃗⃗⃗⃗ = 𝐶2
⃗⃗⃗⃗ . 𝑋 𝛽
⃗⃗⃗⃗⃗ − 𝑋 (6)
𝐷 𝛿
⃗⃗⃗⃗ = 𝐶3
⃗⃗⃗⃗ . 𝑋 𝛿
⃗⃗⃗⃗⃗ − 𝑋 (7)
𝑋1
⃗⃗⃗⃗ = 𝑋 𝛼
⃗⃗⃗⃗ − 𝐴1
⃗⃗⃗⃗ . (𝐷 𝛼
⃗⃗⃗⃗⃗ ) (8)
𝑋2
⃗⃗⃗⃗ = 𝑋 𝛽
⃗⃗⃗⃗ − 𝐴2
⃗⃗⃗⃗ . (𝐷𝛽
⃗⃗⃗⃗ ) (9)
𝑋3
⃗⃗⃗⃗ = 𝑋 𝛿
⃗⃗⃗⃗ − 𝐴3
⃗⃗⃗⃗ . (𝐷 𝛿
⃗⃗⃗⃗ ) (10)
𝑋(⃗⃗⃗⃗ t+1) =
𝑋1⃗⃗⃗⃗⃗ + 𝑋2⃗⃗⃗⃗⃗ +𝑋3⃗⃗⃗⃗⃗
3
(11)
In search space using these equations, a search agent changes and updates its position according to
alpha, beta and delta. Also, the final position reached would be in a random place within a circle which is
defined by the positions of alpha, beta, and delta. In short words, alpha, beta and delta determine the position
of the prey and all other wolves update and change their positions in a random way around the prey.
2.1.2. Exploration and exploitation in GWO
In [15] during the optimization process, the algorithm performs two opposite actions which are
exploration and exploitation. During the exploration phase, the algorithm tries to explore all the new areas of
the problem search space by making changes in the solutions since the main purpose is to know the best areas
of the search landscape and prohibit solutions from being trapped in a local optimum. While during
exploitation phase, the main target is to enhance the calculated solutions obtained in the exploration process
by knowing the neighbourhood parts of each solution. Therefore, updates in the solutions found should be
made to converge towards the global optimal solution of the problem.
In GWO, searching for prey represents exploration phase and mathematically the (C) vector, (A)
and (a) also represents it. The (C) vector presents the effect of obstacles to approaching prey in nature.
In general, the wolves face obstacles during the hunting process which slows them and makes it harder when
approaching the prey. In Summary, the searching process starts by intializing a random population of grey
wolves) in the GWO algorithm. Over the course of iterations, alpha, beta, and delta wolves determine
the exact position of the prey. each agent updates and changes its distance from the prey. The parameter (a) is
decreased from 2 to 0 in order to assure exploration and exploitation, respectively. Agents tend to diverge
away from the prey when |𝐴|⃗⃗⃗⃗⃗ >1and converge towards the prey when 𝐴 <1. Finally, the GWO algorithm is
terminated by the satisfaction of an end condition.
2.2. Modified grey wolf optimization algorithm (MGWOA)
In order to improve the exploration phase in GWO, the value of (a⃗ ) is varied using an exponential
function instead of changing it linearly as prposed in [18]. In this case the following equation is used:
a = 2 (1-
𝑖𝑡𝑒𝑟2
max 𝑖𝑡𝑒𝑟2) (12)
where, 𝑖𝑡𝑒𝑟 is the current iteration, and 𝑚𝑎𝑥 𝑖𝑡𝑒𝑟 is the maxium number of iterations.
5. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 3, June 2020 : 2850 - 2860
2854
2.3. DSTATCOM structure
DSTATCOM is a type of the flexiable AC transmissions (FACTs) devices, and it absorbs or
supplies both the reactive and the active current at a point of common coupling (PCC). Actually, it is
considerd a DC/AC converter, where it consists of a dc energy storage bank or a dc-link capacitor. The main
role of the energy bank is supplying a constant DC voltage, which is converted to a 3-phase voltage. The AC
output voltage feeds a coupling transformer that is commoned coupling with the RDS [19]. Mainly,
the DSTATCOM operates as a variable synchronous voltage source, where both voltage magnitude and
angles are tuned in order to control the bus voltage and improve the power factor. The connection of
the DSTATCOM to the distribution system bus is illustrated as in Figure 2. Most properly, PID controller has
been applied in many studies to control the state of this device; inject or absorb the electrical current. The bus
voltage is regulated by DSTATCOM in the normal or abnormal conditions, where it injects the proper power
to the bus. The power exchange might be for the active or reactive power, but in this paper the DSTATCOM
is only for the reactive power exchange. Newton-Raphosn load flow calculation method has been applied in
this work, and it is assumed that the distribution network is in balance conditions. A section of a sample
distribution network is shown in Figure 3.
Figure 2. DSTATCOM connected to bus i Figure 3. Single line diagram of two consecutive buses of
a distribution system
In this Figure 3, 𝑅𝑖 + 𝑗𝑋𝑖 is the impedance between the 𝑖 𝑡ℎ
and 𝑖 + 1 𝑡ℎ
buses. 𝑉𝑖, 𝑃𝑖, and 𝑄𝑖 are
voltage, active power, and reactive power of the 𝑖 𝑡ℎ
bus respectively, and the same for the 𝑖 + 1 𝑡ℎ
bus. Figure
4 illustrates the phasor diagram of Figure 3, and if KVL is applying the phasor equation is result as in (13):
𝑉𝑖+1∠𝜃𝑖+1 = 𝑉𝑖∠𝜃𝑖 − (𝑅𝑖 + 𝑗𝑋𝑖). 𝐼𝑖∠𝛿 (13)
Figure 4. Phasor diagram of voltage and current of the system
here, 𝐼𝑖 is the flowing current from 𝑖 𝑡ℎ
to 𝑖 + 1 𝑡ℎ
buses. In this work, a DSTATCOM has been installed to
improve the voltage of the 𝑖 + 1 𝑡ℎ
bus to reach the optimized level, as in Figure 5. Finally, this device is
applied for regulating the bus voltage, reducing the system loss in steady state condition. It would be
achievable if the current angle 𝜃 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 of the DSTATCOM is in the desired quadrature with respect to the
voltage angle.
𝜃 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 =
𝜋
2
+ 𝜃𝑖+1 (14)
6. Int J Elec & Comp Eng ISSN: 2088-8708
Enhancing radial distribution system performance by optimal placement of DSTATCOM (S. F. Mekhamer)
2855
So, (13) is modified to the following:
𝑉𝑖+1∠𝜃𝑖+1 = 𝑉𝑖∠𝜃𝑖 − (𝑅𝑖 + 𝑗𝑋𝑖). (𝐼𝑖∠𝛿 + 𝐼 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀∠𝜃 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀) (15)
Figure 5. DSTATCOM installation at the 𝑖 + 1 𝑡ℎ
bus
Figure 4 is modified according to (15), and the final phasor diagram is represented as in
Figure 6. The DSTATCOM current angle is determined as in (14) and the current magnitude could be
obtained from (16):
|𝐼 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀| =
𝑉 𝑖+1 cos 𝜃 𝑖+1−𝑎1
−𝑎4 sin 𝜃 𝑖+1−𝑎3 cos 𝜃 𝑖+1
(16)
where, 𝑎1and 𝑎2 are the real and the imaginary of (13) respectively. while, 𝑎3 is −𝑋𝑖 and 𝑎4 is −𝑅𝑖.
