Optimization of Short-Term Peak Shaving Scenarios for a Gas Pipeline Network

2008 ◽  
Author(s):  
Lili Zuo ◽  
Changchun Wu ◽  
Li Fan ◽  
Meng Wang
Keyword(s):  
Initial Conditions ◽  
Optimal Operation ◽  
Simulation Software ◽  
Gas Pipeline ◽  
Pipeline System ◽  
Short Term ◽  
Peak Shaving ◽  
Flow Rates ◽  
Pipeline Network ◽  
Gas Supply

PetroChina owns and operates the largest gas pipeline network in China of more than 10000 km in length, which includes the famous West-East gas pipeline, the first Shannxi-Beijing gas pipeline and the second Shannxi-Beijing gas pipeline etc. As an outstanding feature of the network, its two circuits of pipelines increases the flexibility of gas transmission and the guarantee of gas supply through the network. On the other hand, these two circuits complicate the topological structure, so that it is a challenge to work out an optimal operation scenario for the network. A steady and transient simulation model of the network has been built based on the gas pipeline network simulation software TGNET, and has been tuned by the historical operation data. By means of the model, several winter operation scenarios in 2007 have been simulated. The steady simulations of the network were carried out for the two planed daily flow-rates of West-East gas pipeline respectively, 41 MMSCMD and 45 MMSCMD. Given the steady operation scenarios determined by the steady simulations as the initial conditions, 4 typical short-term peak shaving scenarios in winter high load week have been analyzed, evaluated and optimized with transient simulations. The main difference of those peak shaving scenarios is the flow-rates of West-East gas pipeline and the regulating mode of underground gas storage named Dagang connected to Shanxi-Beijing gas pipeline system. The technologically and economically optimal peak shaving scenario and the optimal control pressure of end stations have been obtained. The research results shows that the actual control pressure of end stations are higher than the optimization results, indicating that the network has the potential of saving energy and reducing spending. These results not only guarantee the safety of gas supply but also reduce the spending of the gas pipeline network, offering an important value of direction for actual operation.

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.

Multi-Objective Decision-Making on Peak Shaving of West-East Gas Pipeline

2008 ◽  
Author(s):  
Lili Zuo ◽  
Changchun Wu ◽  
Hongwei Zheng ◽  
Fukun Zhang
Keyword(s):  
Decision Making ◽  
Flow Rate ◽  
Gas Pipeline ◽  
Inlet Pressure ◽  
Pipeline System ◽  
Peak Shaving ◽  
Multi Objective ◽  
Operation Cost ◽  
Gas Supply ◽  
Supply Reliability

This paper addresses the peak shaving of West-East Gas Pipeline. For a gas pipeline system, the decision-making on the peak shaving scenarios usually involves a delicate balance between low operation cost and high gas supply reliability. In order to select an acceptable peak shaving scenario from these two angles for West-East Gas Pipeline, the idea of multi-objective decision-making has been introduced. Based on design flow-rate, eight typical peak shaving scenarios have been evaluated, analyzed and optimized with the help of TGNET. During the simulation, in order to make the peak shaving process more approach to the actual operation of the pipeline system, 51 days of forecasted data are used to establish the system starting state for the study period. On the other hand, in order to reduce the effect of different peak shaving process to the subsequent operation, the study period is extended by 7 days to fully account for operating costs and conditions subsequent to the study period, which make different peak shaving scenarios comparable. According to multi-objective optimization criteria including operation cost, gas supply reliability and operation stability, different pareto peak shaving scenarios have been obtained. These scenarios show that from the object of minimizing operation cost, inlet pressure of Shanghai terminal should approach to contractual pressure, from the object of gas supply reliability and operation stability, inlet pressure of Shanghai terminal should maintain a higher value. Operators can adopt different peak shaving scenarios according to different optimization object. Furthermore, with mathematical statistics knowledge, control value of inlet pressure of Shanghai terminal is recommended. When the change of withdrawal flow-rate from underground gas storage is more frequent, the fluctuation of inlet flow-rate is smaller. When withdrawal flow-rate from underground natural gas storage increases, it will not only increase the inventory of whole pipeline and end segment, but also decrease the inlet flow-rate.

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.

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.

Gas Supply Reliability Analysis of a Natural Gas Pipeline System Considering the Effects of Demand Side Management

2021 ◽  
Vol 143 (4) ◽  
Author(s):  
Yichen Li ◽  
Jing Gong ◽  
Weichao Yu ◽  
Weihe Huang ◽  
Kai Wen
Keyword(s):  
Natural Gas ◽  
Demand Side Management ◽  
Gas Pipeline ◽  
Classification Rule ◽  
Pipeline System ◽  
Demand Side ◽  
User Classification ◽  
Natural Gas Pipeline ◽  
Gas Supply ◽  
Supply Reliability

