Nowadays, a power system is operating in a stressed condition due to the increase in demand in addition to constraint in building new power plants. The economics and environmental constraints to build new power plants and transmission lines have led the system to operate very close to its stability limits. Hence, more researches are required to study the important requirements to maintain stable voltage condition and hence develop new techniques in order to address the voltage stability problem. As an action, most Reactive Power Planning (RPP) objective is to minimize the cost of new reactive resources while satisfying the voltage stability constraints and labeled as Secured Reactive Power Planning (SCRPP). The new alternative optimization technique called Adaptive Tumbling Bacterial Foraging (ATBFO) was introduced to solve the RPP problems in the IEEE 57 bus system. The comparison common optimization Meta-Heuristic Evolutionary Programming and original Bacterial Foraging techniques were chosen to verify the performance using the proposed ATBFO method. As a result, the ATBFO method is confirmed as the best suitable solution in solving the identified RPP objective functions.
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.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
The effect of load modelling on phase balancing in distribution networks usin...IJECEIAES
Due to the unequal loads in phases and different customer consumption, the distribution network is unbalanced. Unbalancing in the distribution network, in addition to increasing power losses, causes unbalancing in voltages and increases operating costs. To reduce this unbalancing, various methods and algorithms have been presented. In most studies and even practical projects due to lack of information about the network loads, load models such as constant power model, constant current or constant impedance are used to model the loads. Due to the changing and nonlinear behaviours of today's loads, these models cannot show results in accordance with reality. This paper while introducing an optimal phase-balancing method, discusses the effect of load modelling on phase balancing studies. In this process the re-phasing method for balancing the network and the harmony search algorithm for optimizing the phase displacement process have been used. The simulation was carried out on an unbalanced distribution network of 25 buses. The results show well the effect of this comprehensive modelling on phase balancing studies. It also shows that in the re-phasing method for balancing the network and in the absence of a real load model, the use of which model offers the closest answer to optimal solutions.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
The effect of load modelling on phase balancing in distribution networks usin...IJECEIAES
Due to the unequal loads in phases and different customer consumption, the distribution network is unbalanced. Unbalancing in the distribution network, in addition to increasing power losses, causes unbalancing in voltages and increases operating costs. To reduce this unbalancing, various methods and algorithms have been presented. In most studies and even practical projects due to lack of information about the network loads, load models such as constant power model, constant current or constant impedance are used to model the loads. Due to the changing and nonlinear behaviours of today's loads, these models cannot show results in accordance with reality. This paper while introducing an optimal phase-balancing method, discusses the effect of load modelling on phase balancing studies. In this process the re-phasing method for balancing the network and the harmony search algorithm for optimizing the phase displacement process have been used. The simulation was carried out on an unbalanced distribution network of 25 buses. The results show well the effect of this comprehensive modelling on phase balancing studies. It also shows that in the re-phasing method for balancing the network and in the absence of a real load model, the use of which model offers the closest answer to optimal solutions.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
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.
Optimal SVC allocation via symbiotic organisms search for voltage security im...TELKOMNIKA JOURNAL
It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations.
IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...IRJET Journal
This document discusses contingency analysis and optimal placement of renewable distributed generators (RDGs) using continuation power flow analysis to improve voltage stability and loadability. It presents a methodology to determine the optimal location and mix of different RDG technologies (solar, wind, fuel cells) on the IEEE 9-bus test system using the Power System Analysis Toolbox (PSAT). Reactive power performance indices are calculated for different line contingencies to identify critical buses. The results show that optimally placing RDGs can enhance voltage stability and increase the maximum loadability point compared to the base case without RDGs.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
This document presents a matrix methodology for allocating the costs of reactive power flows in transmission networks. The methodology traces reactive power flows through the network using Kirchhoff's current law and proportional sharing principles. It then allocates the costs of reactive power to generators and loads using the MVAr-mile method. The methodology is demonstrated on sample 6-bus and IEEE 14-bus test systems. Results show the allocated reactive power flows to different loads and the costs allocated to loads for recovery of total reactive power costs in the transmission network.
A progressive domain expansion method for solving optimal control problemTELKOMNIKA JOURNAL
1) The document discusses a progressive domain expansion method for solving optimal control problems and applying it to managing water flows between the Kainji and Jebba hydropower reservoirs in Nigeria.
2) It presents the system dynamics model and formulates an optimal control problem to determine the best water inflow control from Kainji to keep Jebba's operating head at a nominal level.
3) Solving the optimal control problem results in a two-point boundary value problem that is solved using progressive domain expansion, which is a modification of the shooting method. The method determines the optimal inflow control to maximize power generation at Jebba.
Bulk power system availability assessment with multiple wind power plants IJECEIAES
The use of renewable non-conventional energy sources, as wind electric power energy and photovoltaic solar energy, has introduced uncertainties in the performance of bulk power systems. The power system availability has been employed as a useful tool for planning power systems; however, traditional methodologies model generation units as a component with two states: in service or out of service. Nevertheless, this model is not useful to model wind power plants for availability assessment of the power system. This paper used a statistical representation to model the uncertainty of power injection of wind power plants based on the central moments: mean value, variance, skewness and kurtosis. In addition, this paper proposed an availability assessment methodology based on application of this statistical model, and based on the 2m+1 point estimate method the availability assessment is performed. The methodology was tested on the IEEE-RTS assuming the connection of two wind power plants and different correlation among the behavior of these plants.
Power system operation considering detailed modelling of the natural gas supp...IJECEIAES
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
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.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a comprehensive transmission expansion planning (CTEP) strategy proposed for developing countries. The strategy considers physical and operational constraints in the transmission system like power balance, generation limits, transmission line flow limits, right-of-way constraints, and voltage limits. The CTEP is applied to the Garver 6-bus test system considering various contingencies such as generator outages, line outages, load changes, and identifies optimal transmission line expansions. The CTEP aims to achieve optimal planning costs while improving reliability and reducing transmission losses. AC load flow is used to evaluate the CTEP using the Newton-Raphson method.
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.
A Hybrid Control Scheme for Fault Ride-Through Capability using Line-Side Con...Suganthi Thangaraj
As the wind power installations are increasing in number, Wind Turbine Generators (WTG) are required to have Fault Ride-Through (FRT) capabilities. Lately developed grid operating codes demand the WTGs to stay connected during fault conditions, supporting the grid to recover faster back to its normal state. In this paper, the generator side converter incorporates the maximum power point tracking algorithm to extract maximum energy from wind turbine system. A hybrid control scheme for energy storage systems (ESS) and braking choppers for fault ride-through capability and a suppression of the output power fluctuation is proposed for permanent-magnet synchronous generator (PMSG) wind turbine systems. During grid faults, the dc-link voltage is controlled by the ESS instead of the line-side converter (LSC), whereas the LSC is exploited as a STATCOM to inject reactive current into the grid for assisting in the grid voltage recovery. A simple model of the proposed system is developed and simulated in MATLAB environment. The effectiveness of the system is validated through extensive simulation results
A Research on Optimal Power Flow Solutions For Variable LoaIJERA Editor
This document discusses research on using optimization techniques to solve the optimal power flow problem under variable load conditions. It proposes combining the continuation method with an interior point algorithm to track optimal power flow solutions as the load parameter is increased. This would allow analyzing system behavior near the maximum loadability limit. The research aims to study optimal power flow behavior near limits, evaluate the proposed methodology's efficiency, and analyze critical bus indices and sensitivity of maximum load to reactive power injections. Results show the proposed approach can track solutions continuously for load increases where no new operational limits become active.
Power Flow Analysis of Island Business District 33KV Distribution Grid System...IJERA Editor
The solution to power flow is one of the most important problems in electrical power systems. Traditional methods have been previously used for power flow analysis, but with prevalent drawbacks such as abnormal operating solutions and divergences in heavy loads. This paper presents power flow analysis in a power system, by modelling a typical 33kV Distribution Network, and simulating using the NEPLAN software for power flow studies. Island Business Unit’s (IBU) 33kV network of Eko Electricity Distribution Plc (EKEDP) for a scenario day is taken as case study in the analysis. The most important parameters of power flow analysis is utilized to find the magnitude and phase angles of the voltages at each Busbar, as well as the real and reactive power flowing through each distribution line within the network under consideration.