Finally, the injected reactive power 𝑄 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 is the multiplication of 𝑉𝑖+1 by 𝐼 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 as in (17):
𝑗𝑄 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 = 𝑉𝑖+1∠𝜃𝑖+1. 𝐼 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀∠𝜃 𝐷𝑆𝑇𝐴𝑇𝐶𝑂𝑀 (17)
Figure 6. The final phasor diagram of voltage and current of system after installing the DSTATCOM
2.4. Objective Function
From [9] a multi-objective function is represented as in (18), to ensure that the DSTACOM is
located in the optimal bus, and it contains two objective functions. The first objective is to minimize the
system power loss as in (19). Additionally, in (20) demonstrates the second objective which is minimizing
the cost of the DSTATCOM:
𝑂. 𝐹 = 𝑚𝑖𝑛 {
𝑂. 𝐹1
𝑂. 𝐹2
(18)
𝑂. 𝐹1 = 𝑅𝐷𝑆𝑙𝑜𝑠𝑠 (19)
𝑂. 𝐹2 = 𝑇𝐴𝐶 𝐷𝑠𝑡𝑎𝑡𝑐𝑜𝑚,𝑖 (20)
The power loss minimization which is the first objective function is described in (21) as:
𝑃𝑙𝑜𝑠𝑠 𝑖
= ∑ 𝑅𝑖. |𝐼𝑖|2𝑁 𝑏
𝑖=1 (21)
7. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 3, June 2020 : 2850 - 2860
2856
where, 𝑁𝑏 is number of the system branches, 𝑅𝑖 is the branch resistance, and 𝐼𝑖 is the brach current. In (22)
shows the second objective which is minimizing the cost due to power loss.
𝑇𝐴𝐶 𝐷𝑠𝑡𝑎𝑡𝑐𝑜𝑚,𝑖 = 𝐾𝑒 . QDSTATCOM .t (22)
where:
𝑇𝐴𝐶 𝐷𝑠𝑡𝑎𝑡𝑐𝑜𝑚,𝑖 is the total power loss cost
𝐾𝑒 is the energy costof losses in ($/Kwh)
QDSTATCOM is the DSTATCOM size in KVAr
t is the load duration
The weighted-sum method has been applied to convert the multi-objective to single objective
function where 𝑤1 and 𝑤2 are weight factors and (18) is rewritten as follows:
𝑂. 𝐹 = 𝑤1. ∑ 𝑅𝑖. |𝐼𝑖|2𝑁 𝑏
𝑖=1 + 𝑤2. (𝑇𝐴𝐶 𝐷𝑠𝑡𝑎𝑡𝑐𝑜𝑚,𝑖) (23)
Finally, the main constraints of the proposed objective function are described in both (24) and (25), where in
(24) the voltage constraints are defined. The upper and lower limits of the DSTATCOM reactive power
capacity are demonstrated in (25).
𝑉 𝑚𝑖𝑛 ≤ 𝑉𝑖 ≤ 𝑉𝑚𝑎𝑥 (24)
Where, 𝑉 𝑚𝑖𝑛 and 𝑉𝑚𝑎𝑥 are the minimum and maxiumim limits respectively of the bus voltage. While,
in (25) QSTATCOM
min
and QSTATCOM
max
are the minimum and maximum limits respectively of the DSTATCOM
unit size in kVAr.
QSTATCOM
min
≤ 𝑄 𝑆𝑇𝐴𝑇𝐶𝑂𝑀 ≤ QSTATCOM
max
(25)
2.5. Algorithm steps
Using Newton Rapshon method solve the load flow problem for the given test feeder and determine
the system total power loss and system voltage profile.
Initialize the random number of search agents, set the iteration counter=1, set max number of iterations,
set the problem predefined constraints for DSTATCOM size, bus voltage limit and maximum current
in line.
Read the system parameters which include the system real power loss, line data, system constraints and
bus data for generated population by performing load flow calculations.
Intialize the population X randomly, where each agent represents a candidate solution.
𝑋 𝑚 = 𝑋 𝑚
𝑚𝑖𝑛
+ rand (0,1) ( 𝑋 𝑚
𝑚𝑎𝑥
- 𝑋 𝑚
𝑚𝑖𝑛
) (26)
where m = 1,2,3,….,N.
Calculate the fitness function for all population using load flow calculations and taking constraints
into account.
Determine and update Xα , Xβ , Xδ where Xα is the first best search agent, Xβ is the second-best search
agent, Xδ is the third best search agent
Update and move the rest of search agents usings equations (1-12).
Claculate the objective function for the updated agents.
Update the values of A, C, an according to (3-4) & (12).
Repeat until the maximum number of iterations is performed and print the results.
3. RESULTS AND ANALYSIS
3.1. The First Feeder
The first tested feeder using the proposed modified grey wolf optimization algorithm MGWOA is
the 33-bus system. The system single line diagram is shown in Figure 7. This test feeder has a total load of
3720 kW and 2300 kVAr at a voltage level of 12.66 kV. The system data are found in [20-23].
