This paper proposes a method for determining location to shed the load in order to recover the frequency back to the allowable range. Prioritize distribution of the load shedding at load bus positions based on the voltage electrical distance between the outage generator and the loads. The nearer the load bus from the outage generator is, the sooner the load bus will shed and vice versa. Finally, by selecting the rate of change of generation active power, rate of change of active power of load, rate of change of frequency, rate of change of branches active power and rate of change of voltage in the system as the input to an Artificial Neural Network, the generators outage, the load shedding bus are determined in a short period of time to maintain the stability of the system. With this technique, a large amount of load shedding could be avoided, hence, saved from economic losses. The effectiveness of the proposed method tested on the IEEE 39 Bus New England has demonstrated the effectiveness of this method.
Recently, LCL has become amongst the most attractive filter used for grid-connected flyback inverters. Nonetheless, the switching of power devices in the inverter configuration creates harmonics that affect the end application behavior and might shorten its lifetime. Furthermore, the resonance frequencies produced by the LCL network contribute to the system instability. This paper proposes a step-by-step guide to designing an LCL filter by considering several key aspects such as the resonance frequency and maximum current ripple. A single-phase grid-connected flyback microinverter with an LCL filter was designed then constructed in the MATLAB/Simulink environment. Several different parameter variations and damping solutions were used to analyze the performance of the circuit. The simulation result shows a promising total harmonic distortion (THD) value below 5% and harmonic suppression up to 14%.
Comparison of backstepping, sliding mode and PID regulators for a voltage inv...IJECEIAES
In the present paper, an efficient and performant nonlinear regulator is designed for the control of the pulse width modulation (PWM) voltage inverter that can be used in a standalone photovoltaic microgrid. The main objective of our control is to produce a sinusoidal voltage output signal with amplitude and frequency that are fixed by the reference signal for different loads including linear or nonlinear types. A comparative performance study of controllers based on linear and non-linear techniques such as backstepping, sliding mode, and proportional integral derivative (PID) is developed to ensure the best choice among these three types of controllers. The performance of the system is investigated and compared under various operating conditions by simulations in the MATLAB/Simulink environment to demonstrate the effectiveness of the control methods. Our investigation shows that the backstepping controller can give better performance than the sliding mode and PID controllers. The accuracy and efficiency of the proposed backstepping controller are verified experimentally in terms of tracking objectives.
This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.
With the dominating utility of the internet, it becomes critical to manage the efficiency and reliability of telecom and datacenter, as the power consumption of the involved equipment also increases. Much power being wasted through the power conversion stages by converting AC voltage to DC voltage and then stepping down to lower voltages to connect to information and communication technology (ICT) equipment. 48/12 VDC is the standard DC bus architecture to serve the end utility equipment. This voltage level is further processed to multiple lower voltages to power up the internal auxiliary circuits. Power losses are involved when it is converted from higher voltage to lower voltages. Therefore, the efficiency of power conversion is lower. There is a need to increase the efficiency by minimizing the power losses which occur due to the conversion stages. Different methods are available to increase the efficiency of a system by optimizing the converter topologies, semiconductor materials and control methods. There is another possibility of increasing the efficiency by changing the architecture of a system by increasing the DC bus voltage to higher voltages to optimize the losses. This paper presents a review of available high voltage options for telecom power distribution and developments, implementations and challenges across the world.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
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.
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.
Recently, LCL has become amongst the most attractive filter used for grid-connected flyback inverters. Nonetheless, the switching of power devices in the inverter configuration creates harmonics that affect the end application behavior and might shorten its lifetime. Furthermore, the resonance frequencies produced by the LCL network contribute to the system instability. This paper proposes a step-by-step guide to designing an LCL filter by considering several key aspects such as the resonance frequency and maximum current ripple. A single-phase grid-connected flyback microinverter with an LCL filter was designed then constructed in the MATLAB/Simulink environment. Several different parameter variations and damping solutions were used to analyze the performance of the circuit. The simulation result shows a promising total harmonic distortion (THD) value below 5% and harmonic suppression up to 14%.
Comparison of backstepping, sliding mode and PID regulators for a voltage inv...IJECEIAES
In the present paper, an efficient and performant nonlinear regulator is designed for the control of the pulse width modulation (PWM) voltage inverter that can be used in a standalone photovoltaic microgrid. The main objective of our control is to produce a sinusoidal voltage output signal with amplitude and frequency that are fixed by the reference signal for different loads including linear or nonlinear types. A comparative performance study of controllers based on linear and non-linear techniques such as backstepping, sliding mode, and proportional integral derivative (PID) is developed to ensure the best choice among these three types of controllers. The performance of the system is investigated and compared under various operating conditions by simulations in the MATLAB/Simulink environment to demonstrate the effectiveness of the control methods. Our investigation shows that the backstepping controller can give better performance than the sliding mode and PID controllers. The accuracy and efficiency of the proposed backstepping controller are verified experimentally in terms of tracking objectives.
This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.
With the dominating utility of the internet, it becomes critical to manage the efficiency and reliability of telecom and datacenter, as the power consumption of the involved equipment also increases. Much power being wasted through the power conversion stages by converting AC voltage to DC voltage and then stepping down to lower voltages to connect to information and communication technology (ICT) equipment. 48/12 VDC is the standard DC bus architecture to serve the end utility equipment. This voltage level is further processed to multiple lower voltages to power up the internal auxiliary circuits. Power losses are involved when it is converted from higher voltage to lower voltages. Therefore, the efficiency of power conversion is lower. There is a need to increase the efficiency by minimizing the power losses which occur due to the conversion stages. Different methods are available to increase the efficiency of a system by optimizing the converter topologies, semiconductor materials and control methods. There is another possibility of increasing the efficiency by changing the architecture of a system by increasing the DC bus voltage to higher voltages to optimize the losses. This paper presents a review of available high voltage options for telecom power distribution and developments, implementations and challenges across the world.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
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.
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.
Power quality improvement of grid interconnected distribution system using fs...eSAT Journals
Abstract This paper presents a fuzzy step size least mean square (LMS) algorithm for grid connected renewable energy source. The main objective is to mitigate the harmonics and the neutral current compensation. The conventional controllers may fail due to the rapid change in the dynamics of the highly non-linear system. The fuzzy step size least mean square (FSS-LMS) algorithm in handling theuncertainties and learning from the processes is proved to be advantageous while the inverter operating at fluctuatingoperating conditions. The inverter is controlled tocompensate the harmonics and current imbalance of a three phase four wire non-linear load with generatedrenewable power injection in to the grid.The grid will always supply/absorb a balanced set offundamental currents at unity power factor even in the presence of three phase four wire non-linear unbalance load at point of common coupling(PCC).The proposed system is developed and simulated inMATLAB/SimPowerSystem environment under differentoperating conditions.
