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.
VOLTAGE PROFILE IMPROVEMENT AND LINE LOSSES REDUCTION USING DG USING GSA AND ...Journal For Research
In recent years, the power industry has experienced significant changes on the power distribution systems primarily due to the implementation of smart-grid technology and the incremental implementation of distributed generation. Distributed Generation (DG) is simply defined as the decentralization of power plants by placing smaller generating units closer to the point of consumption, traditionally ten mega-watts or smaller. The distribution power system is generally designed for radial power flow, but with the introduction of DG, power flow becomes bidirectional. Therefore this thesis focuses on testing various indices and using effective techniques for the optimal placement and sizing of the DG unit by minimizing power losses and voltage deviation. A 14-bus radial distribution system has been taken as the test system. The feasibility of the work lies on the fast execution of the programs as it would be equipped with the real time operation of the distribution system and it is seen that execution of the DG placement is quite fast and feasible with the optimization techniques used in this work.
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.
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.
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.
VOLTAGE PROFILE IMPROVEMENT AND LINE LOSSES REDUCTION USING DG USING GSA AND ...Journal For Research
In recent years, the power industry has experienced significant changes on the power distribution systems primarily due to the implementation of smart-grid technology and the incremental implementation of distributed generation. Distributed Generation (DG) is simply defined as the decentralization of power plants by placing smaller generating units closer to the point of consumption, traditionally ten mega-watts or smaller. The distribution power system is generally designed for radial power flow, but with the introduction of DG, power flow becomes bidirectional. Therefore this thesis focuses on testing various indices and using effective techniques for the optimal placement and sizing of the DG unit by minimizing power losses and voltage deviation. A 14-bus radial distribution system has been taken as the test system. The feasibility of the work lies on the fast execution of the programs as it would be equipped with the real time operation of the distribution system and it is seen that execution of the DG placement is quite fast and feasible with the optimization techniques used in this work.
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.
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.
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.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Multi-objective optimal placement of distributed generations for dynamic loadsIJECEIAES
Large amount of active power losses and low voltage profile are the two major issues concerning the integration of distributed generations with existing power system networks. High R/X ratio and long distance of radial network further aggravates the issues. Optimal placement of distributed generators can address these issues significantly by alleviating active power losses and ameliorating voltage profile in a cost effective manner. In this research, multi-objective optimal placement problem is decomposed into minimization of total active power losses, maximization of bus voltage profile enhancement and minimization of total generation cost of a power system network for static and dynamic load characteristics. Optimum utilization factor for installed generators and available loads is scaled by the analysis of yearly load-demand curve of a network. The developed algorithm of N-bus system is implemented in IEEE-14 bus standard test system to demonstrate the efficacy of the proposed method in different loading conditions.
Hybrid bypass technique to mitigate leakage current in the grid-tied inverterIJECEIAES
The extensive use of fossil fuel is destroying the balance of nature that could lead to many problems in the forthcoming era. Renewable energy resources are a ray of hope to avoid possible destruction. Smart grid and distributed power generation systems are now mainly built with the help of renewable energy resources. The integration of renewable energy production system with the smart grid and distributed power generation is facing many challenges that include addressing the issue of isolation and power quality. This paper presents a new approach to address the aforementioned issues by proposing a hybrid bypass technique concept to improve the overall performance of the grid-tied inverter in solar power generation. The topology with the proposed technique is presented using traditional H5, oH5 and H6 inverter. Comparison of topologies with literature is carried out to check the feasibility of the method proposed. It is found that the leakage current of all the proposed inverters is 9 mA and total harmonic distortion is almost about 2%. The proposed topology has good efficiency, common mode and differential mode characteristics.
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 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.
Optimal Siting And Sizing Of Distributed Generation For Radial Distribution S...inventy
Research Inventy provides an outlet for research findings and reviews in areas of Engineering, Computer Science found to be relevant for national and international development, Research Inventy is an open access, peer reviewed international journal with a primary objective to provide research and applications related to Engineering. In its publications, to stimulate new research ideas and foster practical application from the research findings. The journal publishes original research of such high quality as to attract contributions from the relevant local and international communities.
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.
Various demand side management techniques and its role in smart grid–the stat...IJECEIAES
The current lifestyle of humanity relies heavily on energy consumption, thusrendering it an inevitable need. An ever-increasing demand for energy hasresulted from the increasing population. Most of this demand is met by thetraditional sources that continuously deplete and raise significantenvironmental issues. The existing power structure of developing nations isaging, unstable, and unfeasible, further prolonging the problem. The existingelectricity grid is unstable, vulnerable to blackouts and disruption, has hightransmission losses, low quality of power, insufficient electricity supply, anddiscourages distributed energy sources from being incorporated. Mitigatingthese problems requires a complete redesign of the system of powerdistribution. The modernization of the electric grid, i.e., the smart grid, is anemerging combination of different technologies designed to bring about theelectrical power grid that is changing dramatically. Demand sidemanagement (DSM) allow customers to be more involved in contributors tothe power systems to achieve system goals by scheduling their shiftableload. Effective DSM systems require the participation of customers in thesystem that can be done in a fair system. This paper focuses primarily ontechniques of DSM and demand responses (DR), including schedulingapproaches and strategies for optimal savings.
Design methodology of smart photovoltaic plant IJECEIAES
In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink.
