Development of natural gas flow rate in pipeline networks based on unsteady state Weymouth equation

Amani, Hossein; Kariminezhad, Hasan; Kazemzadeh, Hamid

doi:10.1016/j.jngse.2016.05.046

Cited by 11 publications

(8 citation statements)

References 18 publications

(28 reference statements)

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“…At present, the methods of the optimization research of natural gas pipeline network have been mainly including two categories: one is the regression method including stochastic, 6 interval analysis approach, 7 linear programming, 8 a sequential quadratic method, 9 a non-sequential dynamic method, 10 a bilevel programming method, 11 and economic nonlinear model; 12 the other is the intelligent method. 13 In previous work, 14 adaptive particle swarm optimization (PSO) algorithm was presented to optimize the natural gas pipeline.…”

Section: Introductionmentioning

confidence: 99%

Study on optimal operation of natural gas pipeline network based on improved genetic algorithm

Zhang

Liu

2017

Advances in Mechanical Engineering

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This article investigates an optimal operation model which is based on improved genetic algorithm for natural gas pipeline network. First, the maximum benefit and the maximum flow were chosen as the objective function, and several conditions were selected as the constraints including the input and output of gas, the input and output pressure of gas, the handling capacity of compressive station, the strength of the pipeline, decreasing of the pipeline pressure, the compressor, the valve, and the flow balance of pipe network node. On the basis of the above two aspects, the optimal mathematical operation model of natural gas pipeline network is established. Second, an improved genetic algorithm is proposed due to the possibility that the fitness value of particular individual in the initial population is abnormal and the possibility that the probabilities of the crossover and the mutation are too high or too low. Finally, a medium-pressure pipe network is taken as a study example. Compared with the basic genetic algorithm and the non-optimized genetic algorithm, the maximum benefit and maximum flow rate of the improved genetic algorithm are increased by 3.09%, 1.61%, 5.98%, and 2.44%, respectively.

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Section: Introductionmentioning

confidence: 99%

Study on optimal operation of natural gas pipeline network based on improved genetic algorithm

Zhang

Liu

2017

Advances in Mechanical Engineering

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“…The EH of the MES utilizes NG as one energy input. Although the NG handling and production methods differ by country and region, in most studies, the Weymouth equation is commonly used to analyze gas flow through pipes [53,54]. Many other techniques in addition to the Weymouth equation exist for analyzing gas networks [55][56][57][58].…”

Section: B Natural Gas Systemmentioning

confidence: 99%

“…After presenting the MES configuration, its objective function is defined to solve the problem based on different perspectives. Many studies have explored the economic improvements associated with the MES compared to conventional single systems [53][54]67]. Some other studies [131][132][133][134][135][136][137][138][139][140] proposed methods for enhancing the reliability of a system through the MES, and the simulation resulted in improved economic and reliability data compared to existing system.…”

Section: Introductionmentioning

confidence: 99%

Multi Energy System With an Associated Energy Hub: A Review

Son¹,

Oh²,

Acquah³

et al. 2021

IEEE Access

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The increasing penetration of renewable resources causes some challenges like the electric power demand prediction uncertainty and energy surplus. Energy storage systems (ESS) are promising solutions for these challenges. However, considering the marginal capacity of ESSs according to the installation area and the economic portion of ESSs according to the installation capacity, the use of battery ESSs to reduce surplus energy is not efficient and has practical limitations. To efficiently resolve the challenges, a multi-energy system (MES) that is capable of operating different energy sources, such as natural gas storage (NGS), thermal energy storage (TES), ice energy storage (IES), and hydrogen energy storage (HES) has been proposed. The centerpiece of converting and managing multiple energy sources associated with the MES is the energy hub (EH). In this paper, we reviewed and compared the performance of existing ESSs and the MES, and the results have demonstrated the superiority of the MES. In addition, EHs that include power-to-gas, combined heat power, and combined cooling heat power, have been examined based on their structural characteristics. A review of the methods and the primary purpose of MES is also highlighted in this paper.

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“…In recent times the natural gas pipeline network optimization research have been categorised into two categories. The first category includes methods like regression method including stochastic [33], linear programming [1], interval analysis approach [4], a sequential quadratic method [10], a non-sequential quadratic method [6], a bi-level programing method [34] and economic nonlinear model [11] and the other category is intelligent method [18].…”

Section: Literature Surveymentioning

confidence: 99%

Optimization of city gas network: a case study from Gujarat, India

Sircar

Yadav

2019

SN Appl. Sci.

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A natural gas flow network consists of city gate station, district regulator, pipelines, compressors and valves. The performance of such a complex system cannot be studied by analysing individual constituents. Simultaneous performance of integrated system can be expressed using non-linear equations to simulate and forecast operational behaviour. The operational behaviour is subject to various alternative operational conditions also. Nodal analysis is performed to calculate the flow capacity of each network segment and the pressure at each node. Two conditions are evaluated, namely, keeping flow capacity unknown or by making nodal pressure primary unknown. The resulting set of governing equations are then solved simultaneously. Genetic algorithm method is applied to solve the desired target unknown. Compressor governs the energy supply required to transport gas from one end to another. The compressor equation is also incorporated in city gas network simulation. The simulations are performed by straight gas ducts and complex gas ducts. Boundary conditions are dependent on the form in which gas duct is fed. It is assumed that the gas duct takes gas from City Gate Station at x = 0 and supplies the gas to a consumer located at x = L according to a time variable curve demand Q n (L, t). The capacity of the compressor is also changed and it is observed that the demand is usually periodic in nature. Flow demand at individual node of a gas pipeline network is calculated. Pressures at various nodes are also calculated and matched with original pressure at nodes. Percentage deviation error suggest a range between 0 and 1.02%. The aim of this paper is to optimise certain parameters of a gas transmission pipeline network namely flow rate, mass, cost and pressure. This optimization is performed to gas transmission pipeline network of Gandhinagar, district, where Gujarat State Petronet Limited (GSPL) and Sabarmati Gas Limited (SGL) are the major players. The network which has been chosen for pipeline network consists of 10 CNG stations and 10 DRS.

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Development of natural gas flow rate in pipeline networks based on unsteady state Weymouth equation

Cited by 11 publications

References 18 publications

Study on optimal operation of natural gas pipeline network based on improved genetic algorithm

Study on optimal operation of natural gas pipeline network based on improved genetic algorithm

Multi Energy System With an Associated Energy Hub: A Review

Optimization of city gas network: a case study from Gujarat, India

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