Design & Simulation of Energy Storage Unified Power Quality Conditioner (EUPQ...IJERA Editor
Rapid consumption of energy from conventional sources can be limited by connecting more no. of distributed generation systems with the support of smart grid technology. But the impact of variation in DG power out putted may lead to power quality problems in the distributed system in which it is connected. In addition to this power system faults, non- linear loads and non-linear characteristics of converter circuits used in DG s further deteriorate quality of the power. Implementation of UPQC in the network itself solves the problems addressed but crowding of more no of DG in the network will suppress the effect of UPQC. However energy storage system integration can suppress the large power fluctuations outputted by DGs. In this paper energy storage based unified power quality conditioner (EUPQC) has been implemented using fuggy logic controller. For energy storage ultra (Super) capacitor has been used for fast rate of charging and discharging. The performance of the implemented UPQC with fuggy logic controller is compared with PI controller with the MATLAB simulation.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
The document summarizes research on using a genetic algorithm to optimize the location and parameters of Flexible AC Transmission System (FACTS) devices in a power system. It first introduces FACTS devices and their ability to control power flow. It then describes using a genetic algorithm to simultaneously determine the optimal type, location, and rating of FACTS devices with the objectives of minimizing generation costs and power losses/voltage deviations. The methodology is tested on the IEEE 30-bus system with different FACTS device types. The results indicate the genetic algorithm approach can effectively determine the configuration of FACTS devices that increase system loadability.
MPPT for PV System Based on Variable Step Size P&O AlgorithmTELKOMNIKA JOURNAL
This paper presents some improvements on the Perturb and Observe (P&O) method to overcome the common drawbacks of conventional P&O method. The main advantage of this modified algorithm is its simplicity with higher accuracy results, compared to the conventional methods. The operation of the entire solar Maximum Power Point Tracking (MPPT) system was observed through two different approaches, which are through MATLAB/Simulink simulation and hardware implementation. A small scale of hardware design, which consists of solar PV cell, boost converter and Arduino Mega2560 microcontroller, had been utilized for further verification on the simulation results. The simulation results that was carried out by this modified P&O algorithm showed improvement and a promising performance: faster convergence speed of 0.67s, small oscillation at steady state region and promising efficiency of 95.23%. Besides, from the hardware results, the convergence time of the power curve was able to maintain at 0.2s and give almost zero oscillation during steady state. It is envisaged that the method is useful in future research of Photovoltaic (PV) system.
Power quality improvement of grid interconnected distribution system using fs...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A novel methodology for maximization of Reactive Reserve using Teaching-Learn...IOSR Journals
This document presents a novel methodology for maximizing reactive reserve using a teaching-learning-based optimization algorithm. The methodology aims to both maximize reactive reserves at generators based on their participation factors, and maintain a desired voltage stability margin. It formulates reactive reserve maximization as an optimization problem with objectives and constraints. A teaching-learning-based optimization approach is applied to find the global optimum solution more efficiently than conventional methods, given the large-scale, non-linear nature of the problem. The methodology is tested on standard 6-bus test systems.
Meta-heuristic optimization Methods for Under Voltage Load Shedding Scheme (I...Raja Larik
This document discusses various meta-heuristic optimization methods that have been applied to under voltage load shedding (UVLS) schemes in power systems. It provides an overview of genetic algorithms, particle swarm optimization, ant colony optimization, big bang big crunch optimization, and fuzzy logic control as meta-heuristic techniques that can be used for UVLS. The document compares these meta-heuristic techniques to conventional UVLS approaches, noting that meta-heuristics can provide optimal load shedding, deal efficiently with large complex power systems, and accurately calculate power imbalances.
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.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
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.
Optimal SVC allocation via symbiotic organisms search for voltage security im...TELKOMNIKA JOURNAL
It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations.
IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...IRJET Journal
This document discusses contingency analysis and optimal placement of renewable distributed generators (RDGs) using continuation power flow analysis to improve voltage stability and loadability. It presents a methodology to determine the optimal location and mix of different RDG technologies (solar, wind, fuel cells) on the IEEE 9-bus test system using the Power System Analysis Toolbox (PSAT). Reactive power performance indices are calculated for different line contingencies to identify critical buses. The results show that optimally placing RDGs can enhance voltage stability and increase the maximum loadability point compared to the base case without RDGs.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
This document presents a matrix methodology for allocating the costs of reactive power flows in transmission networks. The methodology traces reactive power flows through the network using Kirchhoff's current law and proportional sharing principles. It then allocates the costs of reactive power to generators and loads using the MVAr-mile method. The methodology is demonstrated on sample 6-bus and IEEE 14-bus test systems. Results show the allocated reactive power flows to different loads and the costs allocated to loads for recovery of total reactive power costs in the transmission network.
A progressive domain expansion method for solving optimal control problemTELKOMNIKA JOURNAL
1) The document discusses a progressive domain expansion method for solving optimal control problems and applying it to managing water flows between the Kainji and Jebba hydropower reservoirs in Nigeria.
2) It presents the system dynamics model and formulates an optimal control problem to determine the best water inflow control from Kainji to keep Jebba's operating head at a nominal level.
3) Solving the optimal control problem results in a two-point boundary value problem that is solved using progressive domain expansion, which is a modification of the shooting method. The method determines the optimal inflow control to maximize power generation at Jebba.
Bulk power system availability assessment with multiple wind power plants IJECEIAES
The use of renewable non-conventional energy sources, as wind electric power energy and photovoltaic solar energy, has introduced uncertainties in the performance of bulk power systems. The power system availability has been employed as a useful tool for planning power systems; however, traditional methodologies model generation units as a component with two states: in service or out of service. Nevertheless, this model is not useful to model wind power plants for availability assessment of the power system. This paper used a statistical representation to model the uncertainty of power injection of wind power plants based on the central moments: mean value, variance, skewness and kurtosis. In addition, this paper proposed an availability assessment methodology based on application of this statistical model, and based on the 2m+1 point estimate method the availability assessment is performed. The methodology was tested on the IEEE-RTS assuming the connection of two wind power plants and different correlation among the behavior of these plants.
Power system operation considering detailed modelling of the natural gas supp...IJECEIAES
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
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.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a comprehensive transmission expansion planning (CTEP) strategy proposed for developing countries. The strategy considers physical and operational constraints in the transmission system like power balance, generation limits, transmission line flow limits, right-of-way constraints, and voltage limits. The CTEP is applied to the Garver 6-bus test system considering various contingencies such as generator outages, line outages, load changes, and identifies optimal transmission line expansions. The CTEP aims to achieve optimal planning costs while improving reliability and reducing transmission losses. AC load flow is used to evaluate the CTEP using the Newton-Raphson method.
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.
A Hybrid Control Scheme for Fault Ride-Through Capability using Line-Side Con...Suganthi Thangaraj
As the wind power installations are increasing in number, Wind Turbine Generators (WTG) are required to have Fault Ride-Through (FRT) capabilities. Lately developed grid operating codes demand the WTGs to stay connected during fault conditions, supporting the grid to recover faster back to its normal state. In this paper, the generator side converter incorporates the maximum power point tracking algorithm to extract maximum energy from wind turbine system. A hybrid control scheme for energy storage systems (ESS) and braking choppers for fault ride-through capability and a suppression of the output power fluctuation is proposed for permanent-magnet synchronous generator (PMSG) wind turbine systems. During grid faults, the dc-link voltage is controlled by the ESS instead of the line-side converter (LSC), whereas the LSC is exploited as a STATCOM to inject reactive current into the grid for assisting in the grid voltage recovery. A simple model of the proposed system is developed and simulated in MATLAB environment. The effectiveness of the system is validated through extensive simulation results
A Research on Optimal Power Flow Solutions For Variable LoaIJERA Editor
This document discusses research on using optimization techniques to solve the optimal power flow problem under variable load conditions. It proposes combining the continuation method with an interior point algorithm to track optimal power flow solutions as the load parameter is increased. This would allow analyzing system behavior near the maximum loadability limit. The research aims to study optimal power flow behavior near limits, evaluate the proposed methodology's efficiency, and analyze critical bus indices and sensitivity of maximum load to reactive power injections. Results show the proposed approach can track solutions continuously for load increases where no new operational limits become active.