A Tactical Chaos based PWM Technique for Distortion Restraint and Power Spect...IJPEDS-IAES
The pulse width modulated voltage source inverters (PWM-VSI) dominate in the modern industrial environment. The conventional PWM methods are designed to have higher fundamental voltage, easy filtering and reduced total harmonic distortion (THD). There are number of clustered harmonics around the multiples of switching frequency in the output of conventional sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) inverters. This is due to their fixed switching frequency while the variable switching frequency makes the filtering very complex. Random carrier PWM (RCPWM) methods are the host of PWM methods, which use randomized carrier frequency and result in a harmonic profile with well distributed harmonic power (no harmonic possesses significant magnitude and hence no filtering is required). This paper proposes a chaos-based PWM (CPWM) strategy, which utilizes a chaotically changing switching frequency to spread the harmonics continuously to a wideband and to reduce the peak harmonics to a great extent. This can be an effective way to suppress the current harmonics and torque ripple in induction motor drives. The proposed CPWM scheme is simulated using MATLAB / SIMULINK software and implemented in three phase voltage source inverter (VSI) using field programmable gate array (FPGA).
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.
A research on significance of kalman filter approach as applied in electrical...eSAT Journals
Abstract Recently, AC distribution systems have experienced high harmonic pollution due to the fact that electrical power system
parameters are often mixed with noise. In an ideal situation, AC power system is supposed to have a constant frequency at
specific voltage but owing to presence of connected nonlinear loads and injection into the grid from non-sinusoidal output active
sources etc., have immensely contributed to the total distortion of the both current and voltage waveforms. This has increased the
system loses and consequently affected other connected equipment in the system. Therefore there is a need to mitigate these effects
if they cannot be eliminated intoto, hence the proposition of Kalman filter. It has been very useful in the aspect of electrical power
discipline particularly in harmonic estimation. It has also find it way in the application of power system dynamics, optimal
operation and control of motor, relay operation and protection, and also for accurate prediction of short and medium term
electrical load forecasting. This paper is to highlight on the significant of Kalman filter methodological approach as adopted in
electrical power system.
Keywords: Kalman Filter; Electrical Power System; Electrical Load; Harmonic Estimation.
Deep segmentation of the liver and the hepatic tumors from abdomen tomography...IJECEIAES
A pipelined framework is proposed for accurate, automated, simultaneous segmentation of the liver as well as the hepatic tumors from computed tomography (CT) images. The introduced framework composed of three pipelined levels. First, two different transfers deep convolutional neural networks (CNN) are applied to get high-level compact features of CT images. Second, a pixel-wise classifier is used to obtain two outputclassified maps for each CNN model. Finally, a fusion neural network (FNN) is used to integrate the two maps. Experimentations performed on the MICCAI’2017 database of the liver tumor segmentation (LITS) challenge, result in a dice similarity coefficient (DSC) of 93.5% for the segmentation of the liver and of 74.40% for the segmentation of the lesion, using a 5-fold cross-validation scheme. Comparative results with the state-of-the-art techniques on the same data show the competing performance of the proposed framework for simultaneous liver and tumor segmentation.
A novel method for determining fixed running time in operating electric train...IJECEIAES
Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
AN EFFICIENT ALGORITHM FOR WRAPPER AND TAM CO-OPTIMIZATION TO REDUCE TEST APP...IAEME Publication
System-on-Chip (SOC) designs composed of many embedded cores are ubiquitous in today’s integrated circuits. Each of these cores requires to be tested separately after manufacturing of the SoC. That’s why, modular testing is adopted for core-based SoCs, as it promotes test reuse and permits the cores to be tested without comprehensive knowledge about their internal structural details. Such modular testing triggers the need of a special test access mechanism (TAM) to build communication between core I/Os and TAM and promises to minimize overall test time. In this paper, various issues are analyzed to optimize the Wrapper and TAM, which comprises the optimal partitioning of TAM width, assignment of cores to partitioned TAM width etc.
Energy Management by Adaptive Neuro-Fuzzy For Under Frequency Load Shedding/C...idescitation
Energy management is the major concern for both
developing and developed countries. Energy sources are
scarce and expensive to develop and exploit, hence we should
confer a procedure to accumulate it by the use of load
shedding. The conventional method is to solve an optimal
power flow problem to find out the rescheduling for overload
alleviation. But this will not give the desired speed of
solution. Speed and accuracy of under frequency load
shedding (UFLS) has a vital role in its effectiveness for
preserving system stability and reducing energy loss. Initial
rate of change of frequency is a fast and potentially useful
signal to detect the overload when a disturbance accurse. This
paper presents a new method for solving UFLS problem by
using neural network and fuzzy logic controller. It also
presents fast and accurate load shedding technique based on
adaptive neuro-fuzzy controller for determining the amount
of load shed to avoid a cascading outage. The development of
new and accurate techniques for vulnerability control of
power systems can provide tools for improving the reliability,
continuity of power supply and reducing the energy loss. The
applicability of ANFIS is tested on a case study at Renigunta
220/132/33 KV sub- station
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Analysis and Implementation of Artificial Neural Network Techniques for Power...ijtsrd
This project shows how to use a back propagation BP control method to execute a three stage delivery static compensator DSTATCOM for its capabilities such as load balancing and zero voltage management of reactive power compensation under non linear loads. In this case, we utilize a BP based control method to determine the crucial dynamic weight. Furthermore, the BP based control method is often used to estimate the receptive power parts of the load streams required for estimating the reference source streams. The new topic of research in the field of power engineering is the regulation of power efficiency devices using neural networks. The output of the balancing instruments is defined by the extraction of the harmonic components. DSTATCOM and UPFC are used as balancing devices in this case. A DSTATCOM model is created with the help of a computerized signal processor, and its implementation is tailored to specific working circumstances. With the suggested control method, the execution of DSTATCOM is shown to be appropriate for a variety of workloads. The BP based control method is used to calculate the basic weighted value of the loads active and reactive power components. The sample trained back propagation method will identify the power quality signal problem in real time. This algorithms main characteristics include continuity, differentiability, and non decreasing momotomy. The UPFC procedure is similar to that of DSTATCOM, with the exception that the device is not turned off under adverse conditions. The simulation model is created using ANFIS, and its output is investigated under various operating circumstances. For various kinds of loads, the ANFIS output is determined to be acceptable using the suggested control method. The proposed technique must be validated using MATLAB Simulink findings. Amrendra Kumar | Pramod Kumar Rathore "Analysis and Implementation of Artificial Neural Network Techniques for Power Quality Enhancement using DSTATCOM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45218.pdf Paper URL: https://www.ijtsrd.com/engineering/other/45218/analysis-and-implementation-of-artificial-neural-network-techniques-for-power-quality-enhancement-using-dstatcom/amrendra-kumar
Improvement of grid connected photovoltaic system using artificial neural net...ijscmcj
Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. In order to control maximum output power, using maximum power point tracking (MPPT) system is highly recommended. This paper simulates and controls the photovoltaic source by using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum point the ANN and GA are used. Data are optimized by GA and then these optimum values are used in neural network training. The simulation results are presented by using Matlab/Simulink and show that the neural network-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point, also it can increase convergence speed to achieve the maximum power point (MPP) rather than conventional method. Moreover, to control both line voltage and current, a grid side p-q controller has been applied.
These slides present an introduction to load flow analysis for distribution system. Later the detail algorithm, matlab coding and application to IEEE radial distribution system will be subsequently provided.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
These slides explain about MPPT control and different approaches for wind generation system. Later I will show the comparative results with MATLAB simulation.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
A hybrid artificial neural network-genetic algorithm for load shedding IJECEIAES
This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method.