New solutions for optimization of the electrical distribution system availabi...Mohamed Ghaieth Abidi
This paper deals with the availability in microgrids that are composed of a set of sources (Photovoltaic generators, wind turbines, diesel generators and batteries) and a set of loads (critical and uncritical loads). The energy produced by various sources will be grouped in an alternative bus (AC bus), and it will be distributed on loads through an electrical distribution system. The occurrence of a fault in the system can cause a total or partial unavailability of energy required by the loads. The objective of this paper is to characterize the fault caused by the limited reliability of the components of the electrical distribution system and to propose an new design methodology to optimize the availability of this system (as well as the availability of power supply) by taking into account all the economic constraints. The proposed methodology is based on the redundancy of electrical distribution paths. An application of this optimization to a petroleum platform shows clearly a high degree of supply availability distribution in microgrid.
A NOVEL CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT USING ANN TECHNIQUE FO...IJERD Editor
The proposed system presents power-control strategies of a Micro grid-connected hybrid generation
system with versatile power transfer. This hybrid system allows maximum utilization of freely available
renewable energy sources like wind and photovoltaic energies. For this, an adaptive MPPT algorithm along with
standard perturbs and observes method will be used for the system.
The inverter converts the DC output from non-conventional energy into useful AC power for the
connected load. This hybrid system operates under normal conditions which include normal room temperature
in the case of solar energy and normal wind speed at plain area in the case of wind energy. However, designing
an optimal micro grid is not an easy task, due to the fact that primary energy carriers are changeable and
uncontrollable, as is the demand. Traditional design and optimization tools, developed for controlled power
sources, cannot be employed here. Simulation methods seem to be the best solution.
The dynamic model of the proposed system is first elaborated in the stationary reference frame and
then transformed into the synchronous orthogonal reference frame. The transformed variables are used in
control of the voltage source converter as the heart of the interfacing system between DG resources and utility
grid. By setting an appropriate compensation current references from the sensed load currents in control circuit
loop of DG, the active, reactive, and harmonic load current components will be compensated with fast dynamic
response, thereby achieving sinusoidal grid currents in phase with load voltages, while required power of the
load is more than the maximum injected power of the DG to the grid. In addition, the proposed control method
of this paper does not need a phase-locked loop in control circuit and has fast dynamic response in providing
active and reactive power components of the grid-connected loads.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Loss issue is significant in power system since it affects the operation of power system, which ultimately can be translated to monetary effect. Incremental demand that explicitly adding the reactive load causes extra heating losses in the transmission circuit. Without appropriate remedial control, the temperature increase on transmission line cable would end with insulation failure. This phenomenon can be alleviated with a proper compensation scheme that provides optimal solution along with avoidance of under-compensation or over-compensation. Evolutionary Programming (EP) has been recognised as one of the powerful optimisation technique, applied in solving power system problems. Nevertheless, EP is an old technique that sometimes could reach to a settlement that is not fully satisfied. Thus, the need fora new approach to improve the setback is urgent. This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment. The classical EP was integrated with immune algorithm so as to reduce the computational burden experienced by the classical EP.The algorithm has been tested on an IEEE 12-Bus System and IEEE 14-Bus System.Comparative study was conducted between EP and IEP in terms of optimisation performance. The optimal size and location of PV determined by IEP was able to control the loss in transmission system when the load increases. Results obtained from the studies revealed the merit of the proposed IEP; indicating its feasibility for future implementation in practical system.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
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.
Islanded microgrid congestion control by load prioritization and shedding usi...IJECEIAES
The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Multi-objective optimal placement of distributed generations for dynamic loadsIJECEIAES
Large amount of active power losses and low voltage profile are the two major issues concerning the integration of distributed generations with existing power system networks. High R/X ratio and long distance of radial network further aggravates the issues. Optimal placement of distributed generators can address these issues significantly by alleviating active power losses and ameliorating voltage profile in a cost effective manner. In this research, multi-objective optimal placement problem is decomposed into minimization of total active power losses, maximization of bus voltage profile enhancement and minimization of total generation cost of a power system network for static and dynamic load characteristics. Optimum utilization factor for installed generators and available loads is scaled by the analysis of yearly load-demand curve of a network. The developed algorithm of N-bus system is implemented in IEEE-14 bus standard test system to demonstrate the efficacy of the proposed method in different loading conditions.
Hybrid bypass technique to mitigate leakage current in the grid-tied inverterIJECEIAES
The extensive use of fossil fuel is destroying the balance of nature that could lead to many problems in the forthcoming era. Renewable energy resources are a ray of hope to avoid possible destruction. Smart grid and distributed power generation systems are now mainly built with the help of renewable energy resources. The integration of renewable energy production system with the smart grid and distributed power generation is facing many challenges that include addressing the issue of isolation and power quality. This paper presents a new approach to address the aforementioned issues by proposing a hybrid bypass technique concept to improve the overall performance of the grid-tied inverter in solar power generation. The topology with the proposed technique is presented using traditional H5, oH5 and H6 inverter. Comparison of topologies with literature is carried out to check the feasibility of the method proposed. It is found that the leakage current of all the proposed inverters is 9 mA and total harmonic distortion is almost about 2%. The proposed topology has good efficiency, common mode and differential mode characteristics.
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 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.
Optimal Siting And Sizing Of Distributed Generation For Radial Distribution S...inventy
Research Inventy provides an outlet for research findings and reviews in areas of Engineering, Computer Science found to be relevant for national and international development, Research Inventy is an open access, peer reviewed international journal with a primary objective to provide research and applications related to Engineering. In its publications, to stimulate new research ideas and foster practical application from the research findings. The journal publishes original research of such high quality as to attract contributions from the relevant local and international communities.