Power Flow Analysis of Island Business District 33KV Distribution Grid System...IJERA Editor
The solution to power flow is one of the most important problems in electrical power systems. Traditional methods have been previously used for power flow analysis, but with prevalent drawbacks such as abnormal operating solutions and divergences in heavy loads. This paper presents power flow analysis in a power system, by modelling a typical 33kV Distribution Network, and simulating using the NEPLAN software for power flow studies. Island Business Unit’s (IBU) 33kV network of Eko Electricity Distribution Plc (EKEDP) for a scenario day is taken as case study in the analysis. The most important parameters of power flow analysis is utilized to find the magnitude and phase angles of the voltages at each Busbar, as well as the real and reactive power flowing through each distribution line within the network under consideration.
Design & Simulation of Energy Storage Unified Power Quality Conditioner (EUPQ...IJERA Editor
Rapid consumption of energy from conventional sources can be limited by connecting more no. of distributed generation systems with the support of smart grid technology. But the impact of variation in DG power out putted may lead to power quality problems in the distributed system in which it is connected. In addition to this power system faults, non- linear loads and non-linear characteristics of converter circuits used in DG s further deteriorate quality of the power. Implementation of UPQC in the network itself solves the problems addressed but crowding of more no of DG in the network will suppress the effect of UPQC. However energy storage system integration can suppress the large power fluctuations outputted by DGs. In this paper energy storage based unified power quality conditioner (EUPQC) has been implemented using fuggy logic controller. For energy storage ultra (Super) capacitor has been used for fast rate of charging and discharging. The performance of the implemented UPQC with fuggy logic controller is compared with PI controller with the MATLAB simulation.
Improvement of voltage profile for large scale power system using soft comput...TELKOMNIKA JOURNAL
In modern power system operation, control, and planning, reactive power as part of power system component is very important in order to supply electrical load such as an electric motor. However, the reactive current that flows from the generator to load demand can cause voltage drop and active power loss. Hence, it is essential to install a compensating device such as a shunt capacitor close to the load bus to improve the voltage profile and decrease the total power loss of transmission line system. This paper presents the application of a genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC)) to obtain the optimal size of the shunt capacitor where those capacitors are located on the critical bus. The effectiveness of the proposed technique is examined by utilizing Java-Madura-Bali (JAMALI) 500 kV power system grid as the test system. From the simulation results, the PSO and ABC algorithms are providing satisfactory results in obtaining the capacitor size and can reduce the total power loss of around 15.873 MW. Moreover, a different result is showed by the GA approach where the power loss in the JAMALI 500kV power grid can be compressed only up to 15.54 MW or 11.38% from the power system operation without a shunt capacitor. The three soft computing techniques could also maintain the voltage profile within 1.05 p.u and 0.95 p.u.
The document summarizes research on using a genetic algorithm to optimize the location and parameters of Flexible AC Transmission System (FACTS) devices in a power system. It first introduces FACTS devices and their ability to control power flow. It then describes using a genetic algorithm to simultaneously determine the optimal type, location, and rating of FACTS devices with the objectives of minimizing generation costs and power losses/voltage deviations. The methodology is tested on the IEEE 30-bus system with different FACTS device types. The results indicate the genetic algorithm approach can effectively determine the configuration of FACTS devices that increase system loadability.
MPPT for PV System Based on Variable Step Size P&O AlgorithmTELKOMNIKA JOURNAL
This paper presents some improvements on the Perturb and Observe (P&O) method to overcome the common drawbacks of conventional P&O method. The main advantage of this modified algorithm is its simplicity with higher accuracy results, compared to the conventional methods. The operation of the entire solar Maximum Power Point Tracking (MPPT) system was observed through two different approaches, which are through MATLAB/Simulink simulation and hardware implementation. A small scale of hardware design, which consists of solar PV cell, boost converter and Arduino Mega2560 microcontroller, had been utilized for further verification on the simulation results. The simulation results that was carried out by this modified P&O algorithm showed improvement and a promising performance: faster convergence speed of 0.67s, small oscillation at steady state region and promising efficiency of 95.23%. Besides, from the hardware results, the convergence time of the power curve was able to maintain at 0.2s and give almost zero oscillation during steady state. It is envisaged that the method is useful in future research of Photovoltaic (PV) system.
Power quality improvement of grid interconnected distribution system using fs...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A novel methodology for maximization of Reactive Reserve using Teaching-Learn...IOSR Journals
This document presents a novel methodology for maximizing reactive reserve using a teaching-learning-based optimization algorithm. The methodology aims to both maximize reactive reserves at generators based on their participation factors, and maintain a desired voltage stability margin. It formulates reactive reserve maximization as an optimization problem with objectives and constraints. A teaching-learning-based optimization approach is applied to find the global optimum solution more efficiently than conventional methods, given the large-scale, non-linear nature of the problem. The methodology is tested on standard 6-bus test systems.
Meta-heuristic optimization Methods for Under Voltage Load Shedding Scheme (I...Raja Larik
This document discusses various meta-heuristic optimization methods that have been applied to under voltage load shedding (UVLS) schemes in power systems. It provides an overview of genetic algorithms, particle swarm optimization, ant colony optimization, big bang big crunch optimization, and fuzzy logic control as meta-heuristic techniques that can be used for UVLS. The document compares these meta-heuristic techniques to conventional UVLS approaches, noting that meta-heuristics can provide optimal load shedding, deal efficiently with large complex power systems, and accurately calculate power imbalances.
Two-way Load Flow Analysis using Newton-Raphson and Neural Network MethodsIRJET Journal
The document presents a study comparing two-way load flow analysis using the Newton-Raphson method and a neural network method for networked microgrids. The optimal power flow problem is solved using both a conventional Newton-Raphson method and an artificial intelligence neural network method. Results show that the neural network method achieves minimum losses and higher efficiency compared to the Newton-Raphson method, with efficiencies of 99.3% and 97% respectively for the test networked microgrid system.
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.
stability of power flow analysis of different resources both on and off gridrehman1oo
This document presents a power flow optimization strategy model for a distribution network that considers source, load, and storage. The model aims to minimize total cost, voltage deviation, and power losses over time periods determined through k-means clustering of an equivalent load curve. A particle swarm optimization algorithm is used to solve the multi-objective optimization model subject to power flow, voltage, and other constraints. The model is tested on an IEEE 33-node system and is shown to improve economic and reliability performance compared to a fixed weighting approach.
In power engineering the power flow analysis (also known as load flow study) is an important tool involving numerical analysis applied to a powe r system. This project deals with a model of existing power system using the actual data taking care of all parameters required for the simulation and analysis. With the help of Maharasht ra State Electricity Transmission co. Ltd.,a model of 220KV lines,of Solapur District grid usin g MATLAB software will be modeled. In this project,an algorithm will be used for power f low study and data collection and coding required for modeling. Load flow studies will be ca rried out using Newton Raphson method and voltage profile of buses will be analyzed. New meth od for the improvement of voltage profile will be suggested and analyze using the developed m odel. The optimization techniques include power factor compensation,tap changing,up gradati on of substation,up gradation of line and load shifting will be analyzed. Importance of power flow or Load flow studies is in planning future expansion of power system as well as determi ning the best operation of existing systems. From results of simulation buses with low voltage p rofile will be identified and possible solutions can be suggested.