Abstract At present, China has a developing natural gas market, and ensuring the security of gas supply is an issue of high concern. Gas supply reliability, the natural gas pipeline system's ability to satisfy the market demand, is determined by both supply side and demand side and is usually adopted by the researches to measure the security of gas supply. In the previous study, the demand side is usually simplified by using load duration curve (LDC) to describe the demand, which neglects the effect of demand side management. The simplification leads to the inaccurate and unreasonable assessment of the gas supply reliability, especially in high-demand situation. To overcome this deficiency and achieve a more reasonable result of gas supply reliability, this paper extends the previous study on demand side by proposing a novel method of management on natural gas demand side, and the effects of demand side management on gas supply reliability is analyzed. The management includes natural gas prediction models for different types of users, the user classification rule, and the demand adjustment model based on user classification. First, an autoregressive integrated moving average (ARIMA) model and a support vector machine (SVM) model are applied to predict the natural gas demand for different types of users, such as urban gas distributor (including residential customer, commercial customer, small industrial customer), power plant, large industrial customer, and compressed natural gas (CNG) station. Then, the user classification rule is built based on users' attribute and impact of supplied gas's interruption or reduction. Natural gas users are classified into four levels. (1) demand fully satisfied, (2) demand slightly reduced, (3) demand reduced, and (4) demand interrupted. The user classification rule also provides the demand reduction range of different users. Moreover, the optimization model of demand adjustment is built, and the objective of the model is to maximize the amount of gas supplied to each user based on the classification rule. The constraints of the model are determined by the classification rule, including the demand reduction range of different users. Finally, the improved method of gas supply reliability assessment is developed and is applied to the case study of our previous study derived from a realistic natural gas pipeline system operated by PetroChina to analyze the effects of demand side management on natural gas pipeline system's gas supply reliability.

Optimal Operation of a Multi Source Multi Delivery Natural Gas Transmission Pipeline Network

2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Dr. Adarsh Kumar Arya ◽  
Dr. Shrihari Honwad
Keyword(s):  
Natural Gas ◽  
Fuel Consumption ◽  
Optimal Operation ◽  
Gas Pipeline ◽  
Ant Colony ◽  
Generalized Gradient ◽  
Pipeline Network ◽  
Natural Gas Pipeline ◽  
Natural Gas Transmission ◽  
Transmission Pipeline

Abstract Transportation of natural gas from gathering station to consumption centers is done through complex gas pipeline network system. The huge cost involved in transporting natural gas has made pipeline optimization of increased interest in natural gas pipeline industries. In the present work a lesser known application of Ant Colony in pipeline optimization, has been implemented in a real gas pipeline network. The objective chosen is to minimize the fuel consumption in a gas pipeline network consisting of seven compressors. Pressures at forty-five nodes are chosen as the decision variables. Results of Ant Colony Optimization (ACO) have been compared with those of GAMS that utilizes ‘Generalized gradient principles’ for optimization. Our results utilizing ACO show significant improvement in fuel consumption reductions. Similar procedures can be adopted by researchers and pipeline managers to help pipeline operators in fixing up the pressures at different nodes so as the fuel consumption in compressors gets minimized.

Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages

2019 ◽  
Vol 252 ◽  
pp. 113418 ◽  
Author(s):  
Weichao Yu ◽  
Jing Gong ◽  
Shangfei Song ◽  
Weihe Huang ◽  
Yichen Li ◽  
...  
Keyword(s):  
Natural Gas ◽  
Reliability Analysis ◽  
Gas Pipeline ◽  
Pipeline System ◽  
Natural Gas Pipeline ◽  
Gas Supply ◽  
Supply Reliability

Conditioning TRANSPETRO’s Gas Pipeline Network to the Baía de Guanabara LNG Terminal New Regasification Profile

2014 ◽  
Author(s):  
Philipe B. Krause ◽  
Marcos Bruno B. Carnevale ◽  
Denis F. dos Santos ◽  
Rodrigo B. L. Jardim
Keyword(s):  
Natural Gas ◽  
Power Plants ◽  
Gas Pipeline ◽  
Pipeline System ◽  
Pipeline Network ◽  
Short Period ◽  
Future Demands ◽  
Energy Grid ◽  
To Receive ◽  
Different Sources

Petrobras Transporte S.A. – TRANSPETRO’s Gas Pipeline System, composed by 7.3 thousand kilometers, 135 delivery stations and 21 compressor stations, has a very seasonally dependent operation. Highly linked with the Brazilian energy grid, during the dry season of the year a large part of the 77.3 million cubic meters of natural gas daily transportation are used to generate around 6.4 gigawatts to power the country. Additionally, the ever increasing number of power plants and distribution companies around the country demand more and more gas to be offered to supply the system. Among the different sources of natural gas available, the LNG is the most flexible for such seasonal operation. In order to support this current demand and to attend future demands, the regasification ability of Baía de Guanabara LNG Terminal was increased in December 2012, by changing the regasification vessel that supplies the southeast portion of the gas pipeline network, from 14 to 20 million cubic meters per day. To prepare to receive the new ship, some tests were performed to determine the operational limits on system survival time without LNG supply during vessel exchange. This assessment involved two different issues. The ship change operation occurred during a period of high consumption, when the LNG terminal was needed to sustain the network inventory. A long period without this supply, caused by the exchange of LNG vessel, would affect the deliveries. On the other hand, the new ship’s commissioning curve would introduce a large amount of natural gas into the system during a short period of time, demanding that the deliveries absorbed such volume. Four planning scenarios were assessed based on some expected pipeline supply and delivery conditions. The work was important as a reference for future changes on operating supply units of TRANSPETRO gas pipeline system, showing the importance of pipeline simulation both as a planning tool for pipeline logistic problems and as operational support.

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