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.
Various demand side management techniques and its role in smart grid–the stat...IJECEIAES
The current lifestyle of humanity relies heavily on energy consumption, thusrendering it an inevitable need. An ever-increasing demand for energy hasresulted from the increasing population. Most of this demand is met by thetraditional sources that continuously deplete and raise significantenvironmental issues. The existing power structure of developing nations isaging, unstable, and unfeasible, further prolonging the problem. The existingelectricity grid is unstable, vulnerable to blackouts and disruption, has hightransmission losses, low quality of power, insufficient electricity supply, anddiscourages distributed energy sources from being incorporated. Mitigatingthese problems requires a complete redesign of the system of powerdistribution. The modernization of the electric grid, i.e., the smart grid, is anemerging combination of different technologies designed to bring about theelectrical power grid that is changing dramatically. Demand sidemanagement (DSM) allow customers to be more involved in contributors tothe power systems to achieve system goals by scheduling their shiftableload. Effective DSM systems require the participation of customers in thesystem that can be done in a fair system. This paper focuses primarily ontechniques of DSM and demand responses (DR), including schedulingapproaches and strategies for optimal savings.
Design methodology of smart photovoltaic plant IJECEIAES
In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink.
New solutions for optimization of the electrical distribution system availabi...Mohamed Ghaieth Abidi
This paper deals with the availability in microgrids that are composed of a set of sources (Photovoltaic generators, wind turbines, diesel generators and batteries) and a set of loads (critical and uncritical loads). The energy produced by various sources will be grouped in an alternative bus (AC bus), and it will be distributed on loads through an electrical distribution system. The occurrence of a fault in the system can cause a total or partial unavailability of energy required by the loads. The objective of this paper is to characterize the fault caused by the limited reliability of the components of the electrical distribution system and to propose an new design methodology to optimize the availability of this system (as well as the availability of power supply) by taking into account all the economic constraints. The proposed methodology is based on the redundancy of electrical distribution paths. An application of this optimization to a petroleum platform shows clearly a high degree of supply availability distribution in microgrid.
A NOVEL CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT USING ANN TECHNIQUE FO...IJERD Editor
The proposed system presents power-control strategies of a Micro grid-connected hybrid generation
system with versatile power transfer. This hybrid system allows maximum utilization of freely available
renewable energy sources like wind and photovoltaic energies. For this, an adaptive MPPT algorithm along with
standard perturbs and observes method will be used for the system.
The inverter converts the DC output from non-conventional energy into useful AC power for the
connected load. This hybrid system operates under normal conditions which include normal room temperature
in the case of solar energy and normal wind speed at plain area in the case of wind energy. However, designing
an optimal micro grid is not an easy task, due to the fact that primary energy carriers are changeable and
uncontrollable, as is the demand. Traditional design and optimization tools, developed for controlled power
sources, cannot be employed here. Simulation methods seem to be the best solution.
The dynamic model of the proposed system is first elaborated in the stationary reference frame and
then transformed into the synchronous orthogonal reference frame. The transformed variables are used in
control of the voltage source converter as the heart of the interfacing system between DG resources and utility
grid. By setting an appropriate compensation current references from the sensed load currents in control circuit
loop of DG, the active, reactive, and harmonic load current components will be compensated with fast dynamic
response, thereby achieving sinusoidal grid currents in phase with load voltages, while required power of the
load is more than the maximum injected power of the DG to the grid. In addition, the proposed control method
of this paper does not need a phase-locked loop in control circuit and has fast dynamic response in providing
active and reactive power components of the grid-connected loads.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Loss issue is significant in power system since it affects the operation of power system, which ultimately can be translated to monetary effect. Incremental demand that explicitly adding the reactive load causes extra heating losses in the transmission circuit. Without appropriate remedial control, the temperature increase on transmission line cable would end with insulation failure. This phenomenon can be alleviated with a proper compensation scheme that provides optimal solution along with avoidance of under-compensation or over-compensation. Evolutionary Programming (EP) has been recognised as one of the powerful optimisation technique, applied in solving power system problems. Nevertheless, EP is an old technique that sometimes could reach to a settlement that is not fully satisfied. Thus, the need fora new approach to improve the setback is urgent. This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment. The classical EP was integrated with immune algorithm so as to reduce the computational burden experienced by the classical EP.The algorithm has been tested on an IEEE 12-Bus System and IEEE 14-Bus System.Comparative study was conducted between EP and IEP in terms of optimisation performance. The optimal size and location of PV determined by IEP was able to control the loss in transmission system when the load increases. Results obtained from the studies revealed the merit of the proposed IEP; indicating its feasibility for future implementation in practical system.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
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.
Islanded microgrid congestion control by load prioritization and shedding usi...IJECEIAES
The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
Minimization of real power loss and improvement of voltage authenticity of
the network are amongst the key issues confronting power systems owing to
the heavy demand development problem, contingency of transmission and
distribution lines and the financial costs. The distributed generators (DG) has
become one of the strongest mitigating strategies for the network power loss
and to optimize voltage reliability over integration of capacitor banks and
network reconfiguration. This paper introduces an approach for the
optimizing the placement and sizes of different types of DGs in radial
distribution systems using a fine-tuned particle swarm optimization (PSO).