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...IJECEIAES
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Islanded microgrid congestion control by load prioritization and shedding usi...IJECEIAES
The document discusses congestion management in an islanded microgrid supplied by renewable energy sources using an artificial bee colony algorithm. It formulates the congestion management problem as an optimization problem that aims to minimize overloads and power losses by optimally shedding loads based on priority indices. The artificial bee colony algorithm is applied to determine the optimal amount and location of loads to shed. It is tested on a modified IEEE 30-bus distribution system in MATLAB. The results are compared to other algorithms to demonstrate the effectiveness of this approach for congestion control in islanded microgrids with intermittent renewable generation.
SVC device optimal location for voltage stability enhancement based on a comb...TELKOMNIKA JOURNAL
The increased power system loading combined with the worldwide power industry deregulation requires more reliable and efficient control of the power flow and network stability. Flexible AC transmission systems (FACTS) devices give new opportunities for controlling power and enhancing the usable capacity of the existing transmission lines. This paper presents a combined application of the particle swarm optimization (PSO) and the continuation power flow (CPF) technique to determine the optimal placement of static var compensator (SVC) in order to achieve the static voltage stability margin. The PSO objective function to be maximized is the loading factor to modify the load powers. In this scope, two SVC constraints are considered: the reference voltage in the first case and the total reactance and SVC reactive power in the second case. To test the performance of the proposed method, several simulations were performed on IEEE 30-Bus test systems. The results obtained show the effectiveness of the proposed method to find the optimal placement of the static var compensator and the improvement of the voltage stability.
This document proposes an artificial neural network and fuzzy logic controller tool for online voltage stability monitoring and estimating reactive power (VAR) support needs in deregulated power systems. The tool uses bus voltage angles and reactive power loads as inputs to the ANN, which then outputs the voltage stability margin and voltage stability factor of the most vulnerable bus. The ANN is trained offline using patterns from continuation power flow simulations. The tool can estimate stability margins and determine minimum VAR support for different system conditions and contingencies in deregulated markets. It has been tested on IEEE 14 bus and 30 bus systems.
This paper proposes a modified equilibrium algorithm (MEA) to optimally determine the placement and capacity of wind power plants in a transmission power network with 30 nodes. The paper considers two objectives: minimizing generation cost and active power loss. It evaluates cases of placing one and two wind power plants at predetermined and unknown nodes. The MEA and four other algorithms are applied and compared. Results show that MEA most effectively reduces generation cost and power loss by optimizing wind plant location and capacity. MEA performs better than the other algorithms. The paper concludes that wind power integration can reduce costs and losses when optimally placed, and MEA is effective for solving this optimal power flow problem.
A photovoltaic system using supercapacitor energy storage for power equilibri...IJECEIAES
In a photovoltaic system, a stable voltage and of tolerable power equilibrium is needed. Hence, a dedicated analog charge controller for a storage system which controls energy flow to impose power equilibrium, and therefore, voltage stability on the load is required. We demonstrate here our successful design considerations employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system, incorporating a dedicated supercapacitor charge controller for the first time. Firstly, we demonstrated a photovoltaic system employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system. Secondly, we design a constant voltage maximum power point tracker (MPPT) for peak power extraction from the photovoltaic generator. Thirdly, we incorporated a supercapacitor charge controller for power equilibrium and voltage stability through a dedicated analog charge controller in our design, the first of its kind. Fourthly, we analyzed the use of supercapacitor storage to mitigate disequilibrium between power supply and demands, which, in turn, causes overvoltage or under voltage across the load. Lastly, we then went ahead to demonstrate the control of the energy flow in the system so as to maintain rated voltage across a variant demand load.
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
Performance enhancement of maximum power point tracking for grid-connected ph...TELKOMNIKA JOURNAL
This paper presents a new variant of smart adaptive algorithm of Maximum Power Point Tracking (MPPT) in the photovoltaic (PV) system. The algorithm was adopted from Modified Perturb and Observe (MP&O). The smart adaptive MPPT is used to search Maximum Power Point (MPP) of the PV system under various irradiance changes. This algorithm incorporates information of current change (ΔI), maximum operating point margin and dynamic perturbation step to prevent MPPT diverging away from the MPP and minimize the steady state oscillation. The smart adaptive MPPT algorithm performance is compared with the dI-P&O and conventional P&O to prove its effectiveness. The comparison is performed under the various gradient of irradiance change. It was found that, for all the tests, the smart adaptive algorithm scheme improve the tracking efficiency under various gradients of irradiance changes and increase the efficiency of extraction power from PV system.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
This document summarizes a research paper that proposes using an improved particle swarm optimization (IPSO) algorithm to optimize reactive power reserve management in power systems. The IPSO algorithm is applied to minimize total reactive power generation from sources like generators and SVCs by adjusting control variables like generator voltages, transformer taps, and SVC settings. Testing on the IEEE 30-bus system shows the IPSO approach reduces reactive power generation and losses compared to the basic PSO algorithm. The IPSO approach also maintains bus voltages within acceptable ranges while optimizing reactive power reserves.
Stochastic control for optimal power flow in islanded microgridIJECEIAES
The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model.
PHOTOVOLTAIC BASED ELECTRIC VEHICLE USING MAXIMUM POWER POINT TRACKINGIRJET Journal
The document describes a photovoltaic (PV) system for charging electric vehicles (EVs) using maximum power point tracking (MPPT) with model predictive control (MPC). It proposes using an MPC-based MPPT technique to track the global maximum power point of the PV panel with zero oscillations. This provides optimal PV power tracking with high efficiency. A hybrid energy storage system using an ultracapacitor and battery supplies power from the PV system to a BLDC motor that drives the EV. Simulation results in MATLAB/Simulink show that the MPC technique effectively tracks solar power under varying weather conditions.
A Feasible MPPT Algorithm for the DC/DC Boost Converter: An Applied Case for ...phthanh04
One of the most promising forms of renewable energy is solar energy. However, efficient exploitation of this energy form is a
topic of great interest, especially in obtaining the maximum amount of power from the solar photovoltaic (PV) system under changing
environmental conditions. To solve this problem, it is necessary to propose an optimal algorithm. Therefore, this paper presents a feasible
maximum power point tracking (MPPT) technique for DC/DC boost converters applied in load-connected stand-alone PV systems
to extract the maximum available power. This proposed method is based on the combination of the modified perturb and observe
(P&O) and fractional open circuit voltage (FOCV) algorithms. The effectiveness of the proposed technique is verified via time-domain
simulation of the load-connected stand-alone PV system using PSIM software. The simulation results show a tracking efficiency with
an average value of 99.85%, 99.87%, and 99.96% for tracking the MPP under varying loads, irradiation, and simultaneously varying
temperature, load, and irradiation, respectively. In addition, tracking time is always stable at 0.02 sec for changing weather conditions in
the large range. Therefore, the results of the proposed method indicate advantages compared to the conventional method.
Comparison of Maximum Power Point Technique for Solar Photovoltaic ArrayIRJET Journal
This document compares two maximum power point tracking (MPPT) techniques - incremental conductance and perturb and observe algorithms. It summarizes the modeling of a solar photovoltaic module and the use of a DC-DC converter along with an MPPT control mechanism to extract maximum available power from the solar panel under different irradiance conditions. The algorithms are implemented using MATLAB simulations. The perturb and observe algorithm uses duty cycle adjustments to approach the MPP based on the slope of the power-voltage curve. The incremental conductance method matches the PV array impedance to the converter impedance by increasing or decreasing duty cycle. A buck converter configuration is used for MPPT tracking in the simulations.
Similar to Maximum Loadability Enhancement with a Hybrid Optimization Method (20)
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
The document proposes using a particle swarm optimization (PSO) algorithm to optimize the hyperparameters of a convolutional neural network (CNN) for image classification. The PSO algorithm is used to find optimal values for CNN hyperparameters like the number and size of convolutional filters. In experiments on the MNIST handwritten digit dataset, the optimized CNN achieved a testing error rate of 0.87%, which is competitive with state-of-the-art models. The proposed approach finds optimized CNN architectures automatically without requiring manual design or encoding strategies during training.