The configuration of the system before installing DSTATCOM is as follow: the real power loss in kW is
210.9 and the minimum bus voltage is 0.9038. The results of the system performance before and after
8. Int J Elec & Comp Eng ISSN: 2088-8708
Enhancing radial distribution system performance by optimal placement of DSTATCOM (S. F. Mekhamer)
2857
connecting the DSTATCOM to the test feeder are shown in Table 1. Also Table 1 presents the results
obtained by the proposed technique and other recent optimization methods applied to same test feeder.
It is concluded from the results that the proposed method performs superior process regarding the most
minimized system power losses and the best improved voltage profile compared to other optimization
techniques as bat algorithm and immune optimization algorithm.The reduction in system active power losses
has reached 29.15% and minimization of system reactive power losses has achieved 29% accompanied by
reduction in cost due to power loss. Also, the minmum bus voltage in p.u. is raised from 0.91 to 0.93.
Figure 8 shows the effectiveness of the proposed method after placing the DSTATCOM in reducing total
system active power losses compared to recent optimization techniques as BAT algorithm. From the obtained
results shown in Table 1 and Figure 8 for the 33 bus test feeder, the novelity factors in the results were
the most minimized total real power losses in the test feeder, the most improved voltage profile for the test
feeder and the most reduction in costs due to total power loss in test system which showed the effectiveness
of applied method.
Figure 7. Single line diagram of IEEE 33 bus system
Table 1. Optimal results of 33-bus feeder after single DSTATCOM placement
Figure 8. Comparsion of the active power losses reductions in the IEEE 33 bus test system after placing
DSTATCOM using different optimization algoritms
9. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 3, June 2020 : 2850 - 2860
2858
3.2. The second feeder
As in Figure 9, the second tested radial distribution feeder is a larger scale system with 69 buses and
68 branches. The line and bus data of this system are taken from [20-23]. The base values are 100MVA and
12.66KV and the total real and reactive power loads of the system are 3.80MWand 2.69MVAr, respectively.
Table 2 represents a comparison between four different recent techniques applied to the tested feeder,
it is noted that the proposed method has achieved the most reduction in real power loss in Kw and in kVAr
and the most improved system voltage profile as the minimum bus voltage in the system has increased from
0.909 to 0.939 pu. Figure 10 shows the total active power loss in the system after connecting
the DSTATCOM to the network using the proposed optimization technique and various recent optimization
techniques. From the obtained results for the 69 bus test feeder, the novelity factors in the results were
the most minimized total real power losses in the test feeder, the most improved voltage profile for the test
feeder and the most reduction in costs due to total power loss in test system which confirmed the superiority
of the applied technique
Figure 9. Single line diagram of IEEE 69 bus system
Table 2. Optimal results of 69-bus feeder after single DSTATCOM placement
Figure 10. Comparsion of the active power losses reductions in the IEEE 69 bus test system after placing
DSTATCOM using different optimization algoritms
10. Int J Elec & Comp Eng ISSN: 2088-8708
Enhancing radial distribution system performance by optimal placement of DSTATCOM (S. F. Mekhamer)
2859
4. CONCLUSION
In this study, a modified grey wolf optimization algorithm is used to solve the problem of optimal
allocation and sizing of DSTATCOM in radial distribution feeder. The proposed method is tested on different
radial test feeders to ensure its effectiveness and superiority. The results have been compared with other
optimization techniques such as bat algorithm and cuccko search algorithm. It is observed from the obtained
results that the proposed technique has a superior performance regarding minimizing overall system real
power losses, improving system voltage profile and reducing costs due to power loss.
REFERENCES
[1] R. H. Shehata, S. F. Mekhamer, A. Y. Abdelaziz, M. A. L. Badr, “Solution of the capacitor allocation problem
using an improved whale optimization algorithm,” International Journal of Engineering, Science and Technology,
Vol. 10, pp. 1-11, 2018.
[2] S. Surender Reddy, “Optimal Placement of FACTS Controllers for Congestion Management in the Deregulated
Power System,” International Journal of Electrical and Computer Engineering (IJECE), Vol. 8, No. 3,
pp. 1336-1344, 2018.