The suggested approach is evaluated on IEEE 33, IEEE 69 and a real
network in Malaysian context. Simulation results demonstrate the
productiveness of active and reactive power injection into the electric power
system and the comparison depicts that the suggested fine-tuned PSO
methodology could accomplish a significant reduction in network power loss
than the other research works.
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.
IMPROVED SWARM INTELLIGENCE APPROACH TO MULTI OBJECTIVE ED PROBLEMSSuganthi Thangaraj
Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Metaheuristic optimization techniques especially Improved Particle Swarm Optimization (IPSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of IPSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper. This paper illustrates successful implementation of the Improved Particle Swarm Optimization (IPSO) to Economic Load Dispatch Problem (ELD). Power output of each generating unit and optimum fuel cost obtained using IPSO algorithm has been compared with conventional techniques. The results obtained shows that IPSO algorithm converges to optimal fuel cost with reduced computational time when compared to PSO and GA for the three, six and IEEE 30 bus system.
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.
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.
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.
Grid reactive voltage regulation and cost optimization for electric vehicle p...nooriasukmaningtyas
Expecting large electric vehicle (EV) usage in the future due to environmental issues, state subsidies, and incentives, the impact of EV charging on the power grid is required to be closely analyzed and studied for power quality, stability, and planning of infrastructure. When a large number of energy storage batteries are connected to the grid as a capacitive load the power factor of the power grid is inevitably reduced, causing power losses and voltage instability. In this work large-scale 18K EV charging model is implemented on IEEE 33 network. Optimization methods are described to search for the location of nodes that are affected most due to EV charging in terms of power losses and voltage instability of the network. Followed by optimized reactive power injection magnitude and time duration of reactive power at the identified nodes. It is shown that power losses are reduced and voltage stability is improved in the grid, which also complements the reduction in EV charging cost. The result will be useful for EV charging stations infrastructure planning, grid stabilization, and reducing EV charging costs.
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
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Improvement of voltage profile for large scale power system using soft computing approach
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 1, February 2020, pp. 376~384
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i1.13379 376
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Improvement of voltage profile for large scale power system
using soft computing approach
Muhammad Abdillah1
, Herlambang Setiadi2
, Danang Sulistyo3
1
Department of Electrical Engineering, Universitas Pertamina, Indonesia
2
Department of Engineering, Faculty of Vocational Studies, Universitas Airlangga, Indonesia
3
PT. Pakoakuina, Indonesia
Article Info ABSTRACT
Article history:
Received Jun 21, 2019
Revised Nov 17, 2019
Accepted Nov 30, 2019
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.
Keywords:
JAMALI 500 kV
Power loss
Reactive power
Shunt capacitor
This is an open access article under the CC BY-SA license.
Corresponding Author:
Herlambang Setiadi,
Department of Engineering, Faculty of Vocational Studies,
Universitas Airlangga,
Campus B UNAIR, 65 Srikana St., 60286, Surabaya, Indonesia.
Email: herlambang.setiadi@vokasi.unair.ac.id
1. INTRODUCTION
In electric power systems, transmission lines play a key role to distribute electrical energy from power
plants to consumers. Electrical energy distributed by transmission lines consists of active and reactive powers.
In fact, the place of electric power plants is spatially isolated from the consumer. This causes
an enormous challenge in electricity transportation over a long distance which could affect the level of
performance and security of the system. Reactive power is not only generated by the impedance of a large
power system network but also produced by electrical devices such as motor, transformer and other power
electronic components. Hence, this power may have a great impact on the system performance. Reactive power
consumed by all electrical loads is supplied by generation units when there are no sources of reactive power
on electrical load from the transmission line system. The current flowing in the transmission lines increases
due to reactive power on electrical load increases which initiates large reactive current flowing in
2. TELKOMNIKA Telecommun Comput El Control
Improvement of voltage profile for large scale power system using soft computing… (Muhammad Abdillah)
377
the transmission lines. A large amount of reactive currents flowing in the transmission line causes decreasing
in the power factor, increasing network loss and voltage drop. Therefore, the desired voltage profile on
the consumer side becomes inappropriate. To overcome this problem, the shunt capacitor is an important device
to install in the transmission line as reactive power compensation [1]. An appropriate planning methodology
should be conducted for merging shunt capacitors as reactive power compensation into a power system network
in order to get its benefit. The installation of these compensating devices at non-appropriate areas with incorrect
sizing leads to negative consequences such as an increase in power loss and voltage instability. There were
classical approaches for solving reactive power problems such as mixed-integer programing, non-linear
programing, linear programing and quadratic programing [2-4]. Nevertheless, these approaches have some
issues in solving the objective functions that were trapped in local minima. To tackle the inherent limitations
of these solution methods, some simplification has been used to all these practices. Divergence and local
minimum could emerge due the simplification of the problems. Additionally, the conventional method is
consuming computation burden time for finding the solution.
Nowadays, many new soft computing methods have been used for solving optimization problems and
widely employed to handle various problems in engineering fields. Smart computation can be divided into
three categories: first categories is biologically inspired approaches such as grey wolf optimization, fruit fly
algorithm and social spider algorithm. Second categories is physically inspired such as simulated annealing
algorithm, and lastly social inspired such as imperialist competitive algorithm, and tabu search algorithm [5].
