Electrical power system for low-earth-orbit spacecraft applications

1990 ◽  
Vol 6 (1) ◽  
pp. 63-68 ◽  
Author(s):  
P. R. K. Chetty
Keyword(s):  
Power System ◽  
Electrical Power ◽  
Low Earth Orbit ◽  
Earth Orbit ◽  
Electrical Power System

Fuzzy Logic Based Electrical Power System for Pico Satellite ERPSat-1

2014 ◽  
Vol 875-877 ◽  
pp. 1822-1826 ◽  
Author(s):  
Bilel Neji ◽  
Chafaa Hamrouni ◽  
Adel M. Alimi ◽  
Hiroshi Nakajima
Keyword(s):  
Fuzzy Logic ◽  
Power Systems ◽  
Power System ◽  
Electrical Power ◽  
Low Earth Orbit ◽  
Electrical Power System ◽  
Electrical Power Systems ◽  
Small Satellites ◽  
Efficient Energy ◽  
Intelligent Machines

Despite the recent advances in space technologies, electrical power systems still are challenging researchers developing small satellites for low earth orbit use. In order to supply their subsystems, these satellites can only use the power stored on board from solar energy. Therefore, the electrical power system should ensure a maximum exploitation of energy sources and optimize the distribution of the available electrical power. In this context, Research Group of Intelligent Machines Laboratory in Tunisia developed a new intelligent electrical power subsystem to be used for pico satellites. This subsystem is based on fuzzy logic allowing a faster energy storage and better and efficient energy distribution. The intelligent electrical power subsystem was successfully integrated in ERPSat-1 pico satellite. In addition, the simulation has shown better results compared to other used methods in the previous electrical power systems used for small satellites.

Research of Battery Fault-Simulation on Primary Electrical Power System

2011 ◽  
Vol 354-355 ◽  
pp. 1174-1178
Author(s):  
Jian Hui Zhao ◽  
Jing Wang ◽  
Fan Li
Keyword(s):  
Power System ◽  
Fault Simulation ◽  
Electrical Power ◽  
Lithium Ion ◽  
Paper Analysis ◽  
Low Earth Orbit ◽  
Power System Simulation ◽  
Electrical Power System ◽  
Li Ion ◽  
Battery Discharge

Battery, as one of the important parts in satellite electrical power system, is of a high probability of failure, therefore it is especially important to simulate and analysis. Base on the existing satellite power system simulation platform, this paper analysis on the fault of Low Earth Orbit (LEO) satellites lithium-ion (Li-Ion) battery. Storage battery, battery charge regulator (BCR) and battery discharge regulator (BDR) are modeled and simulated, and the models are built in Matlab/Simulink. The simulation results are realistic, and these models are effective methods for power design and fault recovery.

Gradient Ascent Optimization for Fault Detection in Electrical Power System Based on Wavelet Transformation

2019 ◽  
Vol 14 ◽  
Author(s):  
Iyappan Murugesan ◽  
Karpagam Sathish
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Power System ◽  
Electrical Power ◽  
Daubechies Wavelet ◽  
Electrical Power System ◽  
Gradient Ascent ◽  
Neural Learning ◽  
Weight Value ◽  
Transmission And Distribution

: This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like artificial neural network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the power loss rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TLsignal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, feature extraction accuracy (FEA), and fault detection time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-of-the-art works.

scholarly journals Optical Voltage Transformer Based on FBG-PZT for Power Quality Measurement

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2699
Author(s):  
Marceli N. Gonçalves ◽  
Marcelo M. Werneck
Keyword(s):  
Power System ◽  
Power Quality ◽  
Distribution System ◽  
Electrical Power ◽  
Quality Measurement ◽  
Pockels Effect ◽  
Electrical Power System ◽  
Voltage Transformer ◽  
Technical Literature ◽  
Distribution Lines

Optical Current Transformers (OCTs) and Optical Voltage Transformers (OVTs) are an alternative to the conventional transformers for protection and metering purposes with a much smaller footprint and weight. Their advantages were widely discussed in scientific and technical literature and commercial applications based on the well-known Faraday and Pockels effect. However, the literature is still scarce in studies evaluating the use of optical transformers for power quality purposes, an important issue of power system designed to analyze the various phenomena that cause power quality disturbances. In this paper, we constructed a temperature-independent prototype of an optical voltage transformer based on fiber Bragg grating (FBG) and piezoelectric ceramics (PZT), adequate to be used in field surveys at 13.8 kV distribution lines. The OVT was tested under several disturbances defined in IEEE standards that can occur in the electrical power system, especially short-duration voltage variations such as SAG, SWELL, and INTERRUPTION. The results demonstrated that the proposed OVT presents a dynamic response capable of satisfactorily measuring such disturbances and that it can be used as a power quality monitor for a 13.8 kV distribution system. Test on the proposed system concluded that it was capable to reproduce up to the 41st harmonic without significative distortion and impulsive surges up to 2.5 kHz. As an advantage, when compared with conventional systems to monitor power quality, the prototype can be remote-monitored, and therefore, be installed at strategic locations on distribution lines to be monitored kilometers away, without the need to be electrically powered.

Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Diego A. Monroy-Ortiz ◽  
Sergio A. Dorado-Rojas ◽  
Eduardo Mojica-Nava ◽  
Sergio Rivera
Keyword(s):  
Power Systems ◽  
Power System ◽  
Model Reduction ◽  
Electrical Power ◽  
Schur Complement ◽  
Power Transfer ◽  
Electrical Power System ◽  
Admittance Matrix ◽  
Test Beds ◽  
Power Transfer Distribution Factors

Abstract This article presents a comparison between two different methods to perform model reduction of an Electrical Power System (EPS). The first is the well-known Kron Reduction Method (KRM) that is used to remove the interior nodes (also known as internal, passive, or load nodes) of an EPS. This method computes the Schur complement of the primitive admittance matrix of an EPS to obtain a reduced model that preserves the information of the system as seen from to the generation nodes. Since the primitive admittance matrix is equivalent to the Laplacian of a graph that represents the interconnections between the nodes of an EPS, this procedure is also significant from the perspective of graph theory. On the other hand, the second procedure based on Power Transfer Distribution Factors (PTDF) uses approximations of DC power flows to define regions to be reduced within the system. In this study, both techniques were applied to obtain reduced-order models of two test beds: a 14-node IEEE system and the Colombian power system (1116 buses), in order to test scalability. In analyzing the reduction of the test beds, the characteristics of each method were classified and compiled in order to know its advantages depending on the type of application. Finally, it was found that the PTDF technique is more robust in terms of the definition of power transfer in congestion zones, while the KRM method may be more accurate.

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