[3] Aziz Oukennou, Abdelhalim Sandali, and Samira Elmoumen, “Coordinated Placement and Setting of FACTS in
Electrical Network based on Kalai-smorodinsky Bargaining Solution and Voltage Deviation Index,” International
Journal of Electrical and Computer Engineering (IJECE), Vol. 8, No. 6, pp. 4079-4088, 2018.
[4] Sekhane Hocine and Labed Djamel, “Optimal number and location of UPFC devices to enhance voltage profile and
minimizing losses in electrical power systems,” International Journal of Electrical and Computer Engineering
(IJECE), Vol. 9, No. 5, pp. 3981-3992, 2019.
[5] Surekha Manoj, Puttaswamy P. S, “Importance of FACTS Controllers in Power Systems,” International Journal of
Advanced Engineering Technology, Vol. 2, No. 3, pp.207-212, 2011.
[6] Z. Yang, C Shen, M. L. Crow and L. Zhang, “An Improved STATCOM Model for Power Flow Analysis,”
2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134), 2000.
[7] Naseer M. Yasin and Haider A. Talib, “Genetic Based Optimal Location of STATCOM Compensator,”
International Journal of Applied Engineering Research, Vol. 13, No. 10, pp. 7516-7521, 2018.
[8] T. Yuvaraja, K. R. Devabalajia and K. Ravia, “Optimal placement and sizing of DSTATCOM using Harmony
Search algorithm,” Energy Procedia, vol.79, pp.759 – 765, 2015.
[9] Seyed Abbas Taher, Seyed Ahmadreza Afsari, “Optimal location and sizing of DSTATCOM in distribution
systems by immune algorithm,” International Journal of Electrical Power & Energy Systems, vol. 60, pp. 34–44,
2014.
[10] Atma Ram Guptaa and Ashwani Kumarb, “Energy savings using D-STATCOM placement in radial distribution
System,” Procedia Computer Science, vol.70, pp. 558–564, 2015.
[11] T. Yuvaraj, K. Ravi and K. R. Devabalaji, “DSTATCOM allocation in distribution networks considering load
variations using bat algorithm,” Ain Shams Engineering Journal, 2015.
[12] Abu Hachan Shah and Satyajit Bhuyan, “Variable Evaluation and Optimal Placement of STATCOM in Test Bus
Systems,” ADBU-Journal of Engineering Technology, Vol. 7, No. 1, pp.1-6, 2018.
[13] Seyedali Mirjalili, Seyed Mohammad Mirjalili and Andrew Lewis, “Grey Wolf Optimizer,” Advances in
Engineering Software, vol. 69, pp. 46–61, 2014.
[14] Hossam Faris, Ibrahim Aljarah, Mohammed Azmi Al-Betar, Seyedali Mirjalili, “Grey wolf optimizer: a review of
recent variants and applications,” Neural Computing and Applications, vol. 30, pp.413-435, 2018.
[15] Crepinsek M and Liu S-H, Mernik M, “Exploration and exploitation in evolutionary algorithms: a survey,”
ACM Computing Surveys (CSUR), vol.45, No. 3, pp. 35:1-35:33, 2013.
[16] M. A. Algabalawy, A.Y. Abdelaziz, S. F. Mekhamer, M.A.L. Badr ,” Optimal Multi-Criteria Design of a New
Hybrid Power Generation System Using Ant Lion and Grey Wolf Optimizers,” Eighteenth international middle
east power systems conference (MEPCON), Cairo , pp.138-146,2016.
[17] D. P. Ladumor, I. N. Triveedi, R. H. Bhesdadiya and P. Jangir , “optimal power flow problems solution with
STATCOM using meta-heuristic algorithm,” Third International Conference On Advances In Electrical,
Electronics, Information, Communication And Bio-Informatics (AEEICB), Chennai, pp. 392-396, 2017.
[18] Mittal N, Singh U and Sohi BS, “Modified grey wolf optimizer for global engineering optimization,” Applied
Computational Intelligence and Soft Computing, vol. 2016, pp. 1-16, 2016.
