scholarly journals Modeling and recognition of faults in smart distribution grid using maching intelligence technique

2018 ◽  
Author(s):  
◽  
Adeniyi Kehinde Onaolapo
Keyword(s):  
Power Systems ◽  
Power Distribution ◽  
Distribution Systems ◽  
Electrical Power ◽  
Distribution Networks ◽  
Power Distribution Networks ◽  
Data Set ◽  
Power Distribution System ◽  
Fault Recognition ◽  
Ann Models

Electrical power systems experience unforeseen faults attributable to diverse arbitrary reasons. Unanticipated failures occurring in power systems are to be prevented from propagating to other parts of the protective system to enhance economic efficacy of electric utilities and provide better service to energy consumers. Since most consumers are directly connected to power distribution networks, there is an increasing research efforts in distribution network fault recognition and fault-types identifications to solve the problem of outages due to faults. This study focuses on fault recognition and fault-types identification in electrical power distribution system based on the Design Science Research (DSR) approach. Diverse simulations of fault types at different locations were applied to the IEEE 13 Node Test Feeder to produce three phase currents and voltages as data set for this study. This was realized by modelling the IEEE 13-node benchmark test feeder in MATLAB-Simulink R2017a. In order to achieve intelligent fault recognition and fault-type identification, different Multi-layer Perceptron Artificial Neural Networks (MLP-ANN) models were designed and subsequently trained using the generated dataset with the Neural Network toolbox in MATLAB R2017a. The fault recognition task verifies if a fault occurs or not while the fault-types identification task determines the fault class as well as the faulty phase(s). Results obtained from the various MLP-ANN models were recorded and statistically analyzed. Acceptable performances were obtained for fault recognition with the 6-25-20-15-1 MLP-ANN architecture, for fault-types identification with the 6-40-4 MLP-ANN architecture and for fault location with the 6-30-15-5-4 MLP-ANN architecture. Given the result obtained in this study, MLP-ANN is adjudged suitable for intelligent fault recognition and fault-types identification in power distribution systems. The trained MLP-ANNs in this study could ultimately be incorporated in power distribution networks within South Africa and beyond in order to enhance energy customers’ satisfaction.

Planning of Distribution System with High Penetration Level for Distributed Generation in Smart Grid

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Reza Tajik
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Distribution Networks ◽  
Planning Problem ◽  
Renewable Energy Resources ◽  
Power Distribution System ◽  
High Penetration

Nowadays, the utilization of renewable energy resources in distribution systems (DSs) has been rapidly increased. Since distribution generation (DG) use renewable resources (i.e., biomass, wind and solar) are emerging as proper solutions for electricity generation. Regarding the tremendous deployment of DG, common distribution networks are undergoing a transition to DSs, and the common planning methods have become traditional in the high penetration level. Indeed, in conformity with the voltage violation challenge of these resources, this problem must be dealt with too. So, due to the high penetration of DG resources and nonlinear nature of most industrial loads, the planning of DG installation has become an important issue in power systems. The goal of this paper is to determine the planning of DG in distribution systems through smart grid to minimize losses and control grid factors. In this regard, the present work intending to propose a suitable method for the planning of DSs, the key properties of DS planning problem are evaluated from the various aspects, such as the allocation of DGs, and planning, and high-level uncertainties. Also depending on these analyses, this universal literature review addressed the updated study associated with DS planning. In this work, an operational design has been prepared for a higher performance of the power distribution system in the presence of DG. Artificial neural network (ANN) has been used as a method for voltage monitoring and generation output optimization. The findings of the study show that the proposed method can be utilized as a technique to improve the process of the distribution system under various penetration levels and in the presence of DG. Also, the findings revealed that the optimal use of ANN method leads to more controllable and apparent DS.

Distributed Generation Placement for Power Distribution Networks

2014 ◽  
Vol 24 (01) ◽  
pp. 1550009 ◽  
Author(s):  
Xiaodao Chen ◽  
Shiyan Hu
Keyword(s):  
Smart Grid ◽  
Distributed Generation ◽  
Power Distribution ◽  
Power Loss ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Electrical Power ◽  
Distribution Networks ◽  
Ocean Energy ◽  
Electrical Power System

Growing concerns on the energy crisis impose great challenges in development and deployment of the smart grid technologies into the existing electrical power system. A key enabling technology in smart grid is distributed generation, which refers to the technology that power generating sources are located in a highly distributed fashion and each customer is both a consumer and a producer for energy. An important optimization problem in distributed generation design is the insertion of distributed generators (DGs), which are often renewable resources exploiting e.g., photovoltaic, hydro, wind, ocean energy. In this paper, a new power loss filtering based sensitivity guided cross entropy (CE) algorithm is proposed for the distributed generator insertion problem. This algorithm is based on the advanced CE optimization technique which exploits the idea of importance sampling in performing optimization. Our experimental results demonstrate that on large distribution networks, our algorithm can largely reduce (up to 179.3%) power loss comparing to a state-of-the-art sensitivity guided greedy algorithm with small runtime overhead. In addition, our algorithm runs about 5× faster than the classical CE algorithm due to the integration of power loss filtering and sensitivity optimization. Moreover, all existing techniques only test on very small distribution systems (usually with < 50 nodes) while our experiments are performed on the distribution networks with up to 5000 nodes, which matches the realistic setup. These demonstrate the practicality of the proposed algorithm.