A hybrid approach of artificial neural network-particle swarm optimization a...IJECEIAES
This paper proposes an under-frequency load shedding (UFLS) method by using the optimization technique of artificial neural network (ANN) combined with particle swarm optimization (PSO) algorithm to determine the minimum load shedding capacity. The suggested technique using a hybrid algorithm ANN-PSO focuses on 2 main goals: determine whether process shedding plan or not and the distribution of the minimum of shedding power on each demand load bus in order to restore system’s frequency back to acceptable values. In the hybrid algorithm ANN-PSO, the PSO algorithm takes responsible for searching the optimal weights in the neural network structure, which can help to optimize the network training in terms of training speed and accuracy. The distribution of shedding power at each node considering the primary control and secondary control of the generators’ unit and the phase electrical distance between the outage generators and load nodes. The effectiveness of the proposed method is experimented with multiple generators outage cases at various load levels in the IEEE-37 Bus scheme where load shedding cases are considered compared with other traditional technique.
An approach for a multi-stage under-frequency based load shedding scheme for...IJECEIAES
The integration of load shedding schemes with mainstream protection in power system networks is vital. The traditional power system network incorporates different protection schemes to protect its components. Once the power network reaches its maximum limits, and the load demand continue to increase the whole system will experience power system instability. The system frequency usually drops due to the loss of substantial generation creating imbalance. The best method to recover the system from instability is by introducing an under-frequency load shedding (UFLS) scheme in parallel with the protection schemes. This paper proposed a new UFLS scheme used in power systems and industry to maintain stability. Three case studies were implemented in this paper. Multi-stage decisionmaking algorithms load shedding in the environment of the DIgSILENT power factory platform is developed. The proposed algorithm speeds-up the operation of the UFLS scheme. The load shedding algorithm of the proposed scheme is implemented as a systematic process to achieve stability of the power network which is exposed to different operating conditions. The flexibility of the proposed scheme is validated with the modified IEEE 39-bus New England model. The application of the proposed novel UFLS schemes will contribute further to the development of new types of engineers.
Power quality improvement of grid interconnected distribution system using fs...eSAT Journals
Abstract This paper presents a fuzzy step size least mean square (LMS) algorithm for grid connected renewable energy source. The main objective is to mitigate the harmonics and the neutral current compensation. The conventional controllers may fail due to the rapid change in the dynamics of the highly non-linear system. The fuzzy step size least mean square (FSS-LMS) algorithm in handling theuncertainties and learning from the processes is proved to be advantageous while the inverter operating at fluctuatingoperating conditions. The inverter is controlled tocompensate the harmonics and current imbalance of a three phase four wire non-linear load with generatedrenewable power injection in to the grid.The grid will always supply/absorb a balanced set offundamental currents at unity power factor even in the presence of three phase four wire non-linear unbalance load at point of common coupling(PCC).The proposed system is developed and simulated inMATLAB/SimPowerSystem environment under differentoperating conditions.
A Tactical Chaos based PWM Technique for Distortion Restraint and Power Spect...IJPEDS-IAES
The pulse width modulated voltage source inverters (PWM-VSI) dominate in the modern industrial environment. The conventional PWM methods are designed to have higher fundamental voltage, easy filtering and reduced total harmonic distortion (THD). There are number of clustered harmonics around the multiples of switching frequency in the output of conventional sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) inverters. This is due to their fixed switching frequency while the variable switching frequency makes the filtering very complex. Random carrier PWM (RCPWM) methods are the host of PWM methods, which use randomized carrier frequency and result in a harmonic profile with well distributed harmonic power (no harmonic possesses significant magnitude and hence no filtering is required). This paper proposes a chaos-based PWM (CPWM) strategy, which utilizes a chaotically changing switching frequency to spread the harmonics continuously to a wideband and to reduce the peak harmonics to a great extent. This can be an effective way to suppress the current harmonics and torque ripple in induction motor drives. The proposed CPWM scheme is simulated using MATLAB / SIMULINK software and implemented in three phase voltage source inverter (VSI) using field programmable gate array (FPGA).
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.
A research on significance of kalman filter approach as applied in electrical...eSAT Journals
Abstract Recently, AC distribution systems have experienced high harmonic pollution due to the fact that electrical power system
parameters are often mixed with noise. In an ideal situation, AC power system is supposed to have a constant frequency at
specific voltage but owing to presence of connected nonlinear loads and injection into the grid from non-sinusoidal output active
sources etc., have immensely contributed to the total distortion of the both current and voltage waveforms. This has increased the
system loses and consequently affected other connected equipment in the system. Therefore there is a need to mitigate these effects
if they cannot be eliminated intoto, hence the proposition of Kalman filter. It has been very useful in the aspect of electrical power
discipline particularly in harmonic estimation. It has also find it way in the application of power system dynamics, optimal
operation and control of motor, relay operation and protection, and also for accurate prediction of short and medium term
electrical load forecasting. This paper is to highlight on the significant of Kalman filter methodological approach as adopted in
electrical power system.
Keywords: Kalman Filter; Electrical Power System; Electrical Load; Harmonic Estimation.
Deep segmentation of the liver and the hepatic tumors from abdomen tomography...IJECEIAES
A pipelined framework is proposed for accurate, automated, simultaneous segmentation of the liver as well as the hepatic tumors from computed tomography (CT) images. The introduced framework composed of three pipelined levels. First, two different transfers deep convolutional neural networks (CNN) are applied to get high-level compact features of CT images. Second, a pixel-wise classifier is used to obtain two outputclassified maps for each CNN model. Finally, a fusion neural network (FNN) is used to integrate the two maps. Experimentations performed on the MICCAI’2017 database of the liver tumor segmentation (LITS) challenge, result in a dice similarity coefficient (DSC) of 93.5% for the segmentation of the liver and of 74.40% for the segmentation of the lesion, using a 5-fold cross-validation scheme. Comparative results with the state-of-the-art techniques on the same data show the competing performance of the proposed framework for simultaneous liver and tumor segmentation.
A novel method for determining fixed running time in operating electric train...IJECEIAES
Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
AN EFFICIENT ALGORITHM FOR WRAPPER AND TAM CO-OPTIMIZATION TO REDUCE TEST APP...IAEME Publication
System-on-Chip (SOC) designs composed of many embedded cores are ubiquitous in today’s integrated circuits. Each of these cores requires to be tested separately after manufacturing of the SoC. That’s why, modular testing is adopted for core-based SoCs, as it promotes test reuse and permits the cores to be tested without comprehensive knowledge about their internal structural details. Such modular testing triggers the need of a special test access mechanism (TAM) to build communication between core I/Os and TAM and promises to minimize overall test time. In this paper, various issues are analyzed to optimize the Wrapper and TAM, which comprises the optimal partitioning of TAM width, assignment of cores to partitioned TAM width etc.