Supervised machine learning based liver disease prediction approach with LASS...journalBEEI
In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of this deadly disease. By diagnosing the disease in a primary stage, early treatment can be helpful to cure the patient. In this research paper, a method is proposed to diagnose the LD using supervised machine learning classification algorithms, namely logistic regression, decision tree, random forest, AdaBoost, KNN, linear discriminant analysis, gradient boosting and support vector machine (SVM). We also deployed a least absolute shrinkage and selection operator (LASSO) feature selection technique on our taken dataset to suggest the most highly correlated attributes of LD. The predictions with 10 fold cross-validation (CV) made by the algorithms are tested in terms of accuracy, sensitivity, precision and f1-score values to forecast the disease. It is observed that the decision tree algorithm has the best performance score where accuracy, precision, sensitivity and f1-score values are 94.295%, 92%, 99% and 96% respectively with the inclusion of LASSO. Furthermore, a comparison with recent studies is shown to prove the significance of the proposed system.
A secure and energy saving protocol for wireless sensor networksjournalBEEI
The research domain for wireless sensor networks (WSN) has been extensively conducted due to innovative technologies and research directions that have come up addressing the usability of WSN under various schemes. This domain permits dependable tracking of a diversity of environments for both military and civil applications. The key management mechanism is a primary protocol for keeping the privacy and confidentiality of the data transmitted among different sensor nodes in WSNs. Since node's size is small; they are intrinsically limited by inadequate resources such as battery life-time and memory capacity. The proposed secure and energy saving protocol (SESP) for wireless sensor networks) has a significant impact on the overall network life-time and energy dissipation. To encrypt sent messsages, the SESP uses the public-key cryptography’s concept. It depends on sensor nodes' identities (IDs) to prevent the messages repeated; making security goals- authentication, confidentiality, integrity, availability, and freshness to be achieved. Finally, simulation results show that the proposed approach produced better energy consumption and network life-time compared to LEACH protocol; sensors are dead after 900 rounds in the proposed SESP protocol. While, in the low-energy adaptive clustering hierarchy (LEACH) scheme, the sensors are dead after 750 rounds.
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Customized moodle-based learning management system for socially disadvantaged...journalBEEI
This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Understanding the role of individual learner in adaptive and personalized e-l...journalBEEI
Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.
Prototype mobile contactless transaction system in traditional markets to sup...journalBEEI
1) Researchers developed a prototype contactless transaction system using QR codes and digital payments to support physical distancing during the COVID-19 pandemic in traditional markets.
2) The system allows sellers and buyers in traditional markets to conduct fast, secure transactions via smartphones without direct cash exchange. Buyers scan sellers' QR codes to view product details and make e-wallet payments.
3) Testing showed the system's functions worked properly and users found it easy to use and useful for supporting contactless transactions and digital transformation of traditional markets. However, further development is needed to increase trust in digital payments for users unfamiliar with the technology.
Wireless HART stack using multiprocessor technique with laxity algorithmjournalBEEI
The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.
Implementation of double-layer loaded on octagon microstrip yagi antennajournalBEEI
This document describes the implementation of a double-layer structure on an octagon microstrip yagi antenna (OMYA) to improve its performance at 5.8 GHz. The double-layer consists of two double positive (DPS) substrates placed above the OMYA. Simulation and experimental results show that the double-layer configuration increases the gain of the OMYA by 2.5 dB compared to without the double-layer. The measured bandwidth of the OMYA with double-layer is 14.6%, indicating the double-layer can increase both the gain and bandwidth of the OMYA.
The calculation of the field of an antenna located near the human headjournalBEEI
In this work, a numerical calculation was carried out in one of the universal programs for automatic electro-dynamic design. The calculation is aimed at obtaining numerical values for specific absorbed power (SAR). It is the SAR value that can be used to determine the effect of the antenna of a wireless device on biological objects; the dipole parameters will be selected for GSM1800. Investigation of the influence of distance to a cell phone on radiation shows that absorbed in the head of a person the effect of electromagnetic radiation on the brain decreases by three times this is a very important result the SAR value has decreased by almost three times it is acceptable results.
Exact secure outage probability performance of uplinkdownlink multiple access...journalBEEI
In this paper, we study uplink-downlink non-orthogonal multiple access (NOMA) systems by considering the secure performance at the physical layer. In the considered system model, the base station acts a relay to allow two users at the left side communicate with two users at the right side. By considering imperfect channel state information (CSI), the secure performance need be studied since an eavesdropper wants to overhear signals processed at the downlink. To provide secure performance metric, we derive exact expressions of secrecy outage probability (SOP) and and evaluating the impacts of main parameters on SOP metric. The important finding is that we can achieve the higher secrecy performance at high signal to noise ratio (SNR). Moreover, the numerical results demonstrate that the SOP tends to a constant at high SNR. Finally, our results show that the power allocation factors, target rates are main factors affecting to the secrecy performance of considered uplink-downlink NOMA systems.
Design of a dual-band antenna for energy harvesting applicationjournalBEEI
This report presents an investigation on how to improve the current dual-band antenna to enhance the better result of the antenna parameters for energy harvesting application. Besides that, to develop a new design and validate the antenna frequencies that will operate at 2.4 GHz and 5.4 GHz. At 5.4 GHz, more data can be transmitted compare to 2.4 GHz. However, 2.4 GHz has long distance of radiation, so it can be used when far away from the antenna module compare to 5 GHz that has short distance in radiation. The development of this project includes the scope of designing and testing of antenna using computer simulation technology (CST) 2018 software and vector network analyzer (VNA) equipment. In the process of designing, fundamental parameters of antenna are being measured and validated, in purpose to identify the better antenna performance.
Transforming data-centric eXtensible markup language into relational database...journalBEEI
eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.
Key performance requirement of future next wireless networks (6G)journalBEEI
The document provides an overview of the key performance indicators (KPIs) for 6G wireless networks compared to 5G networks. Some of the major KPIs discussed for 6G include: achieving data rates of up to 1 Tbps and individual user data rates up to 100 Gbps; reducing latency below 10 milliseconds; supporting up to 10 million connected devices per square kilometer; improving spectral efficiency by up to 100 times through technologies like terahertz communications and smart surfaces; and achieving an energy efficiency of 1 pico-joule per bit transmitted through techniques like wireless power transmission and energy harvesting. The document outlines how 6G aims to integrate terrestrial, aerial and maritime communications into a single network to provide ubiquitous connectivity with higher
Noise resistance territorial intensity-based optical flow using inverse confi...journalBEEI
This paper presents the use of the inverse confidential technique on bilateral function with the territorial intensity-based optical flow to prove the effectiveness in noise resistance environment. In general, the image’s motion vector is coded by the technique called optical flow where the sequences of the image are used to determine the motion vector. But, the accuracy rate of the motion vector is reduced when the source of image sequences is interfered by noises. This work proved that the inverse confidential technique on bilateral function can increase the percentage of accuracy in the motion vector determination by the territorial intensity-based optical flow under the noisy environment. We performed the testing with several kinds of non-Gaussian noises at several patterns of standard image sequences by analyzing the result of the motion vector in a form of the error vector magnitude (EVM) and compared it with several noise resistance techniques in territorial intensity-based optical flow method.
Modeling climate phenomenon with software grids analysis and display system i...journalBEEI
This study aims to model climate change based on rainfall, air temperature, pressure, humidity and wind with grADS software and create a global warming module. This research uses 3D model, define, design, and develop. The results of the modeling of the five climate elements consist of the annual average temperature in Indonesia in 2009-2015 which is between 29oC to 30.1oC, the horizontal distribution of the annual average pressure in Indonesia in 2009-2018 is between 800 mBar to 1000 mBar, the horizontal distribution the average annual humidity in Indonesia in 2009 and 2011 ranged between 27-57, in 2012-2015, 2017 and 2018 it ranged between 30-60, during the East Monsoon, the wind circulation moved from northern Indonesia to the southern region Indonesia. During the west monsoon, the wind circulation moves from the southern part of Indonesia to the northern part of Indonesia. The global warming module for SMA/MA produced is feasible to use, this is in accordance with the value given by the validate of 69 which is in the appropriate category and the response of teachers and students through a 91% questionnaire.
