Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
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Application of Three-Phase Power Flow Analysis to the Nigerian Distribution Networks
Get PDFSingle-phase power flow analysis is used to study most distribution networks in Nigeria. The use of single-phase-power flow analysis assumes that the network is balanced and that the conductor phases act identically. However, Nigerian distribution networks are highly imbalanced because of untransposed lines, irregularly distributed loads in conductor phases, mismatched conductor sizes, and spacing. Consequently, single-phase modeling of the networks fails to reflect actual network behavior, resulting in an incorrect power flow solution. This research presents the three-phase modeling of radial distribution networks for a three-phase-power flow study of Nigerian distribution networks. Olusanya's 54-bus and Ajinde's 62-bus distribution networks in Nigeria were evaluated, both of which were very imbalanced. Without making any assumptions about the network components, these two distribution networks were properly modeled. Each network's three-phase power flow study was carried out in the MATLAB environment. The power flow solutions for each network demonstrated unevenness in the voltage profile for each network phase, as well as inequality in the real and reactive power losses in each phase, indicating that the deployed three-phase-power flow analysis properly mirrored the underlying network characteristics. Therefore, applying three-phase power flow analysis to distribution networks is critical for proper assessment of distribution network performance
Traffic Occupancy Prediction Using a Nonlinear Autoregressive Exogenous Neural Network
Get PDFThe main aim of the intelligent transportation systems is the ability to accurately predict traffic characteristics like traffic occupancy, speed, flow and accident based on historic and real time data collected by these systems in transportation networks. The main challenge of a huge quantity of traffic data collected automatically, stored and processed by these systems is the way of handling and extracting the required traffic data to formulate the prediction traffic characteristic model. In this research, the required traffic data of a specified road link in UK are extracted from the big raw data of the SCOOT system by designing C++ extractor program. In addition, short term traffic prediction models are created by using deep learning technique NARX neural network to find accurate and exact traffic occupancy. Three scenarios of time interval which are 10 minutes, 20 minutes and 30 minutes are considered for analyzing the prediction accuracy. The results showed that the prediction models for the 30 minutes interval scenario have very good accuracy in estimating the future traffic occupancy compared to another scenarios of time intervals. In addition, the testing and validation study showed that the prediction models for 30 minutes intervals for particular road link yield better accuracy than 10 minutes and 20 minutes intervals
Performance Evaluation of Different GNSS Positioning Modes
Get PDFThis paper gives a comparison of different GPS positioning modes using RTKLIB which is free and open-source software. The modes tested in this work are Single point positioning (SPP), precise point positioning (PPP), Satellite-based augmentation system (SBAS), Differential GPS (DGPS), and Real-Time Kinematic (RTK). The data for tests were obtained from NetR9 receivers, these types of receivers are multi-frequencies and multi-constellation receivers that provide carrier and phase measurements. The SPP mode is the very simplest mode, it can be used for applications where accuracy is not less than 5m, and it can be improved to achieve 1m by using SBAS corrections but only in the coverage area of the system. The DGPS can also provide 1m accuracy using a second receiver as a base station which can increase the cost of the operation. For applications that need very high accuracy, RTK and PPP can be used to reach centimeter-level accuracy. RTK needs a base station in addition to the rover receiver used for the positioning; PPP uses precise orbital and clock solutions which are not available in real time for all users
FIR Filter Design using Raised Semi-ellipse Window Function
Get PDFIn this paper, a new two-parameter window function - Raised semi-ellipse (RSE) is proposed. The window is obtained from a fixed elliptical window known as Semi-ellipse window by raising the radius of the minor axis by the parameter (β), and applied for the design of finite impulse response (FIR) digital filters. The spectral parameters of the proposed window are determined first and compared with the Kaiser window – a 2-parameter adjustable window. Subsequently, in its application in filter design with an established design algorithm, the newly proposed adjustable window is compared to the Semi-ellipse window to examine its improvement and also the Kaiser window to compare its performance with a commonly used adjustable window. The filter simulation results show that the filters designed with the proposed window can provide more reduced ripples than the Kaiser window for prescribed spectral characteristics
Fault Classification in a DG Connected Power System using Artificial Neural Network
Get PDFDistributed generation is playing an important role in power system to meet the increased load demand. Integration of Distributed Generator (DG) to grid leads to various issues of protection and control of power system structure. The effect of the distributed generators to the grid is changes the fault current level, which makes the fault analysis more complex. From the different fault issues occurs in a distributed generator integrated power system, classification of fault remains as one of the most vital issue even after years of in-depth research. This paper emphasis on the classification of faults in DG penetrated power system using Artificial Neural Network (ANN). Because researchers are attempting to detect and diagnose these faults as soon as possible in order to avoid financial losses, this work aims to investigate the sort of fault that happened in the hybrid system. This paper proposed artificial neural network based approaches for fault disturbances in a microgrid made up of wind turbine generators, fuel cells, and diesel generator. The voltage signal is retrieved at the point of common coupling (PCC). The extracted data are used for training and testing purpose. Artificial neural network technique is utilized for the classification of fault in the simulated model. Furthermore, performance indices (PIs) such as standard deviation and skewness are calculated for reduction of data size and better accuracy. Both the fault and parameters are varied to check the usefulness of the proposed method. Finally, the results are discussed and compared with different DG penetration
Restoration of Blurred and Noisy Images Using Inverse Filtering and Adaptive Threshold Method