There are a number of researches that utilizing soft computing based on biological inspired approaches to solve
optimization problems such as genetic algorithm (GA) to determine the optimal generator output [6], ant colony
optimization (ACO) for reactive power management [7], differential evolution (DE) algorithm to solve
non-convex and high non-linear problems [8, 9], particle swarm optimization (PSO) for reactive power
dispatch [10], biogeography based optimization (BBO) for optimal VAR control [11], harmony search
algorithm (HSA) for reactive dispatch [12], hybrid tabu search algorithm (TS) and simulated annealing
algorithm (SA) for optimal reactive power problem [13], teaching learning based optimization algorithm
(TLBO) for reactive power planning [14], group search optimization (GSO) for power and emission
dispatch [15], honey bee mating optimization (HBMO) for power loss minimization [16], gravitational search
algorithm (GSA) to determine the optimal FACTS for reactive power planning [17], artificial bee colony
algorithm (ABC) for reactive power flow [18], cuckoo optimization algorithm (COA) [19] and artificial
immune system (AIS) [20] for distribution network reconfiguration problem.
Moreover, the application of soft computing in optimizing the size of the shunt capacitor has been
investigated by many researches as reactive power compensation as reported in [21]. In [21] the bacterial
foraging algorithm is used to locate as well as sizing the capacity of the capacitor in the radial distribution
system. The application of fuzzy logic for placement of the capacitor in the radial distribution system is reported
in [22]. Moreover, the application of a whale optimization algorithm for the siting of capacitors in the radial
distribution network is reported in [23]. In this paper, three computing methods i.e GA, PSO and ABC are
employed to find the optimal size of the shunt capacitor as reactive power compensation. The GA, PSO, and
ABC are used in this study because they have been popular in academia and industry because of its ability to
effectively solve highly non-linear problems. Some benefits of GA are defined as follow: a) it has
the aptitude to elude being trapped in local optimal due to GA search parallel from a population of points unlike
traditional and other optimization methods, which search from a single point and affect the methods to trapped
on local optima, b) it uses probabilistic preference rules rather than deterministic ones, c) the potential solution
parameters are encoded to chromosome rather than the parameters themselves, d) the fitness score obtained
from objective functions is utilized without other derivative or auxiliary information. Meanwhile, the GA has
drawbacks due to it has many parameters that should be set appropriately and has expensive computational
cost. Furthermore, the PSO method has attracted much attention from researcher communities due to it has few
parameters to adjust, it can be simple to implement, it can converge fast, it doesn’t need a crossover and mutate,
it has higher probability and efficiency in finding global optima, and it has short computational time. Those
are the advantages of PSO compared to GA. While the usage of ABC due to ABC has the same effectiveness
(finding the true global optimal solution) as the PSO. Both PSO and ABC are having significantly better
computational efficiency (fewer function evaluations) than GA.
2. RESEARCH METHOD
The objective function is to minimize the active power loss (Ploss) of the transmission line.
Reactive power compensation is obtained by installing the shunt capacitor on Java-Madura-Bali (JAMALI)
500 kV power system grid to reduce the losses of Ploss. The active power loss (Ploss) can be
calculated using (1).
3. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 1, February 2020: 376 - 384
378
2 2
1
[( ) 2 cos ]
Nl
loss k k i j k i j ij
k
P g t V V t V V
=
= + − (1)
In (1), N1 is the number of transmission lines, gk is conductance of branch k between i and j, tk is the tap ratio
of transformer k, Vi is the voltage magnitude at bus i, and θij is the difference of voltage angle between
buses i and j, respectively. By obtaining the minimum objective function, the determination of the size of
the shunt capacitor as reactive power compensation is essential. Furthermore, the equality constraint in optimal
power flow can be described in (2) and (3).
1
( cos sin ) 0
bus
i i
N
g d i j ij ij ij ij
j
P P V V G B
=
− − + = , for i=1,…, Npv+Npq (2)
1
( sin cos ) 0
bus
i i i
N
g d c i j ij ij ij ij
j
Q Q Q V V G B
=
− + − + = , for i=1,…, Npq (3)
where Npv and Npq are the number of generators and load buses, respectively. While the inequality constraint
of power flow can be calculated using (4), (5), (6) and (7).
min max
, , ,g slack gen slack g slackP P P (4)
min max
i i iL L LV V V
, for i=1,…, Npq (5)
min max
i i ig g gQ Q Q , for i=1,…,Ngen (6)
max
line lineS S , for i=1,…, Nline (7)
The inequality constraint as the control variable can be described in (8), (9), and (10):
min max
i i igen gen genV V V , for i=1,…, Npv (8)
min max
i i ik k kt t t , for i=1,…, Ntf (9)
min max
i i ic c cQ Q Q , for i=1,…, Ncomp (10)
where Ntf and Ncomp are the number of tap transformer and reactive compensating devices, respectively.
3. THE PROPOSED ALGORITHM
3.1. Genetic algorithm (GA)
The genetic algorithm (GA) is a soft computing method inspired by the theory of gen in biological
sciences [6] where introduced by John Holland in 1970. Chromosome variation will affect the reproduction
rate and level of ability of the organism to survive. The control parameters of GA consist of population size,
crossover, and mutation. Basically, there are four conditions that affect the evaluation process of GA:
- Organism's ability to reproduce.
- The existence of populations of organisms that can perform reproduction.
- The diversity of organisms within a population.
- Different inability to survive.