An approach of re-organizing input dataset to enhance the quality of emotion ...journalBEEI
The purpose of this paper is to propose an approach of re-organizing input data to recognize emotion based on short signal segments and increase the quality of emotional recognition using physiological signals. MIT's long physiological signal set was divided into two new datasets, with shorter and overlapped segments. Three different classification methods (support vector machine, random forest, and multilayer perceptron) were implemented to identify eight emotional states based on statistical features of each segment in these two datasets. By re-organizing the input dataset, the quality of recognition results was enhanced. The random forest shows the best classification result among three implemented classification methods, with an accuracy of 97.72% for eight emotional states, on the overlapped dataset. This approach shows that, by re-organizing the input dataset, the high accuracy of recognition results can be achieved without the use of EEG and ECG signals.
Parking detection system using background subtraction and HSV color segmentationjournalBEEI
Manual system vehicle parking makes finding vacant parking lots difficult, so it has to check directly to the vacant space. If many people do parking, then the time needed for it is very much or requires many people to handle it. This research develops a real-time parking system to detect parking. The system is designed using the HSV color segmentation method in determining the background image. In addition, the detection process uses the background subtraction method. Applying these two methods requires image preprocessing using several methods such as grayscaling, blurring (low-pass filter). In addition, it is followed by a thresholding and filtering process to get the best image in the detection process. In the process, there is a determination of the ROI to determine the focus area of the object identified as empty parking. The parking detection process produces the best average accuracy of 95.76%. The minimum threshold value of 255 pixels is 0.4. This value is the best value from 33 test data in several criteria, such as the time of capture, composition and color of the vehicle, the shape of the shadow of the object’s environment, and the intensity of light. This parking detection system can be implemented in real-time to determine the position of an empty place.
Quality of service performances of video and voice transmission in universal ...journalBEEI
The universal mobile telecommunications system (UMTS) has distinct benefits in that it supports a wide range of quality of service (QoS) criteria that users require in order to fulfill their requirements. The transmission of video and audio in real-time applications places a high demand on the cellular network, therefore QoS is a major problem in these applications. The ability to provide QoS in the UMTS backbone network necessitates an active QoS mechanism in order to maintain the necessary level of convenience on UMTS networks. For UMTS networks, investigation models for end-to-end QoS, total transmitted and received data, packet loss, and throughput providing techniques are run and assessed and the simulation results are examined. According to the results, appropriate QoS adaption allows for specific voice and video transmission. Finally, by analyzing existing QoS parameters, the QoS performance of 4G/UMTS networks may be improved.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
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Foraging Algorithm (BFA) with advanced search techniques make the problems possible to be solved. These
techniques offered global optimal solutions, however, at the expense of computational time [6]. Therefore,
recent researches are inspired to merge conventional methods and advanced optimization techniques for
better and faster optimization approaches.
This study intended to introduce a new Adaptive Tumbling Bacterial Foraging Optimization
(ATBFO) algorithm which is an improvement to the basic Bacterial Foraging Optimization (BFO) algorithm.
The proposed technique was implemented to solve the single objective SCRPP problems. Finally, the
performances of the newly developed technique ATBFO were compared with that provided by the EP and
the basic BFO. The best solutions were identified based on the smallest total system losses and maximum
loading point that the system can withstand. In addition, the aggregate function method was applied to
confirm the outperformed method among them. The lowest total aggregate value is declared as the excellent
approach for the SCRRP problem.
2. SECURED REACTIVE POWER PLANNING
RPP is also known as VAR planning in which reactive power sources are managed and planned
optimally [7]. Reactive power can either inductive or capacitive in nature [8]. RPP is normally solved by
using optimization methods. Various factors and objectives are taken into account in solving RPP in order to
ensure for optimal power flow solution. The main objective of RPP is normally minimization of cost
functions such as variable VAR cost, fixed VAR cost, real power losses and also fuel cost [9]. The authors in
this reference also have explained on the deviation of the operating voltage from a specified voltage schedule
and hence utilized Voltage Stability Margin (VSM). In Secured Reactive Power Planning (SCRPP), voltage
stability criteria are normally treated as the constraints. Therefore, the importance of Load Margin (LM)
assessment is used as a tool to indicate the maximum loading point in order to provide secure operating
margin in power system operation.
2.1. Load Margin Assessment
Load Margin (LM) is broadly accepted in analyzing the closeness of the operating condition of a
power system to its voltage collapse. The LM is defined as the quantity of load increment allowable before a
power system reaches the unsecure voltage condition. The load margin was determined by gradually increase
the load until the load flow failed to give solution.
The relationship between reactive power reserve and Voltage Stability Margin (VSM) was
investigated by researchers in reference [10]. The authors in [11] proposed for re-dispatch of reactive power
in order to improve the voltage stability condition of the power system. However, the total active power
losses were not measured because they believed that the solution is not the optimum one. For that reason,
many researchers have given attention to enhance voltage stability condition by sustaining the reactive power
in a power system [12].
The important steps for load margin estimation that involved the load margin analysis and
enhancement were discussed. Thus, load margin assessment can be classified into two categories in which
the first is to forecast the MLP while the second one is to enhance the voltage stability margin for better
stability condition.
2.2. Objective Functions for SCRPP
The consideration to be an objective function based on Maximum Loadability Point (MLP)
improvement for all load busses in solving SCRPP and also at the improvement of MLP at the
critical bus [13].
2.2.1. Maximizing MLP
MLP for a power networks is the maximum amount of load that could be sustained before it reached
the unstable operating point. As referred to references [14], the LM or also called as VSM could be defined
as the distance from the base case, λ0 load to the maximum loading limit, λmax prior to its imbalance point as
shown in Figure 1. During the assessment, the weakest bus among the network and maximum load that it can
sustain can also be determined. The bus with the smallest margin is identified as the weak or critical bus.
This figure also illustrates the comparison between the MLP before optimizing the reactive power sources
through RPP i.e point A and the MLP after the reactive sources are optimized i.e point B.
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325
Figure 1. The comparison graph between pre and post SCRPP implementation
2.2.2. Minimizing Total System Losses
The objective function for total loss minimization is given by Equation 1.
𝑚𝑖𝑛 𝑓𝑄 = ∑ 𝑃𝑘𝐿𝑜𝑠𝑠,(𝑣, 𝜃) = ∑ 𝑔𝑘
𝑘∈𝑁𝐺
𝑘=(𝑖,𝑗)
(𝑉𝑖
2
𝑘∈𝑁𝐺
+ 𝑉
𝑗
2
− 2𝑉𝑖𝑉
𝑗𝑐𝑜𝑠𝜃𝑖𝑗) MW
𝑉𝑖𝑚𝑖𝑛
≤ 𝑉𝑖 ≤ 𝑉𝑖𝑚𝑎𝑥
𝑖 ∈ 𝑁𝐵
𝑄𝐺𝑖𝑚𝑖𝑛
≤ 𝑄𝐺𝑖 ≤ 𝑄𝐺𝑖𝑀𝑎𝑥
𝑖 ∈ {𝑁𝑃𝑉, 𝑛𝑠}
(1)
where, Qi and Qjare reactive power at sending and receiving buses respectively, 𝑄𝐺𝑖 is generated reactive
power of bus i, 𝑉𝑖 𝑎𝑛𝑑 𝑉
𝑗 are voltage magnitude at sending and receiving buses respectively. 𝑃𝑘𝐿𝑜𝑠𝑠, is total
active power loss over the network,𝑁𝐵is load bus, 𝑁𝑃𝑉 is voltage controlled bus and 𝑛𝑠 is reference (slack)
bus.
2.2.3. The Important Control Variables
The control variables considered are capacitor or reactor switching transformer tap changing [15]
and active power of generator, to facilitate the requirement of SCRPP.