[19] Blazic B and Papic I., “A new mathematical model and control of DSTATCOM for operation under unbalanced
conditions,” Electrical Power System Research, vol. 72, no. 3, pp.279–287, 2004.
[20] Hingorani N.,” Introducing custom power,” IEEE Spectrum, vol. 32, no.6, pp. 41–48, 1995.
[21] Nilsson S., “Special application consideration for custom power systems,” IEEE conference power engineering
society, vol. 2, pp. 1127-1131, 1999.
[22] A. Adya, B. Singh, J. R. P. Gupta and A. P. Mittal, "Application of D-STATCOM for isolated systems," 2004 IEEE
Region 10 Conference TENCON 2004, Chiang Mai, vol. 3, pp. 351-354, 2004.
[23] D. Rama Prabha and T. Jayabarathi, "Optimal placement and sizing of multiple distributed generating units in
distribution networks by invasive weed optimization algorithm," Ain Shams Engineering Journal, vol. 7, no.2,
pp. 683–694, 2016.
11. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 3, June 2020 : 2850 - 2860
2860
[24] K. R. Devabalaji and K. Ravi, “Optimal size and siting of multiple DG and DSTATCOM in radial distribution
system using Bacterial Foraging Optimization Algorithm,” Ain Shams Engineering Journal, vol.7, no. 3,
pp.959–971, 2016.
[25] T. Yuvaraj, K. Ravi and K. R. Devabalaji, “Optimal Allocation of DG and DSTATCOM in Radial Distribution
System Using Cuckoo Search Optimization Algorithm,” Hindawi Modelling and Simulation in Engineering,
vol. 2017, pp.1-11, 2017.
BIOGRAPHIES OF AUTHORS
Dr. S. F. Mekhamer was born in Egypt in 1964. He received the B. Sc. and M.Sc. degrees in
electrical engineering from Ain Shams University, Cairo, Egypt, and the Ph.D. degree in electrical
engineering from Ain Shams University with joint supervision from Dalhousie University, Halifax,
NS, Canada, in 2002. He is currently a Professor in the Department of Electric Power and Machines,
Ain Shams University. His research interests include power system analysis, power system
protection, and applications of AI in power systems. Currently, he is a professor in Future University
in Egypt (FUE) on leave from Ain Shams University.
Eng. R. H. Shehata was born in Egypt in 1986.He received the B.Sc. and M.Sc. degrees in electrical
engineering from Ain Shams University, Egypt, in 2008 and 2014, respectively and is currently
registered as a Ph.D. researcher in electrical engineering in the same university. Since 2009, he has
been working for the Arab Contractors in Egypt and currently occupies the position as a senior
electrical power system design and tender engineer. Through this position, he has participated in
many local, regional and African projects about the design and tender studies of different power
systems in buildings and water stations with the different national and international organizations.
Dr. A. Y. Abdelaziz Received the B.Sc. and M.Sc. degrees in electrical engineering from Ain
Shams University, Egypt, in 1985 and 1990, respectively, and the Ph.D. degree in electrical
engineering according to the channel system between Ain Shams University, Egypt, and Brunel
University, U.K., in 1996. He is currently a Professor of electrical power engineering at Ain Shams
University. Dr. Abdelaziz is the chair of IEEE Education Society chapter in Egypt, senior editor of
Ain Shams Engineering Journal, editor of Electric Power Components & Systems Journal, editorial
board member, associate editor and editorial advisory board member of several international journals
and conferences. He is also a member in IET and the Egyptian Sub-Committees of IEC and CIGRE’.
He has been awarded many prizes for distinct researches and for international publishing from Ain
Shams University, Egypt. He has authored or coauthored more than 320 refereed journal and
conference papers in his research areas which include the applications of artificial intelligence,
evolutionary and heuristic optimization techniques to power system operation, planning, and control.
Dr. M. A. Al-Gabalawy, he was born in 1983, in Egypt. He had finished his B.Sc. degree in 2005 in
honor from the electrical engineering department, Cairo University. In 2011 and 2017 he has been
awarded the M.Sc. and PhD degrees respectively from the electrical engineering department,
Ain Shams University. Currntly, the main research interest is in the field of the energy management
and energy control applying new artifial intelligence algorithms.