Detection Method of Nature Gas Pipeline Leakage Based on Pattern Recognition

2011 ◽  
Vol 403-408 ◽  
pp. 3144-3148
Author(s):  
Shuai Wang ◽  
Jian Jun Yu ◽  
Ming Qing Yan ◽  
Shu Ying Xiao
Keyword(s):  
Pattern Recognition ◽  
Natural Gas ◽  
Safety Management ◽  
Gas Pipeline ◽  
Actual Condition ◽  
Pipeline Network ◽  
Natural Gas Pipeline ◽  
Detection Technology ◽  
Continuous Progress ◽  
Nature Gas

Natural gas pipeline network is one of the most important city lifeline. Because of the complex process of pipeline operation, there has not an authoritative and reliable way to detect leakage. Taking into account the current continuous progress of pipeline network simulation and mature of gas SCADA system, the fault of natural gas pipeline network can be diagnosed by pattern recognition method. The method takes full advantage of the existing detection technology and the actual condition of the pipe network. It is very useful for pipeline safety management and maintenance.

scholarly journals GPU-accelerated hydraulic simulations of large-scale natural gas pipeline networks based on a two-level parallel process

2020 ◽  
Vol 75 ◽  
pp. 86
Author(s):  
Yue Xiang ◽  
Peng Wang ◽  
Bo Yu ◽  
Dongliang Sun
Keyword(s):  
Natural Gas ◽  
Large Scale ◽  
Parallel Simulation ◽  
Simulation Software ◽  
Gas Pipeline ◽  
Processing Unit ◽  
Pipeline Network ◽  
Natural Gas Pipeline ◽  
Pipeline Networks ◽  
Speedup Ratio

The numerical simulation efficiency of large-scale natural gas pipeline network is usually unsatisfactory. In this paper, Graphics Processing Unit (GPU)-accelerated hydraulic simulations for large-scale natural gas pipeline networks are presented. First, based on the Decoupled Implicit Method for Efficient Network Simulation (DIMENS) method, presented in our previous study, a novel two-level parallel simulation process and the corresponding parallel numerical method for hydraulic simulations of natural gas pipeline networks are proposed. Then, the implementation of the two-level parallel simulation in GPU is introduced in detail. Finally, some numerical experiments are provided to test the performance of the proposed method. The results show that the proposed method has notable speedup. For five large-scale pipe networks, compared with the well-known commercial simulation software SPS, the speedup ratio of the proposed method is up to 57.57 with comparable calculation accuracy. It is more inspiring that the proposed method has strong adaptability to the large pipeline networks, the larger the pipeline network is, the larger speedup ratio of the proposed method is. The speedup ratio of the GPU method approximately linearly depends on the total discrete points of the network.

scholarly journals Analysis and Design of Interruptible Gas Contract in China under Energy Market Reform

2020 ◽  
Vol 12 (2) ◽  
pp. 506
Author(s):  
Jian Chai ◽  
Liqiao Wang
Keyword(s):  
Natural Gas ◽  
Option Price ◽  
Gas Pipeline ◽  
Shaanxi Province ◽  
Stable Operation ◽  
Short Term ◽  
Peak Shaving ◽  
Pipeline Network ◽  
Analysis And Design ◽  
Natural Gas Pipeline

Under the background of economic development, energy security and environmental demands, the development of clean and low-carbon energy has promoted natural gas and non-fossil energy to become the main direction of world energy development. China’s natural gas consumer market has wide seasonal peaks and valleys. Because China’s natural gas peak shaving practices have some problems, we concluded that interruptible gas management has become a viable short-term emergency peak shaving method for natural gas systems in the transition period. In this paper, we take Shaanxi Province as an example. From the perspective of option pricing, this paper explains the method of using interruptible gas management to deal with the short-term supply and demand imbalance of natural gas. Therefore, we propose an interruptible gas contract trading mode, discuss the content of the interruptible gas contract and the relevant market organization form, and try to use the Black–Scholes model to calculate the option price of the interruptible gas contract. Finally, based on the price of interruptible gas and the option price of the interruptible gas contract to meet the maximum capacity shortage constraint, a provincial natural gas pipeline network company’s optimal purchase model for the interruptible gas was established, and the model was solved using the dynamic queuing method. The results show that the interruptible gas contract can not only reduce the market risk of the provincial natural gas pipeline network company and maintain the stable operation of the gas pipeline, but also reduce the cost of the interruptible users and make up for gas shortage losses.