Get PDFA restoration scheme for images that are corrupted with both blur and impulsive noise is proposed in this paper to reconstruct an image with minimum degradation. The restoration scheme consists of two stages in sequence where the first stage is applied to the blurred image and the second stage is applied to de-blurred image that has been subject to noise through electronic transmission. The first stage uses frequency domain filtering while the second utilizes spatial filtering to reduce the indicated blur and noise, respectively. In particular, truncated inverse filtering is used for reducing the blur and an adaptive algorithm with an estimated threshold is used for minimizing the noise. Simulation of the introduced method uses several performance measuring indices such as mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results of these simulations show great performance of the proposed method in terms of reducing the blur and noise significantly while keeping details and sharpness of the image edges
Multi-Channel Configuration for improving received signal strength in non-line-of-sight environments of indoor visible light communication localization
Get PDFIn modern engineering technologies, energy conservation is a factor of primary concern. A feature of Light-emitting diode (LED) light sources is the ability to transmit information in addition to illumination at no additional cost. VLC (Visible Light Communication) is gaining an upper hand over the traditional RF data communication model, as it utilizes a technology by which light can be used to transmit data. It is commonly seen that dealing with non-line of sight (NLOS) is a major challenge for VLC systems as the light intensity is reflected in a variety of directions. To overcome this drawback, a new technique based on multichannel configuration is utilized to enhance the overall system performance. An indoor VLC model is designed and simulated on the basis of the eye-diagram, bit error rate, and received power of the proposed model. We also investigated the model under the influence of ambient light noise. The corresponding results are compared with the conventional NLOS system and an inference made shows the significant improvement for the next-generation optical communication system
Effect of Reactive Power Capability of the PV Inverter on the Power System Quality
Get PDFDistributed generation (DG) based on a photovoltaic system (PV) connected to a power system is a very promising solution to meet the present demand for energy and to reap the advantages of using clean energy. With the exponential increase in the deployment of distributed energy sources based on renewable energy, the reactive power drawn from the grid has increased dramatically compared to the active power. This affects the quality of the power from the network. Reactive power is usually required to regulate the power factor and the grid voltage so as to improve the ability of the system to handle power. In this paper, the reactive power capacity of a PV inverter connected to the grid was determined using the MATLAB/Simulink program. The power (active and reactive) injected into the network were independently controlled by their reference values. A study was conducted on the effects of the injection/absorption of reactive power on the quality of power under different operating conditions
ANFIS multi-tasking algorithm implementation scheme for ball-on-plate system stabilization
Get PDFThis paper presents the design and realization of a ball-on-plate system using a 3-degree-of-freedom parallel robot controlled by an adaptive neuro-fuzzy in-ference system. The ball-on-plate system is nonlinear, multivariable, with an under-actuated feature. Initially, the parallel robot is designed using SolidWorks and mechanized using a computer numerical control machine. Followed by the presentation of the ball-on-plate system mathematical model and the simplified model obtained. Afterwards, the inverse kinematics are performed to derive the appropriate angle for each servomotor. Eventually, the controller is designed and implemented in a double loop feedback scheme. A comparison between the proposed controller and a conventional proportional–integral–derivative controller in terms of time response, overshoot, and steady-state error is carried out. Furthermore, a comparison between sequential and asynchronous parallel processing is conducted for two different scenarios. The first scenario is when moving the ball to the origin while the second is for disturbance rejection. Simulation and experimental results show that the adaptive neuro-fuzzy inference system implemented using asynchronous parallel processing improves the real-time system stability by considerably decreasing oscillations as well as enhancing the ball movement smoothness with a small stead-state error
Smart DIPSS for Dynamic Stability Enchancement on Multi-Machine Power System
Get PDFDisruption of the electric power system always results in instability. These disturbances can be in the form of network breaks (transients) or load changes (dynamic). Changes in load that occur suddenly and periodically cannot be responded well by the generator so that it can affect the dynamic stability of the system. This causes the occurrence of frequency oscillations in the generator. A poor response can cause frequency oscillations for a long period. This will result in a reduction in the available power transfer power. In a multi-machine power system, all the machines work in synchrony, so the generator must operate at the same frequency. Therefore, disturbances that arise will have a direct impact on changes in electrical power. In addition, changes in electrical power will have an impact on mechanical power. The difference in response speed between a fast electrical power response and a slower mechanical power response will result in instability. As a result of these differences, the system oscillates. The addition of the excitation circuit gain is less able to stabilize the system. To solve the problem, additional signal changes are required. The additional signal is generated by the Dual Input Power System Stabilizer (DIPSS) setting using the Ant Colony Optimization (ACO) method.Disruption of the electric power system always results in instability. These disturbances can be in the form of network breaks (transients) or load changes (dynamic). Changes in load that occur suddenly and periodically cannot be responded well by the generator so that it can affect the dynamic stability of the system. This causes the occurrence of frequency oscillations in the generator. A poor response can cause frequency oscillations for a long period. This will result in a reduction in the available power transfer power. In a multi-machine power system, all the machines work in synchrony, so the generator must operate at the same frequency. Therefore, disturbances that arise will have a direct impact on changes in electrical power. In addition, changes in electrical power will have an impact on mechanical power. The difference in response speed between a fast electrical power response and a slower mechanical power response will result in instability. As a result of these differences, the system oscillates. The addition of the excitation circuit gain is less able to stabilize the system. To solve the problem, additional signal changes are required. The additional signal is generated by the Dual Input Power System Stabilizer (DIPSS) setting using the Ant Colony Optimization (ACO) method