Stronger individuals would have the level of survival and reproduction rates are higher when
compared to an individual who is not strong. At a certain time (generation), the overall population will contain
more fit organ-isms. Processing steps of Genetic Algorithm are defined as follow:
- Encoding problem solution into a set of chromosome structures
- GA initialized to a population with a few N chromosomes
- Each chromosome will be encoded into an individual with a specific fitness value.
4. TELKOMNIKA Telecommun Comput El Control
Improvement of voltage profile for large scale power system using soft computing… (Muhammad Abdillah)
379
- Selecting individuals with the best fitness value. The method used is different, for example by using
the method roulette wheel.
- To generate a new population, it is necessary to use the genetic
a. Cross Over: generate new offspring by replacing some of the information from the parent chromosomes
that are crossed by.
b. Mutation: create new individuals by modifying one or more genes in the chromosome.
3.2. Particle swarm optimization
The second optimization approach employed in this paper is particle swarm optimization (PSO)
proposed by Kennedy and Eberhart in 1995 [10] where this algorithm mimics the behavior of bird flocking.
This algorithm is a population-based search approach where each individual in a population is presented as a
particle. Each particle in a swarm flies around in a multi-dimensional search space by memorizing its own
experience and the experience of neighboring particles [10]. Furthermore, the flowchart of PSO is depicted in
Figure 1.
Figure 1. Flowchart of PSO
The velocity of a particle to move can be evaluated using information from: (i) the present velocity,
(ii) the distance between the starting position with the best position that has been found. Based on the concept
of PSO, the mathematical representation of particle velocity and particle position can be expressed using (11)
and (12),
1
1 1 2 2( ) ( )i
k k k
i i best i best iv v c r P x c r G x+
= + − + − (11)
1 1k k
i i ix x v+ +
= + (12)
in (11) and (12), w is inertia weight, c is the speed constant, the rand is a uniform random value in the range
[0, 1], Pbest is the best position of the i-th particle and Gbest is the best position of all Pbest.
START
Inisialisation of
Current Position
and Velocity
Objective
Function
Position Update
Individual Best Update
Velocity Update
Global Best Update
Max Iter
STOP
Yes
No
5. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 1, February 2020: 376 - 384
380
3.3. Artificial bee colony
The third optimization method utilized in this study is an artificial bee colony algorithm introduced
by Karaboga [18] where this algorithm mimics the behavior of bees in searching for the food. In the ABC
algorithm, the colonies of artificial bees are classified into three categories of bees i.e the employed bees,
the onlooker bees, and the scout bees. The employed bees seek the new food source that never prior to being
visited, while the onlooker bees that are waiting in the dance area are to make decisions in the preference of
food sources site. The third bees are the scout bees that are doing random searching for the food sources. Noted
that only one employed bee exists for each food source. Thus, it could be emphasized that the number of food
sources around the nest equals the set of employed bees in the colony. When the employed bees run out of their
food sources, then, they become the scout bees [18]. The location of a food source denotes a potential solution
to the optimization issue. The number of food sources called the nectar corresponds to the quality (fitness) of
the associated solution. Furthermore, the main steps of ABC are described below:
- Initialize the location for food source.
- Devolve the employed bees onto their food sources and specify the number of their nectars. A new food
source of each employed bee is described as (13). The new solution is compared to the solution xij after
the result in vij and the employed bee exploits the better source.
( )ij ij ij ij kjv x x x= + − (13)
- Devolve the onlooker bees towards the food sources and specify the number of their nectars. In this step,
the probability is employed by an onlooker bee to pick a food source and yields a new source in the location
of the chosen food source. While for the employed bee, the preferred food source is defined to be exploited
by (14).
1
i
i SN
ii
fit
P
fit
=
=
(14)
- Determine the food source to be forsaken and allocate its employed bee as a scout for finding the new food
sources based on a random search by (15).
maxmin min[0,1]( )j jj j
ix x rand x x= + − (15)
- Memorize the best food source found so far.
- Go steps 2-until the termination criteria are satisfied.
4. NUMERICAL RESULTS
In this paper, the test system is Java-Madura-Bali (JAMALI) 500kV power grid as depicted in
Figure 2. The data of the JAMALI 500kV power grid is taken from [24]. Simulation is conducted by using a
MATLAB software environment. Furthermore, the appropriate control parameter plays key role in
the computation techniques and is very sensitive problem of finding a good solution for the soft computing
technique. The parameters of soft computing approaches used for the simulations are defined as follow:
GA parameters:
NGen=Dimension of problem; Crossover probability = 0.8; Population siz = 50;
Mutation probability = 0.05; Maximum generations = 150
PSO parameters:
NVariabel = Dimension of problem; Social parameter (C2) = 0.9; Weight (w)= 0.9;
Cognitive parameter (C1) =1.5; Population size = 50; Maximum iterations = 150;
ABC parameters:
Dimension (D) = Dimension of problem; FoodNumber = NP/2; limit = FoodNumber*D;
colony size (NP) = 50; Maximum cycles = 150;
The dimension search space (Dim) of each algorithm depends on the number of compensating devices
corresponding to the number of bus systems that have voltage value (p.u) lower than voltage reference standard
around -5% of its nominal value.
6. TELKOMNIKA Telecommun Comput El Control
Improvement of voltage profile for large scale power system using soft computing… (Muhammad Abdillah)
381
Figure 2. Single line diagram of JAMALI 500 kV transmission system [25]
The evaluation of fitness for each population of the GA, PSO, and ABC algorithms is frequently
conducted in one iteration. The convergence characteristic of three soft computing techniques is compared to
the number of fitness evaluations due to the fitness evaluation is consuming the optimization process time.