scholarly journals Study on the multi-objective optimization of reliability and operating cost for natural gas pipeline network

2021 ◽  
Vol 76 ◽  
pp. 42
Author(s):  
Kaituo Jiao ◽  
Peng Wang ◽  
Yi Wang ◽  
Bo Yu ◽  
Bofeng Bai ◽  
...  
Keyword(s):  
Natural Gas ◽  
Optimization Model ◽  
Network Reliability ◽  
Operating Cost ◽  
Gas Pipeline ◽  
Multi Objective Optimization ◽  
Pipeline Network ◽  
Multi Objective ◽  
Natural Gas Pipeline ◽  
The Impact

The development of natural gas pipeline network towards larger scale and throughput has urged better reliability of the pipeline network to satisfy transportation requirement. Previously, studies of optimizing natural gas pipeline network have been mainly focused on reducing operating cost, with little concern on the reliability of pipeline network. For a natural gas pipeline network with a variety of components and complicated topology, a multi-objective optimization model of both reliability and operating cost is proposed in this study. Failure of each component and the state of pipeline network under failure conditions are taken into account, and minimum cut set method is employed to calculate the reliability of the pipeline network. The variables to be determined for the optimization objectives are the rotating speed of compressors and the opening of valves. Then the solving procedure of the proposed model is presented based on Decoupled Implicit Method for Efficient Network Simulation (DIMENS) method and NS-saDE algorithm. The validity of the optimization model is ascertained by its application on a complicated pipeline network. The results illustrate that the optimization model can depict the relative relationship between reliability and operating cost for different throughput, by which the operation scheme with both satisfying reliability and operating cost can be obtained. In addition, the customer reliability and the impact of the failure of each pipeline on the whole network can be evaluated quantitatively to identify the consumers and pipelines of maintenance priority. The pipeline network reliability can be improved through proper monitoring and maintenance of these consumers and pipelines.

Using Machine Learning Tools for Forecasting Natural Gas Market Demand

2020 ◽  
Author(s):  
Kai Yang ◽  
Lei Hou
Keyword(s):  
Natural Gas ◽  
Prediction Model ◽  
Evaluation Method ◽  
Gas Pipeline ◽  
Prediction Methods ◽  
Error Evaluation ◽  
Pipeline Network ◽  
Natural Gas Pipeline ◽  
Gas Consumption ◽  
Gas Supply

Abstract Providing reliable and accurate forecasts of natural gas consumption can keep supply and demand of natural gas pipelines in balance, which can increase profits and reduce supply risks. In order to accurately predict the short-term load demand of different gas nodes in the natural gas pipeline network, a hybrid optimization strategy of integrated genetic optimization algorithm and support vector machine are proposed. Factors such as holidays, date types and weather were taken into account to build a natural gas daily load prediction model based on GA-SVM was established. A natural gas pipeline network in China includes three gas supply nodes of different user type gas is forecasted, and a variety of error evaluation method, the GA-SVM evaluation index compared with other prediction methods, and through different data set partition is discussed in the periods of peak gas and gas resources in the GA — the applicability of the SVM prediction model, the ends of a natural gas pipeline network in China includes four gas supply nodes of different user type gas is forecasted, and a variety of error evaluation method, the GA-SVM evaluation index compared with other prediction methods, The applicability of the method is also discussed by dividing different data sets. By predicting the gas load forecast of the three nodes, the results show that GA-SVM hybrid prediction model has high prediction accuracy compared with other single models, and the three gas nodes MAPE of GA-SVM is respectively 3.66%, 5.17% and 3.43%. Through further analysis, even with the data samples reduced, the winter gas peak of gas prediction can still maintain good prediction effects. The research shows that the GA-SVM model has high accuracy and strong applicability in predicting gas consumption at different nodes of the natural gas pipeline network. This study can provide a research basis for analysis of gas supply uncertainty and further gas supply reliability evaluation of pipeline network.

Sign in / Sign up

Export Citation Format

Share Document