3. METHODOLOGY
3.1. New Adaptive Bacterial Foraging Optimization (ATBFO) Algorithm
This recent Bacterial Foraging Optimization (BFO) searching algorithm invented by K.M. Passino,
is supported by the fact that natural selection tends to eliminate animals with poor foraging strategies against
those with attractive foraging [16]. These poor hunters will be either eliminated or sometimes reshaped to
good ones through a repeated generation process. Several processes of E. coli foraging that are present in our
intestines are called chemotaxis, swarming, reproduction and elimination and dispersal [17]. Using the E.coli
foraging strategy as in BFO, the global searching space is improved by modifying the tumbling approach by
adapting the mutation technique applied in Meta-EP into tumbling expression implemented in basic BFO
thus represented by new Equation 2 to 4 in ATBFO algorithm.
𝜃𝑖(𝑗 + 1, 𝑘, 𝑙) = 𝜃𝑖(𝑗, 𝑘, 𝑙) + 𝐶(𝑖)Ø(𝑖) (2)
Hence: Ø(𝑖) =
∆(𝒊)
√∆𝑻(𝒊)∆(𝒊)
, where ∆(𝑖)= random vector for each bacterium, ∆𝑇(𝑖)= transpose of random vector
for each bacterium. Then, mutate the new position of 𝐽𝑙𝑎𝑠𝑡 by using given by Equation 2.
∅′
𝑖(𝑗) = ∅(𝑗) exp 𝜏′
𝑁(0,1) + 𝜏𝑁𝑖(0,1) (3)
𝑃′
𝑖(𝑗) = 𝑃𝑖(𝑗) + ∅′
𝑖(𝑗)𝑁𝑗(0,1) (4)
where 𝜏 = √
1
√2𝑛
, 𝜏′ =
1
√2𝑛
, 𝑃′
𝑖(𝑗), 𝑃𝑖(𝑗), ∅′
𝑖(𝑗) and ∅(𝑗) is a ith
component of respective vector, 𝑁𝑖(0,1) is
normally distributed one dimensional random number with mean 0 and 1. 𝑁𝑗(0,1) indicates the random
number will be new for each value of j.
λ0 λmax
pre
λmax
post Load
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3.2. A New ATBFO Algorithm for Single Objective Function SCRPP
An intelligence heuristic technique named as ATBFO algorithm was implemented as an
optimization mechanism for solving SCRPP problems with single objective solution. This single objective is
either to maximize the Maximum Loadability Point (MLP) or minimize system losses while satisfying the
operational constraints. The corresponding objective function is calculated while the value of the other is
observed. The simulations were tested under tested on the IEEE 57 bus system for unstressed and stressed
conditions as illustrated in Figure 2. The task also covered all possibilities of load increments as following:
a. Reactive load increment or Q increment
b. Real load increment or P increment and
c. Reactive and Real load increment or Q and P load increased simultaneously.
In addition, the ATBFO method was also executed on identified critical load bus growth called as
Case 1. While, in Case 2 was when the load at all busses were increased simultaneously. During the
implementation, different sizes of control variables were determined, such as Reactive Power Dispatch
(RPD) Qgs, Capacitor Placement (CP), Qinj and Transformer Tap Change Setting (TTCS), Xmer. The solution
in searching for optimal sizes of control variables were also categories into different group of RPP techniques
such as Xmer ,Qinj, Qgs&Qinj, Qgs&Xmer, Qinj&Xmer or Qinj, Qgs&Xmer as RPP technique respectively as referred
in [32, 33]. The overall implementations of the structure covered throughout the contribution were explained
in depth by the subsequent Figure 2.
Start
Generation of
control variables
Run load flow
Comply initial
condition?
Calculate maximum
load margin
Enter the pool
Pool full?
Tumble
Run load flow
Comply initial
condition?
Calculate maximum
load margin
All parents
tumbled?
Swim
Run load flow
Comply initial
condition?
Rank the
descending results
Select the best 10
readings
Duplicate the 10
readings
Probability
<0.25?
Tumble
Take the
reading
All readings been
checked?
End
Calculate maximum
load margin
Calculate maximum
load margin
Comply initial
condition?
Satisfied
swimming
iteration?
Figure 2. Flowchart of ATBFO process for SCRPP for stressed and unstressed condition
The proposed ATBFO was tested on the IEEE 57 bus system for each Single Objective SCRPP
functions as the following:
a. SOSCRPP1=maximum MLP
b. SOSCRPP2=minimum total losses
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The similar optimization process using this ATBFO method which to minimize the total system
losses SOSCRPP2 solutions were also obtained from Case 1 and Case 2 i.e during unstressed and stressed
situations.
3.3. Aggregate Function Method
The aggregate function is introduced in this study as an alternative to describe the results obtained
from optimization methods to meaningful evaluation and conclusion. From the results obtained, the least
answers bring the smallest aggregate value among others objective functions and vice versa. At the end, the
total aggregates are calculated and the smallest sum value as the finest solution.
4. RESULTS AND DISCUSSION
This section discusses the comparison between two individual objective functions namely
SOSCRPP1 and SOSCRPP2 which are to maximize the MLP and to minimize the total losses. Table 1 shows
the improved voltages and their corresponding losses after the implementation SCRPP by optimizing
RPD+TTCS+CP using ATBFO (Point A’). Similarly, the less total loss was determined from SOSCRPP1 as
compared to SOSCRPP2 at the same Point A’. Initially, the Pre-SCRPP (Point A) has 0.849V (Vmin),
30.4575MW (Losses) and 195% (MLP).
Table 1. Comparison between SOSCRPP1 and SOSCRPP2 at Point A’ (After the Implementation of SCRPP)
for Case 1
Single objective of SCRPP for Case 1 using (RPD+TTCS+CP) technique at Point A’
Types
of
load
increment
Objective function SOSCRPP 1 SOSCRPP 2 SOSCRPP 1 SOSCRPP 2
Minimum
Voltage, (p.u)
Minimum
Voltage, (p.u)
Losses
(MW)
Losses
(MW)
P load-unstressed condition 0.957 0.877 31.2383 31.9231
P load-stressed condition 0.940 0.912 30.9819 31.8038
Q load-unstressed condition 0.971 0.866 28.2897 28.6808
Q load-stressed condition 0.973 0.942 27.9983 27.9994
Q & P load-unstressed condition 0.948 0.885 29.5578 30.1719
Q & P load-stressed condition 0.951 0.885 29.2530 30.1169
Table 1 highlights that SOSCRPP 1 resulted in the highest minimum voltage improvement for all
types of load increments at the critical load bus 31. The SOSCRPP1 is solved through the improved ATBFO
which optimized the RPD+RPP+CP with minimizing total losses and maximizing MLP as objective
functions.
While in case 2, the results obtained from SOSCRPP1 (objective function: maximizing MLP) and
SOSCRPP2 (objective function: minimizing total losses) for P load, Q load and Q with P load increments
during the unstressed and stressed situations are compared as shown in Table 2. The table also tabulates the
minimum voltages after of the implementation of SCRPP.
Table 2. Comparison between SOSCRPP1 and SOSCRPP2 at Point A’ (post optimization)for Case 2
Single objective of SCRPP for Case 2 using (RPD+TTCS+CP) technique
Types
of
load
increment
Objective function SOSCRPP1 SOSCRPP2 SOSCRPP1 SOSCRPP2
Minimum
Voltage, (p.u)
Minimum
Voltage, (p.u)
Losses
(MW)
Losses
(MW)
P load-unstressed condition 0.931 0.906 70.6513 71.6664
P load-stressed condition 0.935 0.898 66.4320 67.7000
Q load-unstressed condition 0.932 0.919 29.3769 29.7674
Q load-stressed condition 0.924 0.913 29.9849 29.7363
Q & P load-unstressed condition 0.925 0.899 48.2148 48.5307
Q & P load-stressed condition 0.939 0.887 46.4769 46.6924
The results gained from SOSCRPP1 show higher minimum voltage as compared to that obtained by
SOSCRPP2. In addition, SOSCRPP 1 also leads to lower total losses. Hence, SOSCRPP1 is better in
performance as compared to SOSCRPP2 for Case 1 and Case 2.