The convergence behavior of all soft computing approaches is depicted in Figure 3. Figure 3 illustrates that all
soft computing approaches obtained satisfactory performances to reach their convergence values for the chosen
parameters. The convergence characteristics of GA are faster than ABC but may not investigate deeply for
potential candidates as found by ABC. While PSO towards convergence value quickly and explores a good
potential solution rather than other soft computing methods. Table 1 shows the comparison of total loss before
and after the installing of capacitors from each of these methods. The results obtained are that the GA method
can reduce the transmission line losses 11.38%. A better result is obtained by using PSO and ABC algorithm
Paiton
Grati
Surabaya Barat
Gresik
Tanjung jati
Ungaran
Kediri
Pedan
Mandiracan
Saguling
Tasikmalaya
Cirata
Cibatu
Muaratawar
Bekasi
Bandung
Depok
Gandul
Cilegon
Suralaya
Kembangan
Cawang
Cibinong
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
7. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 1, February 2020: 376 - 384
382
with a percentage decrease of 11.63%. While Table 2 depicts the capacity of capacitors installed on each of the
critical buses. The comparison of the voltage level on each result is depicted in Figure 4. It is found that after
the system is compensated, the voltage drops decrease in order to obtain better performance of voltage.
Figure 3. Convergence characteristics of algorithms
Figure 4. Comparison of voltages level
Table 1. Comparison of total active power loss
Before GA PSO ABC
Total Loss (MW) 136.539 120.999 120.666 120.666
The difference of total loss (MW) - 15.54 15.873 15.873
% - 11.38 11.63 11.63
8. TELKOMNIKA Telecommun Comput El Control
Improvement of voltage profile for large scale power system using soft computing… (Muhammad Abdillah)
383
Table 2. Optimization of shunt capacitor’s size
Unit Bus Compensation Compensation Compensation
GA PSO ABC
(MVAR) (MVAR) (MVAR)
1 13 370.451 400 400
2 14 376.878 400 400
3 19 399.272 248.244 248.245
4 20 386.468 400 400
5 21 369.731 400 400
Total 1902.8 1848.244 1848.245
5. CONCLUSION
In this paper, the use of three different soft computing techniques to overcome the reactive power
compensation issue in the transmission system has been investigated. From the simulation result, it is shown
that the GA method to reach convergence on the 20th iteration, PSO on the 3rd iteration and ABC on the 23rd
iteration. The ABC dan PSO algorithms can reduce the total active power loss by 15.873 MW, from
136.539 MW to 120.666 MW. These results obtained are better than the GA approach where it only can reduce
by 15.54 MW, from 136.539 MW to 120.999 MW. From all the simulation results, the PSO algorithm is very
superior rather than the other methods in the viewpoint of the selected set of parameters to tackle the reactive
power compensation issue in the transmission system.
ACKNOWLEDGEMENTS
The authors thank the anonymous reviewers for their precious comments and suggestions for
the improvement of this paper.
REFERENCES
[1] M. Dixit, et al., "Optimal Integration of Shunt Capacitor Banks in Distribution Networks for Assessment of
Techno-Economic Asset," Computers & Electrical Engineering, vol. 71, pp. 331-345, Oct 2018.
[2] D. S. Kirschen, et al., “MW/Voltage Control in Linear Programming Based Optimal Power Flow,” IEEE Trans. Power
Syst., vol. 3, no. 2, pp. 481–489, May 1988.
[3] N. Grudinin, "Reactive power optimization using successive quadratic programming method," in IEEE Transactions
on Power Systems, vol. 13, no. 4, pp. 1219-1225, Nov 1998.
[4] K. Aoki, M. Fan and A. Nishikori, "Optimal VAr planning by approximation method for recursive mixed-integer
linear programming," in IEEE Transactions on Power Systems, vol. 3, no. 4, pp. 1741-1747, Nov 1988.
[5] H. Setiadi, et al., “Power System Design using Firefly Algorithm for Dynamic Stability Enhancement,” Indonesian
Journal of Electrical Engineering and Computer Science, vol. 1, no.3, pp. 446-455, Mar 2016.
[6] A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas and V. Petridis, "Optimal power flow by enhanced genetic algorithm,"
in IEEE Transactions on Power Systems, vol. 17, no. 2, pp. 229-236, May 2002.
[7] A. Ketabi, et al., “Application of The Ant Colony Search Algorithm to Reactive Power Pricing in an Open Electricity
Market,” International Journal of Electrical Power & Energy Systems, vol. 32, pp. 622-628, July 2010.
[8] A. A. Abou El Ela, et al., “Optimal Power Flow using Differential Evolution Algorithm,” Electr. Power Syst Res.,
vol. 80, no. 7, pp. 878-885, July 2010.
[9] N. H. Awada, et al., “An Efficient Differential Evolution Algorithm for Stochastic OPF Based Active–Reactive Power
Dispatch Problem Considering Renewable Generators,” Applied Soft Computing, vol. 76, pp. 445-458, 2019.
[10] M. R. Monteiro, et al., “Particle Swarm Optimization Applied to Reactive Power Dispatch Considering Renewable
Generation,” Decision Making Applications in Modern Power Systems, United Kingdom: Academic Press,
pp. 247-267, 2020.