scholarly journals Probability-Based Customizable Modeling and Simulation of Protective Devices in Power Distribution Systems

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 199
Author(s):  
Chengwei Lei ◽  
Weisong Tian
Keyword(s):  
Power Systems ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Short Circuit ◽  
Current Data ◽  
System Level ◽  
Power Distribution Systems ◽  
Power Distribution System ◽  
Protective Devices

Fused contactors and thermal magnetic circuit breakers are commonly applied protective devices in power distribution systems to protect the circuits when short-circuit faults occur. A power distribution system may contain various makes and models of protective devices, as a result, customizable simulation models for protective devices are demanded to effectively conduct system-level reliable analyses. To build the models, thermal energy-based data analysis methodologies are first applied to the protective devices’ physical properties, based on the manufacturer’s time/current data sheet. The models are further enhanced by integrating probability tools to simulate uncertainties in real-world application facts, for example, fortuity, variance, and failure rate. The customizable models are expected to aid the system-level reliability analysis, especially for the microgrid power systems.

scholarly journals Multilevel diode clamped D-Statcom for power quality improvement in distribution systems

2021 ◽  
Vol 12 (1) ◽  
pp. 217
Author(s):  
Jasti Venkata Ramesh Babu ◽  
Malligunta Kiran Kumar
Keyword(s):  
Power Quality ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Electrical Power ◽  
Reference Signal ◽  
Power Distribution System ◽  
Received Power ◽  
Multi Level ◽  
Result Analysis

Power quality is one big issue in power system and a big challenge for power engineers today. Electrical consumers (or otherwise load devices) expect electrical power received power should be of first-class. Bad quality in electrical power directs to fuse blowing, machine overheating, increase in distribution losses, damage to sensitive load devices and many more. DSTATCOM is one of the FACTS controllers designed to improve the quality in electrical power and thus improving the performance of distribution system. This paper presents a multilevel DSTATCOM topology to enhance power quality in power distribution system delivering high-quality power to the customer load devices. Diode-clamped structure is employed for multi-level DSTATCOM structure. ‘PQ’ based control strategy generates reference signal which is further processed through level-shifted multi-carrier PWM strategy for the generation of gate pulses to multi-level DSTATCOM structure. Simulation work of proposed system is developed and the result analysis is presented using MATLAB/SIMULINK software. Performance of multi-level DSTATCOM topology is verified with fixed and variable loads.

scholarly journals Review of Steady-State Electric Power Distribution System Datasets

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4826
Author(s):  
Steffen Meinecke ◽  
Leon Thurner ◽  
Martin Braun
Keyword(s):  
Steady State ◽  
Power Systems ◽  
Power System ◽  
Power Distribution ◽  
Distribution System ◽  
New Technologies ◽  
Electrical Power ◽  
Background Information ◽  
Electrical Power Systems ◽  
Power Distribution System

Publicly available grid datasets with electric steady-state equivalent circuit models are crucial for the development and comparison of a variety of power system simulation tools and algorithms. Such algorithms are essential to analyze and improve the integration of distributed energy resources (DERs) in electrical power systems. Increased penetration of DERs, new technologies, and changing regulatory frameworks require the continuous development of the grid infrastructure. As a result, the number and versatility of grid datasets, which are required in power system research, increases. Furthermore, the used grids are created by different methods and intentions. This paper gives orientation within these developments: First, a concise overview of well-known, publicly available grid datasets is provided. Second, background information on the compilation of the grid datasets, including different methods, intentions and data origins, is reviewed and characterized. Third, common terms to describe electric steady-state distribution grids, such as representative grid or benchmark grid, are assembled and reviewed. Recommendations for the use of these grid terms are made.

scholarly journals Power Scalable Bi-Directional DC-DC Conversion Solutions for Future Aircraft Applications

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5470
Author(s):  
Antonio Lamantia ◽  
Francesco Giuliani ◽  
Alberto Castellazzi
Keyword(s):  
High Voltage ◽  
Power Distribution ◽  
Distribution Systems ◽  
Low Voltage ◽  
Leading Edge ◽  
Wide Band ◽  
Distribution Networks ◽  
Significant Degree ◽  
Energy Storage Devices ◽  
Power Distribution Networks

With the introduction of the more electric aircraft, there is growing emphasis on improving overall efficiency and thus gravimetric and volumetric power density, as well as smart functionalities and safety of an aircraft. In future on-board power distribution networks, so-called high voltage DC (HVDC, typically +/−270VDC) supplies will be introduced to facilitate distribution and reduce the associated mass and volume, including harness. Future aircraft power distribution systems will also very likely include energy storage devices (probably, batteries) for emergency back up and engine starting. Correspondingly, novel DC-DC conversion solutions are required, which can interface the traditional low voltage (28 V) DC bus with the new 270 V one. Such solutions presently need to cater for a significant degree of flexibility in their power ratings, power transfer capability and number of inputs/outputs. Specifically, multi-port power-scalable bi-directional converters are required. This paper presents the design and testing of such a solution, addressing the use of leading edge wide-band-gap (WBG) solid state technology, especially silicon carbide (SiC), for use as high-frequency switches within the bi-directional converter on the high-voltage side.

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