The Short-Term Reliability Assessment of Distribution Network Based on Conditions Dependent Element Failure Rate

2014 ◽  
Vol 716-717 ◽  
pp. 1130-1135
Author(s):  
Guo Xun Yuan ◽  
Song Lin ◽  
Yang Xu ◽  
Can Zhao ◽  
Lei Dong ◽  
...  
Keyword(s):  
Distribution Network ◽  
Reliability Assessment ◽  
Assessment Model ◽  
Assessment Process ◽  
Failure Model ◽  
Temperature Dependent ◽  
Short Term ◽  
Actual Operation ◽  
Dependent Model ◽  
Maintenance Personnel

Specific to the demand for the actual operation, this paper calculates short-term failure rates of various types of elements by adopting improved conditions dependent model: temperature-dependent element aging failure model, weather-dependent occasional failure model, current-dependent overload protection model, and processes a short-term reliability assessment by forward failure diffusion algorithm. Example analysis is simulated by 11kV distribution network of IEEE RBTS Bus-2 system to prove the reliability assessment model, the reliability assessment process are effective and provide on-site operation and maintenance personnel with guidance for decision making in the short-term scheduling and online operation.

A Practical GIS-Based Reliability Estimation System for Large Scale Distribution Network

2012 ◽  
Vol 433-440 ◽  
pp. 1802-1810 ◽  
Author(s):  
Lin Guan ◽  
Hao Hao Wang ◽  
Sheng Min Qiu
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Network Reliability ◽  
Distribution Network ◽  
Reliability Assessment ◽  
Distribution Networks ◽  
Reliability Estimation ◽  
Assessment Model ◽  
Estimation System ◽  
The Impact

A new algorithm as well as the software design for large-scale distribution network reliability assessment is proposed in this paper. The algorithm, based on fault traversal algorithm, obtains network information from the GIS. The structure of distribution network data storage formats is described, facilitating automatic output of the feeders’ topological and corresponding information from the GIS. Also the judgment of load transfer is discussed and the method for reliability assessment introduced in this paper. Moreover, The impact of the scheduled outage is taken into account in the assessment model, making the results more in accordance with the actual situation. Test Cases show that the proposed method features good accuracy and effectiveness when applied to the reliability assessment of large-scale distribution networks.

RELIABILITY MODEL FOR COMPONENT-BASED SYSTEMS IN COSMIC (A CASE STUDY)

2008 ◽  
Vol 18 (04) ◽  
pp. 515-539 ◽  
Author(s):  
OLGA ORMANDJIEVA ◽  
MANAR ABU TALIB ◽  
ALAIN ABRAN
Keyword(s):  
System Reliability ◽  
Reliability Assessment ◽  
Software Component ◽  
Assessment Model ◽  
Assessment Process ◽  
Component Technology ◽  
Substantial Impact ◽  
Effort Reduction ◽  
Typical Component

Software component technology has a substantial impact on modern IT evolution. The benefits of this technology, such as reusability, complexity management, time and effort reduction, and increased productivity, have been key drivers of its adoption by industry. One of the main issues in building component-based systems is the reliability of the composed functionality of the assembled components. This paper proposes a reliability assessment model based on the architectural configuration of a component-based system and the reliability of the individual components, which is usage- or testing-independent. The goal of this research is to improve the reliability assessment process for large software component-based systems over time, and to compare alternative component-based system design solutions prior to implementation. The novelty of the proposed reliability assessment model lies in the evaluation of the component reliability from its behavior specifications, and of the system reliability from its topology; the reliability assessment is performed in the context of the implementation-independent ISO/IEC 19761:2003 International Standard on the COSMIC method chosen to provide the component's behavior specifications. In essence, each component of the system is modeled by a discrete time Markov chain behavior based on its behavior specifications with extended-state machines. Then, a probabilistic analysis by means of Markov chains is performed to analyze any uncertainty in the component's behavior. Our hypothesis states that the less uncertainty there is in the component's behavior, the greater the reliability of the component. The system reliability assessment is derived from a typical component-based system architecture with composite reliability structures, which may include the composition of the serial reliability structures, the parallel reliability structures and the p-out-of-n reliability structures. The approach of assessing component-based system reliability in the COSMIC context is illustrated with the railroad crossing case study.

