Development of an integrated dynamic model for supply security and resilience analysis of natural gas pipeline network systems

An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.

Fuzzy Reliability Analysis for Seabed Oil Gas Pipeline Networks Under Earthquakes

The seabed oil gas pipeline network is simplified to a network with stochastic edge weight by means of the fuzzy graphics theory. With the help of network analysis, fuzzy mathematics, and stochastic theory, the problem of reliability analysis for the seabed oil gas pipeline network under earthquakes is transformed into the calculation of the transitive closure of fuzzy matrix of the stochastic fuzzy network. In classical network reliability analysis, the node is supposed to be non invalidated; in this paper, this premise is modified by introducing a disposal method which has taken the possible invalidated node into account. A good result is obtained by use of the Monte Carlo simulation analysis.

Analytical and Experimental Study on Complex Compressed Air Pipe Network

To analyze the working characteristics of complex compressed air networks, numerical methods are widely used which are based on finite element technology or intelligent algorithms. However, the effectiveness of the numerical methods is limited. In this paper, to provide a new method to optimize the design and the air supply strategy of the complex compressed air pipe network, firstly, a novel method to analyze the topology structure of the compressed air flow in the pipe network is initially proposed. A matrix is used to describe the topology structure of the compressed air flow. Moreover, based on the analysis of the pressure loss of the pipe network, the relationship between the pressure and the flow of the compressed air is derived, and a prediction method of pressure fluctuation and air flow in a segment in a complex pipe network is proposed. Finally, to inspect the effectiveness of the method, an experiment with a complex network is designed. The pressure and the flow of airflow in the network are measured and studied. The results of the study show that, the predicted results with the proposed method have a good consistency with the experimental results, and that verifies the air flow prediction method of the complex pipe network. This research proposes a new method to analyze the compressed air network and a prediction method of pressure fluctuation and air flow in a segment, which can predicate the fluctuation of the pressure according to the flow of compressed air, and predicate the fluctuation of the flow according to the pressure in a segment of a complex pipe network.

Two-stage robust optimization of power cost minimization problem in gunbarrel natural gas networks by approximate dynamic programming

In short-term operation of natural gas network,the impact of demand uncertainty is not negligible.To address this issue we propose a two-stage robust model for power cost minimization problem in gunbarrel natural gas networks.The demands between pipelines and compressor stations are uncertain with a budget parameter,since it is unlikely that all the uncertain demands reach the maximal deviation simultaneously.During solving the two-stage robust model we encounter a bilevel problem which is challenging to solve.We formulate it as a multi-dimensional dynamic programming problem and propose approximate dynamic programming methods to accelerate the calculation.Numerical results based on real network in China show that we obtain a speed gain of 7 times faster in average without compromising optimality compared with original dynamic programming algorithm.Numerical results also verify the advantage of robust model compared with deterministic model when facing uncertainties.These findings offer short-term operation methods for gunbarrel natural gas network management to handle with uncertainties.

Optimal design of the gas storage surface pipeline system with injection and withdrawal conditions

Underground natural gas storage(UNGS)is an important part of the natural gas supply system to ensure a balanced energy supply.The surface system,as an important part of the gas storage,undertakes the functions of gas injection and gas production of the gas storage,and its investment economy is of vital importance.In fact,the UNGS surface pipeline network has two-way injection and production characteristics,which is different from the one-way production characteristics of conventional oil&gas gathering and transportation systems.This paper takes the minimum investment of the pipeline network as the objective function,considers the gas injection and gas withdrawal flow conditions and esablishes a mixed integer non-linear programming model(MINLP)for the surface pipeline network of the UNGS to optimize its pipeline layout and diameter parameters.Constraints including the well affiliation,the number of stations,the gathering radius,the processing capacity and the flow/pressure equilibrium equations,are also taken into consideration.Taking an UNGS in China as an example,the results of the optimal structure and diameter of the pipeline network,as well as the pipe flow,node pressure,and maximum/minimum flowrate during gas injection and gas withdrawal are obtained.Finally,the effects of constraints such as processing capacity and radius on the structure layout and investment of the UNGS are analyzed,verifying the reliability and effectiveness of the model.

Optimization design of multi-gathering mode for the surface system in coalbed methane field

As a potential resource for emerging clean energy with abundant reserves,coalbed methane(CBM)has risen rapidly in recent years,and the construction of rational and economical CBM gathering system plays a vital role in the development of the oil and gas industry.At present,there is no literature that considers the optimization of the multi-gathering mode of coalbed methane pipe network system.Due to the complexity and high investment,this paper establishes a unified mixed-integer nonlinear programming model to determine the gathering modes(including liquified natural gas,compressed natural gas,and gas gathering station)of gathering system to reduce the cost of coalbed methane collection and export.The objective function is the maximization of total profit during the period of the whole project,and such constraints,like network structure,facility number,location,node flow balance,capacity and variable value,are taken into consideration.The solution strategy and heuristic algorithm is proposed and verified by the field data from Shanxi province(China).The results show that the model can solve the problem for optimization design of the surface system in complicated CBM fields.