[11] P. K. Roy, et al., “Optimal VAR Control for Improvements in Voltage Profiles and For Real Power Loss Minimization
using Biogeography Based Optimization,” International Journal of Electrical Power & Energy Systems, vol. 43,
no. 1, pp. 830-838, December 2012.
[12] A. H. Khazali, et al., “Optimal Reactive Power Dispatch Based on Harmony Search Algorithm,” International Journal
of Electrical Power & Energy Systems, vol. 33, no. 3, pp. 684-692, Mar 2011.
[13] K. Lenin, et al., “Hybrid Tabu Search-Simulated Annealing Method to Solve Optimal Reactive Power Problem,”
International Journal of Electrical Power & Energy Systems, vol. 82, pp. 87-91, November 2016.
[14] B. Bhattacharyya, et al., “Teaching Learning Based Optimization Algorithm for Reactive Power Planning,”
International Journal of Electrical Power & Energy Systems, vol. 81, pp. 248-253, Oct 2016.
[15] N. Daryani, et al., “Multi-Objective Power and Emission Dispatch using Modified Group Search Optimization
Method,” Ain Shams Engineering Journal, vol. 9, no. 3. pp. 319-328, Sep 2018.
[16] E. A. Farsani, “Loss Minimization in Distribution Systems Based on LMP Calculation using Honey Bee Mating
Optimization and Point Estimate Method,” Energy, vol. 140, pp. 1-9, Dec 2017.
[17] B. Bhattacharyya, et al., “Reactive Power Planning with FACTS Devices using Gravitational Search Algorithm,” Ain
Shams Engineering Journal, vol. 6, no. 3, pp. 865-871, Sep 2015.
9. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 1, February 2020: 376 - 384
384
[18] K. Ayan, et al., “Artificial Bee Colony Algorithm Solution for Optimal Reactive Power Flow,” Applied Soft
Computing, vol. 12, no. 5 pp. 1477-1482, May 2012.
[19] T. Thanh Nguyen, et al., “An Improved Cuckoo Search Algorithm for The Problem of Electric Distribution Network
Reconfiguration,” Applied Soft Computing, vol. 84, pp. 1-8, Nov 2019.
[20] S. S. F. Souza, et al., “Artificial Immune Algorithm Applied to Distribution System Reconfiguration with Variable
Demand,” International Journal of Electrical Power & Energy Systems, vol. 82, pp. 561-568, Nov 2016.
[21] K. R. Devabalaji, et al., “Optimal Location and Sizing of Capacitor Placement in Radial Distribution System using
Bacterial Foraging Optimization Algorithm,” International Journal of Electrical Power & Energy Systems, vol. 71,
pp. 383-390, Oct 2015.
[22] S. K. Bhattacharya, et al., “A New Fuzzy Based Solution of The Capacitor Placement Problem in Radial Distribution
System,” Expert Systems with Applications, vol. 36, no. 3, pp. 4207-4212, Apr 2009.
[23] D. B. Prakash, et al., “Optimal Siting of Capacitors in Radial Distribution Network using Whale Optimization
Algorithm,” Alexandria Engineering Journal, vol. 56, no. 4, pp. 499-509, Dec 2017.
[24] M. A. Juningtijastuti, et al., “Optimal Sizing of Static Var Compensators (SVCs) for Reducing Power Losses in 500
kV JAMALI Grid Power System using Bacteria Foraging Algorithm (BFA),” Proceeding of National Seminar of
Mathematics, University of Indonesia, 2010.
[25] D. Lastomo, Widodo and H. Setiadi, "Optimal Power Flow using Fuzzy-Firefly Algorithm," 2018 5th
International
Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Malang, Indonesia,
pp. 210-215, 2018.
BIOGRAPHIES OF AUTHORS
Muhammad Abdillah was born in Pasuruan. He received Sarjana Teknik
(equivalent to B.Eng.), and Magister Teknik (equivalent to M.Eng.) degrees from Department of
Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia in 2009
and 2013, respectively. He obtained Dr. Eng. degree from Graduate School of Engineering,
Hiroshima University, Japan in 2017. He is currently working as lecturer at Department of
Electrical Engineering, Universitas Pertamina, Jakarta, Indonesia. As author and co-author,
he had published 70 scientific papers in different journals and conferences. He was a member of
IEEJ, IAENG and IEEE. His research interests are power system operation and control,
power system optimization, robust power system security, power system stability,
intelligent control and system, and artificial intelligences (optimization, machine learning, and
deep learning).
Herlambang Setiadi was born in Sidoarjo, in November 1990. He received a Bachelor degree
from Sepuluh Nopember Institute of Technology (Surabaya, Indonesia) majors in Power System
Engineering in 2014. Then a Master degree from Liverpool John Moores University
(Liverpool, United Kingdom), majors in Electrical Power and Control Engineering in 2015.
Furthermore, he received his Doctoral degree from The University of Queensland, majors in
Electrical Engineering in 2019. Currently, he is a lecturer at the Department of Engineering,
Universitas Airlangga. His research interests include small signal stability in power systems,
renewable energy integration, control system engineering and metaheuristic algorithms.
The author can be contacted at herlambang.setiadi @vokasi.unair.ac.id.
Danang Sulistyo was born in Madiun. He received Sarjana Teknik (equivalent to B.Eng.) from
Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (Surabaya,
Indonesia) majors in Power System Engineering in 2010. During his bachelor studied period,
he had involved in the research area related to artificial intelligence that was applied to power
system optimization. He is currently working as process engineer at PT. Pakoakuina,
Jakarta, Indonesia.