Energy Management by Adaptive Neuro-Fuzzy For Under Frequency Load Shedding/C...idescitation
Energy management is the major concern for both
developing and developed countries. Energy sources are
scarce and expensive to develop and exploit, hence we should
confer a procedure to accumulate it by the use of load
shedding. The conventional method is to solve an optimal
power flow problem to find out the rescheduling for overload
alleviation. But this will not give the desired speed of
solution. Speed and accuracy of under frequency load
shedding (UFLS) has a vital role in its effectiveness for
preserving system stability and reducing energy loss. Initial
rate of change of frequency is a fast and potentially useful
signal to detect the overload when a disturbance accurse. This
paper presents a new method for solving UFLS problem by
using neural network and fuzzy logic controller. It also
presents fast and accurate load shedding technique based on
adaptive neuro-fuzzy controller for determining the amount
of load shed to avoid a cascading outage. The development of
new and accurate techniques for vulnerability control of
power systems can provide tools for improving the reliability,
continuity of power supply and reducing the energy loss. The
applicability of ANFIS is tested on a case study at Renigunta
220/132/33 KV sub- station
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
Analysis and Implementation of Artificial Neural Network Techniques for Power...ijtsrd
This project shows how to use a back propagation BP control method to execute a three stage delivery static compensator DSTATCOM for its capabilities such as load balancing and zero voltage management of reactive power compensation under non linear loads. In this case, we utilize a BP based control method to determine the crucial dynamic weight. Furthermore, the BP based control method is often used to estimate the receptive power parts of the load streams required for estimating the reference source streams. The new topic of research in the field of power engineering is the regulation of power efficiency devices using neural networks. The output of the balancing instruments is defined by the extraction of the harmonic components. DSTATCOM and UPFC are used as balancing devices in this case. A DSTATCOM model is created with the help of a computerized signal processor, and its implementation is tailored to specific working circumstances. With the suggested control method, the execution of DSTATCOM is shown to be appropriate for a variety of workloads. The BP based control method is used to calculate the basic weighted value of the loads active and reactive power components. The sample trained back propagation method will identify the power quality signal problem in real time. This algorithms main characteristics include continuity, differentiability, and non decreasing momotomy. The UPFC procedure is similar to that of DSTATCOM, with the exception that the device is not turned off under adverse conditions. The simulation model is created using ANFIS, and its output is investigated under various operating circumstances. For various kinds of loads, the ANFIS output is determined to be acceptable using the suggested control method. The proposed technique must be validated using MATLAB Simulink findings. Amrendra Kumar | Pramod Kumar Rathore "Analysis and Implementation of Artificial Neural Network Techniques for Power Quality Enhancement using DSTATCOM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45218.pdf Paper URL: https://www.ijtsrd.com/engineering/other/45218/analysis-and-implementation-of-artificial-neural-network-techniques-for-power-quality-enhancement-using-dstatcom/amrendra-kumar
Improvement of grid connected photovoltaic system using artificial neural net...ijscmcj
Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. In order to control maximum output power, using maximum power point tracking (MPPT) system is highly recommended. This paper simulates and controls the photovoltaic source by using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum point the ANN and GA are used. Data are optimized by GA and then these optimum values are used in neural network training. The simulation results are presented by using Matlab/Simulink and show that the neural network-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point, also it can increase convergence speed to achieve the maximum power point (MPP) rather than conventional method. Moreover, to control both line voltage and current, a grid side p-q controller has been applied.
These slides present an introduction to load flow analysis for distribution system. Later the detail algorithm, matlab coding and application to IEEE radial distribution system will be subsequently provided.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
These slides explain about MPPT control and different approaches for wind generation system. Later I will show the comparative results with MATLAB simulation.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
A hybrid artificial neural network-genetic algorithm for load shedding IJECEIAES
This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method.
A hybrid approach of artificial neural network-particle swarm optimization a...IJECEIAES
This paper proposes an under-frequency load shedding (UFLS) method by using the optimization technique of artificial neural network (ANN) combined with particle swarm optimization (PSO) algorithm to determine the minimum load shedding capacity. The suggested technique using a hybrid algorithm ANN-PSO focuses on 2 main goals: determine whether process shedding plan or not and the distribution of the minimum of shedding power on each demand load bus in order to restore system’s frequency back to acceptable values. In the hybrid algorithm ANN-PSO, the PSO algorithm takes responsible for searching the optimal weights in the neural network structure, which can help to optimize the network training in terms of training speed and accuracy. The distribution of shedding power at each node considering the primary control and secondary control of the generators’ unit and the phase electrical distance between the outage generators and load nodes. The effectiveness of the proposed method is experimented with multiple generators outage cases at various load levels in the IEEE-37 Bus scheme where load shedding cases are considered compared with other traditional technique.
An approach for a multi-stage under-frequency based load shedding scheme for...IJECEIAES
The integration of load shedding schemes with mainstream protection in power system networks is vital. The traditional power system network incorporates different protection schemes to protect its components. Once the power network reaches its maximum limits, and the load demand continue to increase the whole system will experience power system instability. The system frequency usually drops due to the loss of substantial generation creating imbalance. The best method to recover the system from instability is by introducing an under-frequency load shedding (UFLS) scheme in parallel with the protection schemes. This paper proposed a new UFLS scheme used in power systems and industry to maintain stability. Three case studies were implemented in this paper. Multi-stage decisionmaking algorithms load shedding in the environment of the DIgSILENT power factory platform is developed. The proposed algorithm speeds-up the operation of the UFLS scheme. The load shedding algorithm of the proposed scheme is implemented as a systematic process to achieve stability of the power network which is exposed to different operating conditions. The flexibility of the proposed scheme is validated with the modified IEEE 39-bus New England model. The application of the proposed novel UFLS schemes will contribute further to the development of new types of engineers.
Dual techniques of load shedding and capacitor placement considering load mo...IJECEIAES
Voltage stability represents one of the main issues in electrical power system. Under voltage load shedding (UVLS) has long been regarded as one of the most successful techniques to prevent the voltage collapse. However, the ordinary load shedding schemes do not consider the different load models and decreasing in the economic cost that resulted from load disconnection, so the dual techniques of load shedding with reactive compensation are needed. Usually loads being modeled as constant power, while in fact of load flow the various load models are utilized. An investigation of optimal dual load shedding with reactive compensation for distribution system based on direct backward forward sweep method (DBFSM) load flow along with a comparison among the other load models are presented in this paper. The teaching learning-based optimization (TLBO) algorithm is executed in order to reduce power losses and enhance the voltage profile. This algorithm is tested and applied to IEEE-16 bus distribution test system to find the optimal superior capacitor size and placement while minimizing load shading for the network. Five different load shedding sequences are considered and the optimization performance of load models demonstrated the comparison through MATLAB program.
A Novel Back Up Wide Area Protection Technique for Power Transmission Grids U...Power System Operation
Current differential protection relays are widely applied
to the protection of electrical plant due to their simplicity,
sensitivity and stability for internal and external faults. The proposed
idea has the feature of unit protection relays to protect large
power transmission grids based on phasor measurement units. The
principle of the protection scheme depends on comparing positive
sequence voltage magnitudes at each bus during fault conditions
inside a system protection center to detect the nearest bus to
the fault. Then the absolute differences of positive sequence current
angles are compared for all lines connecting to this bus to
detect the faulted line. The new technique depends on synchronized
phasor measuring technology with high speed communication
system and time transfer GPS system. The simulation of the interconnecting
system is applied on 500 kV Egyptian network using
Matlab Simulink. The new technique can successfully distinguish
between internal and external faults for interconnected lines. The
new protection scheme works as unit protection system for long
transmission lines. The time of fault detection is estimated by 5
msec for all fault conditions and the relay is evaluated as a back
up relay based on the communication speed for data transferring.