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4.1. Comparison of Single Objective Function in SCRPP among Optimization Techniques
The single objective results for maximizing MLP obtained by ATBFO were compared with those
obtained from the original BFO and Meta-EP approaches. Thus, Table 3 highlights the comparison of the
results obtained after solving SCRPP using the above approaches i.e at Point A’ and Point B.
Aggregate function was introduced in the comparative study in order to identify the technique which
gives the best optimization performance as in Table 4. At Point A’, the observed performances are the
minimum voltage improvement and total losses minimization. While at point B, MLP enhancement is
observed.
In Table 4, the performance of each optimization technique is ranked and value 1 is given to the best
result, while value 3 is given to the worst. The least total aggregate indicates the best performance overall.
From this table, it shows that ATBFO always resulted in the best overall performance. Hence, it can be
concluded that ATBFO outperformed the other two optimization technique. This conclusion is summarized
in Table 5.
Therefore, the outstanding optimization computational tool is recorded by the new ATBFO,
followed by Meta-EP and finally the original BFO algorithm.
Table 3. Comparison between ATBFO and Others Optimization Techniques for SOSCRPP1
RPP technique -(RPD+TTCS+CP)
Point B ( Post-optimization) Point A' ( Post-optimization)
Optimization
techniques
Vmin
(p.u)
Vmax
(p.u)
Losses
(MW)
MLP
(%)
Vmin
(p.u)
Vmax
(p.u)
Losses
(MW)
MLP
(%)
Case1
P load –
unstressed
ATBFO 0.855 1.064 43.439 705 0.957 1.092 31.238 325
BFO 0.847 1.067 41.241 600 0.916 1.067 32.409 325
Meta-EP 0.847 1.066 41.278 635 0.929 1.077 31.387 325
P load -
stressed
ATBFO 0.852 1.096 41.550 570 0.940 1.100 30.982 285
BFO 0.855 1.076 38.865 495 0.917 1.073 31.685 285
Meta-EP 0.846 1.071 40.250 535 0.937 1.071 31.237 285
Q load-
unstressed
ATBFO 0.853 1.075 32.362 905 0.971 1.099 28.290 350
BFO 0.850 1.051 31.083 765 0.925 1.067 28.423 350
Meta-EP 0.849 1.075 30.893 795 0.959 1.074 27.977 350
Q load -
stressed
ATBFO 0.850 1.086 31.615 765 0.973 1.100 27.998 305
BFO 0.848 1.069 30.768 655 0.958 1.077 28.335 305
Meta-EP 0.849 1.098 31.285 655 0.946 1.070 28.628 305
Q&P load-
unstressed
ATBFO 0.846 1.082 36.297 455 0.948 1.099 29.558 225
BFO 0.850 1.065 35.737 425 0.940 1.070 29.961 225
Meta-EP 0.846 1.075 34.493 405 0.947 1.053 29.566 225
Q&P load -
stressed
ATBFO 0.856 1.091 35.755 390 0.951 1.095 29.253 195
BFO 0.844 1.046 34.510 335 0.909 1.048 30.010 195
Meta-EP 0.843 1.069 35.346 365 0.938 1.068 29.769 195
Case2
P load-
unstressed
ATBFO 0.843 1.074 159.430 235 0.931 1.089 70.651 165
BFO 0.847 1.040 89.111 180 0.855 1.040 73.946 165
Meta-EP 0.850 1.056 122.053 210 0.907 1.051 66.686 165
P load -
stressed
ATBFO 0.840 1.066 159.298 205 0.935 1.097 66.432 140
BFO 0.844 1.040 80.660 150 0.846 1.040 69.740 140
Meta-EP 0.847 1.069 126.100 185 0.906 1.054 67.641 140
Q load-
unstressed
ATBFO 0.855 1.045 35.709 265 0.932 1.100 29.377 160
BFO 0.843 1.040 33.404 205 0.881 1.040 31.287 160
Meta-EP 0.844 1.040 36.000 260 0.924 1.058 29.728 160
Q load -
stressed
ATBFO 0.858 1.040 35.020 245 0.924 1.053 29.985 140
BFO 0.852 1.040 33.003 165 0.866 1.040 31.759 140
Meta-EP 0.840 1.040 35.945 215 0.913 1.043 30.498 140
Q&P load-
unstressed
ATBFO 0.842 1.044 91.411 180 0.925 1.085 48.215 135
BFO 0.848 1.040 67.629 155 0.878 1.040 50.383 135
Meta-EP 0.844 1.049 80.010 170 0.905 1.060 48.383 135
Q&P load -
stressed
ATBFO 0.857 1.095 89.123 155 0.939 1.100 46.477 115
BFO 0.841 1.040 63.136 130 0.867 1.040 48.992 115
Meta-EP 0.835 1.070 77.541 145 0.902 1.060 47.225 115
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329
Table 4. Comparison between ATBFO and Others Optimization Techniques for SOSCRPP1 Using
Aggregate Performance
Aggregate Function
Point A’ Point B
Optimization techniques Vmin Losses MLP Total Aggregates
Case1
P load-unstressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
P load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Q load- unstressed
ATBFO 1.0 2.0 1.0 4.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 1.0 2.0 5.0
Q load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 2.0 2.0 2.0 6.0
Meta-EP 3.0 3.0 3.0 9.0
Q&P load-unstressed
ATBFO 1.0 2.0 1.0 4.0
BFO 3.0 3.0 2.0 8.0
Meta-EP 2.0 1.0 3.0 6.0
Q&P load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Case2
P load-unstressed
ATBFO 1.0 2.0 1.0 4.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 1.0 2.0 5.0
P load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Q load-unstressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Q load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Q&P load-unstressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Q&P load -stressed
ATBFO 1.0 1.0 1.0 3.0
BFO 3.0 3.0 3.0 9.0
Meta-EP 2.0 2.0 2.0 6.0
Table 5. Comparison between ATBFO and Others Optimization Techniques for SOSCRPP1 for Overall
Performance
Optimization Techniques ATBFO BFO MetaEP
Case1
P load-unstressed 3.0 9.0 6.0
P load -stressed 3.0 9.0 6.0
Q load- unstressed 4.0 9.0 5.0
Q load -stressed 3.0 6.0 9.0
Q&P load-unstressed 4.0 8.0 6.0
Q&P load -stressed 3.0 9.0 6.0
Case2
P load-unstressed 4.0 9.0 5.0
P load -stressed 3.0 9.0 6.0
Q load- unstressed 3.0 9.0 6.0
Q load -stressed 3.0 9.0 6.0
Q&P load-unstressed 3.0 9.0 6.0
Q&P load -stressed 3.0 9.0 6.0
Overall Aggregates 39.0 104.0 73.0
5. CONCLUSION
The objective of SCRPP was to maximize the MLP. In other words, the system has the capability to
support extra loads before going into the voltage instability point. Hence, the number of voltage collapse
events could be reduced. The MLP considered in the study were P, Q and P & Q load increases, while two
cases were analyzed, which were MLP at the critical bus (case 1) and MLP for all load buses simultaneously
(case 2). Single objective functions namely, total losses minimization and MLP improvement were
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implemented and analyzed in solving the SCRPP problems. Several RPP approaches were studied and it was
found that optimizing RPD, CP and TTCS simultaneously gave the best results. Hence, ATBFO was utilized
in SCRPP in order to optimize the RPD, CP and TTCS simultaneously so that the required optimal results
would be obtained. The performance ATBFO was compared with that obtained by BFO and Meta-EP. Based
on the analysis, it was found that ATBFO performed better in terms of MLP improvement, minimum voltage
improvement and total losses minimization.
ACKNOWLEDGEMENT
We thank you to Universiti Teknikal Malaysia Melaka (UTeM) and Kementerian Pengajian Tinggi
(KPT) by funding this research paper successful through the grant of RAGS/1/2015/TK0/ FKE/03/B00094.
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