scholarly journals Assessing the Impact of DMAs and the Use of Boosters on Chlorination in a Water Distribution Network in Greece

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2141
Author(s):  
Stavroula Tsitsifli ◽  
Vasilis Kanakoudis
Keyword(s):  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Assessment Process ◽  
Water Volume ◽  
Pressure Management ◽  
Water Age ◽  
Chlorination Process ◽  
Management Measures ◽  
The Impact

Disinfection is one of the most important water treatment processes as it inactivates pathogens providing safe drinking water to the consumers. A fresh-water distribution network is a complex system where constant monitoring of several parameters and related managerial decisions take place in order for the network to operate in the most efficient way. However, there are cases where some of the decisions made to improve the network’s performance level, such as reduction of water losses, may have negative impacts on other significant operational processes such as the disinfection. In particular, the division of a water distribution network into district metered areas (DMAs) and the application of various pressure management measures may impact the effectiveness of the water chlorination process. Two operational measures are assessed in this paper: (a) the use of inline chlorination boosters to achieve more efficient chlorination; and (b) how the DMAs formation impacts the chlorination process. To achieve this, the water distribution network of a Greek town is chosen as a case study where several scenarios are being thoroughly analyzed. The assessment process utilizes the network’s hydraulic simulation model, which is set up in Watergems V8i software, forming the baseline to develop the network’s water quality model. The results proved that inline chlorination boosters ensure a more efficient disinfection, especially at the most remote parts/nodes of the network, compared to conventional chlorination processes (e.g., at the water tanks), achieving 100% safe water volume and consuming almost 50% less chlorine mass. DMAs’ formation results in increased water age values up to 8.27%, especially at the remote parts/nodes of the network and require more time to achieve the necessary minimum effective chlorine concentration of 0.2 mg/L. However, DMAs formation and pressure management measures do not threaten the chlorination’s efficiency. It is important to include water age and residual chlorine as criteria when optimizing water pressure and the division of DMAs.

A comparative study of short-term load forecasting methods in distribution network

2021 ◽  
Vol 15 (1) ◽  
pp. 23-35
Author(s):  
Tuan Ho Le ◽  
◽  
Quang Hung Le ◽  
Thanh Hoang Phan
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Arima Model ◽  
Distribution Network ◽  
Load Forecasting ◽  
Short Term ◽  
Load Demand ◽  
Forecasting Methods ◽  
Short Term Load Forecasting

Short-term load forecasting plays an important role in building operation strategies and ensuring reliability of any electric power system. Generally, short-term load forecasting methods can be classified into three main categories: statistical approaches, artificial intelligence based-approaches and hybrid approaches. Each method has its own advantages and shortcomings. Therefore, the primary objective of this paper is to investigate the effectiveness of ARIMA model (e.g., statistical method) and artificial neural network (e.g., artificial intelligence based-method) in short-term load forecasting of distribution network. Firstly, the short-term load demand of Quy Nhon distribution network and short-term load demand of Phu Cat distribution network are analyzed. Secondly, the ARIMA model is applied to predict the load demand of two distribution networks. Thirdly, the artificial neural network is utilized to estimate the load demand of these networks. Finally, the estimated results from two applied methods are conducted for comparative purposes.

Temperature dependent model dielectric function of highly disordered Ga0.52In0.48P

2011 ◽  
Vol 519 (9) ◽  
pp. 2859-2862
Author(s):  
E. Montgomery ◽  
C. Krahmer ◽  
K. Streubel ◽  
T. Hofmann ◽  
E. Schubert ◽  
...  
Keyword(s):  
Dielectric Function ◽  
Temperature Dependent ◽  
Dependent Model ◽  
Temperature Dependent Model
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