An Adaptive Virtual Impedance Based Droop Control Scheme for Parallel Inverte...IAES-IJPEDS
This paper presents an adaptive virtual impedance based droop control
scheme for parallel inverter operation in low voltage microgrid. Because it is
essential to achieve power sharing between inverters in microgrid, various
droop control schemes have been proposed. In practice, the line impedance
between inverters and the point of common coupling (PCC) in microgrid are
not always equal. This imbalance in line impedance often results in a reactive
power mismatch among inverters. This problem has been solved by
introducing a virtual impedance loop in the conventional droop control
scheme. However, the reactive power sharing performance of this method is
still deteriorated when the line impedances change during operation. To
overcome such a problem, a new control scheme that is based on a virtual
impedance loop and an impedance estimation scheme is proposed.
To monitor the changes in line impedances, the impedance estimator is
implemented by using the output voltages and currents of inverters as well as
the voltages at the PCC. To compensate for the reactive power mismatch due
to the line impedance changes, the estimated line impedance is fed to the
virtual impedance loop in which it adjusts the virtual impedance value.
Comparative simulation results with the conventional ones verify the
effectiveness of the proposed adaptive virtual impedance based droop control
scheme.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability
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.
MAXIMUM POWER POINT TRACKING WITH ARTIFICIAL NEURAL NET WORKIAEME Publication
Fossil fuels’ rapid depletion and need to protect the environment has left us to think upon alternatives and solutions to curb the excess use of conventional sources and shift focus on the renewable energy. In this paper we have designed a prototype model inclusive of techniques that support the need to harness the solar energy.
An accurate technique for supervising distance relays during power swingnooriasukmaningtyas
Power swing is a power system transient phenomenon that arises due to several reasons including line switching, line outage, sudden increment or decrement in load, faults, etc. Unnecessary tripping during power swing and unnecessary blocking for faults occur during power swing result in distance relay maloperation. Several cascaded outages and major worldwide blackouts have occurred due to maloperation of distance relays. This paper proposes a technique for supervising distance relays during power swing. The proposed online technique discriminates real faults and power swing accurately. It relies on constructing a locus diagram for the current and voltage differences (∆I-∆V) between the two ends of the protected line. The locus is estimated at every power frequency cycle to continuously monitor the state of the line by utilizing the synchrophasor measurements at the sending and receiving ends of the line. The proposed technique is tested for two-area, four-machine power system under faults at different locations of zone-1 and zone-2 regions of distance relays, fault resistances, fault inception angles and slip frequencies using MATLAB software. The simulation results proved the superior improvement of distance relay performance for handling power swing blocking and unblocking actions.
Transient Stability Assessment and Enhancement in Power SystemIJMER
Power system is subjected to sudden changes in load levels. Stability is an important concept
which determines the stable operation of power system. For the improvement of transient stability the
general methods adopted are fast acting exciters, circuit breakers and reduction in system transfer
reactance. The modern trend is to employ FACTS devices in the existing system for effective utilization
of existing transmission resources. The critical clearing time is a measure to assess transient instability.
Using PSAT, the critical clearing time (CCT) corresponding to various faults are calculated. The most
critical faults were identified using this calculation. The CCT for the critical faults were found to change
with change in operating point. The CCT values are predicted using Artificial Neural Network (ANN) to
study the training effects of ANN. TCSC is selected as the FACTS device for transient stability
enhancement. Particle Swarm Optimization method is used to find the optimal position of TCSC using
the objective function real power loss minimization. The result shows that the technique effectively
increases the transient stability of the 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.
Static VAR Compensators (SVCs) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting capacitive or inductive current components at the midpoint of interconnection line or in load areas. This device is capable of minimizing the overall system losses and concurrently improves the voltage stability. A line index, namely SVSI becomes indicator for the placement of SVC and the parameters of SVCs are tuned by using the multi-objective evolutionary programming technique, effectively able to control the power. The algorithm was tested on IEEE-30 Bus Reliability Test System (RTS). Comparative studies were conducted based on the performance of SVC in terms of their location and sizing for installations in power system.
Enhanced Protection Modeling Approach for Power System Transient Stability St...Power System Operation
Accurate protection modelling in power system transient stability studies is required to ensure that reliable conclusions are drawn from such analyses. Typically, protection models available in transient stability programs use only positive sequence quantities such as the positive sequence voltages, currents, etc. to trigger any preventive/corrective actions such as tripping of generators, load-shedding, etc. However, with the increasing penetration of inverter-based resources, these models could prove to be inadequate in some scenarios. The work reported in this paper uses improved modelling practices for protection elements in transient stability studies using sequence/individual phase quantities. This approach does not necessarily require additional data from users and incurs only minimal incremental computational costs. In addition to using the sequence voltages/currents or individual phase voltages/currents for more accurate representation of protection systems, simply monitoring these quantities can also provide useful additional information about the system. Additionally, having access to these quantities could be useful in more accurate modelling of inverter-based resources such as the ability to model converter controls’ protective functions, controls that actively suppress the negative sequence current produced by the inverter, and other such controls that use or control the negative sequence or zero sequence current injections.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
A New Under-Frequency Load Shedding Method Using the Voltage Electrical Distance and Artificial Neural Networks
1. International Journal of Advanced Engineering, Management and Science (IJAEMS) [Vol-5, Issue-3, Mar-2019]
https://dx.doi.org/10.22161/ijaems.5.3.3 ISSN: 2454-1311
www.ijaems.com Page | 171
A New Under-Frequency Load Shedding Method
Using the Voltage Electrical Distance and
Artificial Neural Networks
Le. Trong. Nghia1,*, Quyen. Huy. Anh2, P.T.T. Binh3, Phung. Trieu. Tan4
1,2,4 Faculty of Electrical and Electronics Engineering, HCMC University of Technology and Education, Hochiminh city,
Vietnam
3,*Faculty of Electrical and Electronics Engineering, HCMC University of Technology, Hochiminh city, Vietnam
Abstract—This paper proposes a method for determining
location to shed the load in order to recover the
frequency back to the allowable range. Prioritize
distribution of the load shedding at load bus positions
based on the voltage electrical distance between the
outage generator and the loads. The nearer the load bus
from the outage generator is, the sooner the load bus will
shed and vice versa. Finally, by selecting the rate of
change of generation active power, rate of change of
active power of load, rate of change of frequency, rate of
change of branches active power and rate of change of
voltage in the system as the input to an Artificial Neural
Network, the generators outage, the load shedding bus
are determined in a short period of time to maintain the
stability of the system. With this technique, a large
amount of load shedding could be avoided, hence, saved
from economic losses. The effectiveness of the proposed
method tested on the IEEE 39 Bus New England has
demonstrated the effectiveness of this method.
Keywords—load shedding, Voltage Electrical Distance,
Artificial Neural Network, under-frequency load
shedding.
I. INTRODUCTION
The imbalance active power between the generation and
the load demand causes a decrease the frequency in the
power system. When the balance with the active power
occurs, it’ll give the serious for the frequency instability
of the system. The methods such as primary frequency
control, secondary frequency control, reserve power of
the generation units in the system are only effectiveness
when the system is slightly overloaded and the frequency
of the system is less decrease. But in cases of serious
power imbalance and lead to the blackout completely, the
system need be used load shedding program to recovery
the frequency.
Jianfeng and et al [1] have developed a method with risk
indicators to determine the bus should be targeted for load
shedding to maintain stable voltages. Buses with the
highest voltages risk are prioritized for load shedding.
This is estimated from the probability of the collapse of
the voltage occurring. Risk indicators are the products of
these probabilities and the effects of voltage collapse.
In [2], Hsu and et al presented a strategy of load shedding
by performing artificial neural network (ANN) and
transient stability analysis for an electrical system. To
prepare the training data for ANN, transient stability
analysis of a real power systemhas been made to address
the minimized load with different operating scenarios.
The Levenberg-Marquardt algorithm was combined with
the back propagation algorithm for neural network
training. By choosing the total generating capacity, total
load demand and decay frequency are neural inputs of
ANN, the output is the minimum number of load
shedding that are identified to maintain the stability of the
power system.
In the paper [3], a new approach based on hybrid Particle
Swarm-Based-Simulated Annealing Optimization
technique (PSO-B-SA) is proposed for solving under-
voltage load shedding (UVLS) problem. Under voltage
load shedding (UVLS) is one of the most important tools
for avoiding voltage instability. In this paper, the UVLS
problem is formulated based on the concept of the static
voltage stability margin and its sensitivity at the
maximum loading point or the collapse point. The voltage
stability criterion is modeled
directly into the load-shedding scheme. In any UVLS
scheme finding the global point is very important for
having cost effective economy. The proposed PSO-B-SA
methodology is implemented in the under voltage load
shedding scheme for IEEE 14 and 118 bus test systems.
Simulation
results show the efficacy and advantage of the proposed
scheme.
A good load shedding program must shed the minimum
number of loads as quickly as possible, it also meets all
technical constraints to ensure a stable system.
Conventional load shedding techniques are limited by
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load shedding overloading required and slow
performance. Intelligent load shedding methods have also
been studied and developed such as genetic algorithm
(GA) [4] and particle swarm optimization (PSO)
algorithm [5]. These
focus on determining when and how much load should be
disconnected.Studies on the location of load shedding are
very limited.
This paper proposed the method of load shedding based
on voltage electrical distance method and neural
networks. ANN is used to identify and classify load
shedding control strategies based on the designed rules.
The effectiveness of the proposed method has been tested
on the IEEE 39 Bus New England.
II. THE VOLTAGE ELECTRICAL DISTANCE
The voltage electrical distance between the two nodes i
and j is the following formula [6]:
D(i,j) = D(j,i) = −Log(αij ∗ 𝛼𝑗𝑖) (1)
Where:
/
/
i j
ij
j j
V Q
a
V Q
,
/
/
j i
ji
i i
V Q
a
V Q
(2)
i
j
V
Q
,
j
j
V
Q
,
j
i
V
Q
, i
i
V
Q
are components extracted
from the inverse matrix of the Jacobian matrix.
The formula ∆Vi = αij∗∆Vj [6] represents the voltage drop
at node i when disturbance occurs at node j. Fromformula
(1), the distance near found, relative with D(i,j) small or αij
as large. On the other hand, the larger the αij, the lower
the voltage drop at node i when the disturbance at j as
large. Thus, when the generator outage, the voltage
fluctuation range near the fault node is large, resulting in
the voltage drop at near nodes also increases, then load
shedding will be at the nearest distance load buses or the
largest voltage drop.
Fig. 1: The block diagram of the relationship between
the generator k and the loads
With: DV(k,1)< DV(k,2) < DV(k,3) < …< DV(k,n)
Prioritized load shedding: Load 1 Load 2 Load 3
… Load n
III. PROPOSED METHODS
3.1. Set up load shedding program
Load shedding program are based on three main factors:
the timing, the amount of load to be shed and the location
of load shedding.
The timing: The system data is sent to the control center
for continuous measurement, when the system frequency
is within the allowable range of 59.7Hz<f, the load
shedding program will start, the neuron function will be
activated to identify the generator outage and the load
shedding sequence. The operating time of the UFLS relay
is about 0.1s [7] after the frequency falls below the
allowable threshold and the process is carried out until the
recovery frequency reaches the allowable value. In some
emergency cases, (short circuit, loss of generator) this
method cannot maintain system stability or restore the
frequency with quite long time. Using smart computing
technology,the proposed effective load shedding intervals
require less than 500ms [8]. Here, the proposed load
shedding period is 200ms. This time period includes:
measurement of data acquisition, data transfer, data
processing and tripping trip. However, to ensure safe
margin in real time as well as allowable errors, a period of
100ms [9] is added. So, in the simulation, here the
proposed load shedding time is 300ms.
The amount of load to be shed: After obtaining the load
shedding sequence list for each generator failure, use the
offline PowerWorld simulation software to shed for each
generator in trouble at different load levels from 80% to
100% full load. Dismissed until the frequency of the
buses are within the allowable range of stopping, so that
for each case the incident will have the number of load
shedding corresponding to that case. The incident data
collected would correspond to a number of load shedding
from the trained neuron function.
Location of load shedding: Use voltage electrical distance
for calculating distance between nodes. The load
shedding position will be based on the distances fromthe
generator outage (generator bus) to the remaining load
buses to the load shedding order, or in other words the
priority of the nodes closer to the generator will be first
off, because these load nodes directly affect the generator
is the most trouble. The flowchart load shedding process
is shown in Fig. 2.
3.2. Application ANN to identify the load shedding
Due to the complexity of the power system, the above-
mentioned traditional methods take a lot of time to clear
up, thus causing delays in decision making, The ANN
method is used to solve difficult problems that traditional
methods do not solve in terms of speed and performance.
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However, ANN needs to be trained on the basis of initial
data. Therefore, it is necessary to build the set to leran,
including various outages. Data samples representing in
each outage are the change in generator power ΔPG, the
change of frequency in buses Δfbus, the voltage drop of
buses ΔVbus, the change of load ΔPload and the change of
power distribution across the transmission lines ΔPbranch.
During the simulation, various load levels were
considered to cover the operating modes.
Fig. 2: Flowchart load shedding online
During the ANN model identification process, the
creation database of the generator outage is considered
the most important. Reliable databases not only determine
the accuracy of the assessment,but also have a significant
impact on the robustness of the model.
There are two elements that need to be clearly
demonstrated during the simulation:
- The database must cover the operational status and
must adequately represent the various incident scenarios.
- The generated database must ensure the objectivity
of the parameters of the test power system.
The process of creating a database based on simulation
PowerWorld and it is done through the following 5
stages:
Fig. 3: Simulation steps for input, output sampling
The process of creating input database set is shown in
Fig. 4.
Fig. 4: The process of creating input database set
The process of creating output database set is shown in
Fig 5.
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Fig. 5: The process of creating output database set
Fig. 6: Neural network training model with inputs and
outputs
IV. TESTING ON THE IEEE 39 BUS NEW
ENGLAND
The proposed method is tested on The IEEE 39 bus New
England, using Power world software to collect samples
and Matlab software for neural network training.
Fig. 7: The IEEE 39 bus New England
4.1. Load shedding programthe neural network
The process created a load shedding program use the
neural network shown in Fig. 8.
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Fig. 8: Flowchart simulatorsampling and neural network
training
4.2. Creating database set
Data is available when each generator outage occurs at
different load levels (80% to 100%). This process is done
by off-line simulation using PowerWorld software.
Parameters representing in each case of generator faults
are the change of generator power (ΔPG), the change of
frequency at the bus (Δfbus), the voltage drop at the bus
(ΔVbus), the change in load capacity (ΔPload) and the
change in power distribution across transmission lines
(ΔPbranch).
4.3. Calculate the Voltage Electrical Distance
Voltage electrical distance is physical relationship
between two buses in power system. Voltage electrical
distance can be obtained by following step.
Step 1: Turning all PV generator buses into PQ load
buses.
Step 2: From the matrix Jacobian J, have a matrix J4
from Powerworld, in which J4 = [∂Q/∂V] (3)
Step 3: Inverse J4, call B = J4−1
. Each element of
matrix B is written:
[ ]i
ij
i
V
b
Q
(4)
Step 4: Take the αij decrease matrix, between nodes
i and j, as follows:
ij
ij
jj
b
a
b
(5)
ij
ji
ii
b
a
b
(6)
Step 5: Calculate the voltage electrical distance
between nodes i and j calculated according to the formula
(1):
log( )ij ji ij jiD D
After completing step 5, we obtain table 1
Table.1: Table voltage electrical distance between the generator buses and the load buses.
Bus 30 Bus 32 Bus 33 Bus 34 Bus 35 Bus 36 Bus 37 Bus 38 Bus 39
Bus 3 0.2713 0.6145 0.5104 0.6583 0.4860 0.5908 0.3627 0.5117 0.4162
Bus 4 0.4117 0.4983 0.5665 0.7144 0.5421 0.6469 0.4949 0.6263 0.4479
Bus 7 0.5514 0.5471 0.7253 0.8732 0.7009 0.8057 0.6386 0.7783 0.4446
Bus 8 0.5339 0.5491 0.7153 0.8631 0.6909 0.7957 0.6221 0.7643 0.4053
Bus 12 0.7925 0.6192 0.9137 1.0615 0.8893 0.9940 0.8725 0.9968 0.7824
Bus 15 0.4517 0.6132 0.4053 0.5531 0.3809 0.4856 0.5106 0.5905 0.5427
Bus 16 0.4124 0.6393 0.3183 0.4662 0.2939 0.3987 0.4651 0.5323 0.5243
Bus 18 0.3432 0.6505 0.4561 0.6039 0.4317 0.5364 0.4074 0.4983 0.4790
Bus 20 0.7244 0.9513 0.2636 0.1542 0.6059 0.7107 0.7771 0.8443 0.8363
Bus 21 0.5188 0.7458 0.4248 0.5726 0.2317 0.3679 0.5716 0.6387 0.6308
Bus 23 0.5941 0.8210 0.5000 0.6479 0.2020 0.2170 0.6468 0.7140 0.7060
Bus 24 0.4657 0.6926 0.3716 0.5194 0.3064 0.3967 0.5184 0.5855 0.5776
Bus 25 0.2592 0.7422 0.6092 0.7571 0.5848 0.6896 0.1742 0.4549 0.4567
Bus 26 0.3793 0.7671 0.5769 0.7247 0.5525 0.6573 0.3553 0.2737 0.5449
Bus 27 0.3901 0.7334 0.5179 0.6658 0.4936 0.5983 0.3963 0.3713 0.5405
Bus 28 0.5605 0.9483 0.7581 0.9059 0.7337 0.8384 0.5365 0.1557 0.7261
Bus 29 0.5702 0.9580 0.7678 0.9156 0.7434 0.8482 0.5462 0.0828 0.7359
Bus 39 0.5220 0.8264 0.8426 0.9905 0.8182 0.9230 0.6309 0.8187 0.0000
From Table 1, we build the order of load shedding for each of the generator outage following in Table 2.
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Table.2: Proposed load shedding strategy
Bus
Order Bus 30 Bus 32 Bus 33 Bus 34 Bus 35 Bus 36 Bus 37 Bus 38 Bus 39
1 Load 25 Load 4 Load 20 Load 20 Load 23 Load 23 Load 25 Load 29 Load 39
2 Load 3 Load 7 Load 16 Load 16 Load 21 Load 21 Load 26 Load 28 Load 8
3 Load 18 Load 8 Load 24 Load 24 Load 16 Load 24 Load 3 Load 26 Load 3
4 Load 26 Load 15 Load 15 Load 15 Load 24 Load 16 Load 27 Load 27 Load 7
5 Load 27 Load 3 Load 21 Load 21 Load 15 Load 15 Load 18 Load 25 Load 4
6 Load 4 Load 12 Load 18 Load 18 Load 18 Load 18 Load 16 Load 18 Load 25
7 Load 16 Load 16 Load 23 Load 23 Load 3 Load 3 Load 4 Load 3 Load 18
8 Load 15 Load 18 Load 3 Load 3 Load 27 Load 27 Load 15 Load 16 Load 16
9 Load 24 Load 24 Load 27 Load 27 Load 4 Load 4 Load 24 Load 24 Load 27
10 Load 21 Load 27 Load 4 Load 4 Load 26 Load 26 Load 28 Load 15 Load 15
11 Load 39 Load 25 Load 26 Load 26 Load 25 Load 25 Load 29 Load 4 Load 26
12 Load 8 Load 21 Load 25 Load 25 Load 20 Load 20 Load 21 Load 21 Load 24
13 Load 7 Load 26 Load 8 Load 8 Load 8 Load 8 Load 8 Load 23 Load 21
14 Load 28 Load 23 Load 7 Load 7 Load 7 Load 7 Load 39 Load 8 Load 23
15 Load 29 Load 39 Load 28 Load 28 Load 28 Load 28 Load 7 Load 7 Load 28
16 Load 23 Load 28 Load 29 Load 29 Load 29 Load 29 Load 23 Load 39 Load 29
17 Load 20 Load 20 Load 39 Load 39 Load 39 Load 39 Load 20 Load 20 Load 12
18 Load 12 Load 29 Load 12 Load 12 Load 12 Load 12 Load 12 Load 12 Load 20
Explanation: According to the suggested strategy table
above, if there is a fault at generator 30, the load shedding
order will be Load 25 Load 3 Load 18 ... until
the system is stabilized again. Similarly, for the remaining
generators.
4.4. Build a learning sample set, identify the input
variable, output variable
The number of sample data received via off-line
simulation
total plus 189 samples (including 21 load from 80% to
100%, per each level have 9 case with 9 generators
outage).
Building a learning template is a file under [samples x
variables]. The samples are rows, and variables are
columns.
Samples data in the learning template under the vector
include the variables to the ∆PG (10), ∆fbus (39), ∆Vbus
(39), ∆Pload (19) và ∆Pbranch (46).
Total the input variables are 153 = (10 + 39 +39 + 19 +
46)
x = [∆PG ∆fbus ∆Vbus ∆Pload ∆Pbranch]
The output variables y is assigned as following: y = [y1
STR1 STR2 STR3 STR4… STRn] = 13
where: y1 is the name of generator outage, STRn is
strategic load shedding
Total results of the strategic load shedding on the Table 3
Table.3: Load shedding strategy for each generator fault
Strategic load shedding Load to be shed
Strategic 1 (STR1) L25
Strategic 2 (STR2) L25, L3
Strategic 3 (STR3) L4, L7
Strategic 4 (STR4) L4, L7, L8
Strategic 5 (STR5) L20
Strategic 6 (STR6) L20, L16
Strategic 7 (STR7) L23, L21, L16
Strategic 8 (STR8) L23, L21, L24
Strategic 9 (STR9) L25, L26, L3
Strategic 10 (STR10) L25, L26, L3, L27
Strategic 11 (STR11) L29, L28, L26, L27
Strategic 12 (STR12) L39
Data consists of 189 samples and split into two subsets:
training data and test data. Training data covers all
generator faults at various load levels as well as covers all
strategies load shedding when the generator faults.
Training data is 85% of the samples (162 samples), test
data is 15% of the samples (27 samples).
4.5. Neural network training
The training of the neural network using the Back
Propagation Neural Network (BPNN) with the Scaled
Conjugate Gradient training algorithm was developed by
Moller [10]. It was designed to reduce computational time
at each step of the search, so the training time is faster and
more optimal. It only needs 4 hidden layers neural and
much less than the Levenberg-Marquardt algorithm.
Meanwhile, the accuracy and error of the network is
equivalent to the training method by Levenberg-
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Marquardt algorithm. The structure of the neuron network
is shown in Fig. 9.
Fig. 9: Neural network training structure
Fig. 10: The relationship between the number of neurons
in the hidden layers and the accuracy
4.6. Test load shedding on the IEEE 39 bus New
England by Powerwold.
Process simulation sampling with the IEEE 10 generators
39 bus are made as follows:
Assuming the generator outage is 34, at load level 100%,
the frequency and deviation of the rotor angle become
unstable.
Fig. 11: Diagram of frequency of system at fault
generator 34 load level 100%
When implementing the proposed method, just load
shedding the load on bus 20, the frequency has stabilized.
V. COMPARISON OF METHODLOGY
SUGGESTED WITH OTHER METHODS.
5.1. Load shedding based on under frequency load
shedding relays [11].
Load shedding based on under frequency load shedding
relays is the most commonly used method, which is still
being used in many parts of the world, including
Vietnam. When the grid frequency falls below the
permitted threshold, the relay will be load shedding,
prevents the systemfrequency declines. Without this load
shedding control, the greatest possible consequence is the
blackout and the widespread outage.
For example, the FRCC load shedding program, has a
load shedding plan under frequency load shedding shown
in Table 4.
Table.4: The FRCC load shedding program
UFLS
Steps
Frequency
(Hz)
Time
delay
(s)
Amount
of load (%
of
member
system)
Cumulative
amount of
load (% )
A 59.7 0.28 9 9
B 59.4 0.28 7 16
C 59.1 0.28 7 23
D 58.8 0.28 6 29
E 58.5 0.28 5 34
F 58.2 0.28 7 41
L 59.4 10 5 46
In case of fault at generator 34 the load is 100%, when the
system frequency drops to 59.7Hz, it was load shedding
9% of total load. System frequency continues to fall, and
when dropped to 59.4Hz, load shedding 7% of total load.
The system frequency started to stabilize, the total load
shedding was 16% (9% + 7%).
5.2. Load shedding based on the AHP algorithm
(Analytic Hierarchy Process) [12]
AHP is the approach to making decisions. This method
presents balanced assessment options and criteria, and
integrates them into a final decision. AHP is particularly
suitable for cases involving analysis and quantification,
make decisions when there are multiple options
depending on the criteria with multiple interactions.
Strategic load shedding according to the AHP algorithm
is shown in Table 5.
Table.5: The order of load shedding according to the
AHP algorithm
Order Load
1 L31
2 L12
3 L18
4 L26
5 L23
6 L25
7 L21
8 L28
9 L24
10 L3
11 L16
12 L15
13 L29
14 L27
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15 L7
16 L20
17 L8
18 L4
19 L39
In the case of generator 34 outage, the load is 100%, load
shedding according to AHP algorithm will be shed 31-12-
18-26-23-25, the systemis stability.
5.3. Simulation and results
Comparative results of the methods are presented in Table
6.
Table.6: Comparative results of the methods
Method
Amount of
load
shedding
(MW)
Frequency
recovery
time
(s)
Frequency
stability
(Hz)
UFLS relay 975,52 65 60,75
AHP 785,2 47 60,157
Proposed 628 35 60,030
In the case of generators 34 outage with a load level of
100%, the proposed method has many advantages over
the AHP method and the low frequency method, as
follows:
The proposed load shedding method reduced the amount
of load by 347.52 MW (55.3%) compared to the
traditional load shedding method and 157.2 MW (25%)
compared to the load shedding method based on the AHP
algorithm.
The proposed load shedding method had a frequency
recovery time of 30 seconds (85.7%) compared to
traditional load shedding and 12 seconds faster (34.3%)
than load shedding based on the AHP algorithm. The
simulation result is shown in Fig. 12.
0 10 20 30 40 50 60 70 80 90 100
59.4
59.6
59.8
60
60.2
60.4
60.6
60.8
Time (s)
Frequency(Hz)
UFLS
AHP
Voltage Electrical
Distance
Fig. 12: Diagram of system frequency after generator 34
outage of all three methods of load shedding
0 10 20 30 40 50 60 70 80 90 100
1.01
1.02
1.03
1.04
1.05
1.06
1.07
1.08
1.09
1.1
Time (s)
Volt(V) UFLS
AHP
VOLTAGE ELECTRICAL DISTANCE
Nomal
Fig. 13: Diagram of voltage after generator 34 outage of
all three methods of load shedding
Table.7: Comparison of recovery voltages at 19 bus loads when 34 generators were lost for all three methods
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In the case of generators 34 outage with a load level of
100%, the proposed method has many advantages over
the AHP method and the low frequency method, as
follows:
The proposed load shedding method has a voltage
recovery time of 131.6% compared to conventional
method and 39.5% compared to the AHP algorithm.
The proposed load shedding method has better recovering
voltage values than traditional methods and AHP
algorithm methods as follows: the change in voltage
variation compared to the voltage before the fault of
proposed load shedding method is 0.17%, the traditional
method is 3.65% and the AHP algorithm method is
2.27%.
VI. CONCLUSION
The paper proposed a load shedding scheme with priority
based on the voltage electrical distance between the
generator outage and the load nodes to ensure system
stability in the event of a severe load imbalance in the
event loss a generator occurring in the electric system.
The effectiveness of the proposed load shedding program
has been demonstrated by analyzing the simulation results
of the IEEE 39 system, 10 generators. The results show
that: the method of load shedding proposed to reduce the
amount of load shedding, frequency recovery time, faster
voltage, and better recovery voltage values than
traditional methods and algorithm AHP.
ACKNOWLEDGEMENTS
This research was supported by Ho Chi Minh City
University of Technology and Education, and Ho Chi
Minh City University of Technology.
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