A multi-objective optimization model for gas pipeline operations

Demissie, Alem; Zhu, Weihang; Belachew, Chanyalew Taye

doi:10.1016/j.compchemeng.2017.02.017

Cited by 84 publications

(31 citation statements)

References 19 publications

(19 reference statements)

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“…14 Another popular topic on steady-state pipeline problems is multiobjective optimization, where typical conflicting objectives are minimizing compressor power consumption and maximizing transported gas volume. 15,16 However, steady-state models cannot describe transient behaviors of gas for short-term operations, where the gas state changes over time due to process disturbance, market fluctuation, etc. Therefore, dynamic models with time-varying differential equations are often formulated to handle it.…”

Section: Mikolajková Et Al Linearized the Minlp Model Of Pipeline Nementioning

confidence: 99%

“…Koch et al reformulated discrete aspects with complementarity constraints and a mathematical program with equilibrium constraints (MPEC) model was solved instead . Another popular topic on steady‐state pipeline problems is multiobjective optimization, where typical conflicting objectives are minimizing compressor power consumption and maximizing transported gas volume …”

Section: Introductionmentioning

confidence: 99%

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Dynamic optimization for gas blending in pipeline networks with gas interchangeability control

Kazi

Biegler

et al. 2020

AIChE Journal

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The increasing penetration of unconventional gas and liquefied natural gas poses an operational challenge on existing regional gas networks for gas quality problems. A new dynamic model for natural gas pipeline network with multiple supplies is presented with a special emphasis on gas interchangeability control. Wobbe index serves as gas interchangeability indicator and is calculated by equations derived from rigorous composition‐based partial differential equations. Disjunctive formulation is applied to represent different modes of gas blending due to gas reversal, and the disjunctive model is then reformulated as a nonsmooth model with min/max and absolute value functions, which is solved by a gradient‐based nonlinear program solver after smooth approximation. Moreover, a heuristic algorithm is proposed to tune the penalty parameters in order to focus on different penalty terms while keeping the model well‐conditioned. The developed model and strategy are first tested with a small pipeline network model and then extended to a large model. The results show that the model can effectively manage gas interchangeability issues in pipeline networks within reasonable CPU time.

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Section: Mikolajková Et Al Linearized the Minlp Model Of Pipeline Nementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic optimization for gas blending in pipeline networks with gas interchangeability control

Kazi

Biegler

et al. 2020

AIChE Journal

View full text Add to dashboard Cite

show abstract

“…Zhang and Ma [48] developed a multiobjective optimal model considering minimization of production cost and minimization of operation cost based on NSGA-II and covariance matrix adaptation evolution strategy (CMA-ES). Yang et al [49] proposed a new multiobjective optimization method for sheet metal part based on the 8 Mathematical Problems in Engineering In order to solve the complex multiobjective optimal performance design of parameters, NSGA-II is used to find a much better spread of design solutions and better convergence near the true Pareto-optimal front [50][51][52]. After obtaining the pressure field and the temperature field, the multiobjective optimization model (MOO) of the quality of the injection molding products is further established.…”

Section: Multiobjective Optimization Model Using Nsga-ii Inmentioning

confidence: 99%

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

Wang

Zhang

2018

Mathematical Problems in Engineering

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The viscoelastic injection molding involves multidisciplinary thermoplastic rheomolding parameters which is a complex mathematical problem. Particularly for rheomolding of complex parts with thin-walled structure, boss, and grooves, the increasing higher requirements on energy efficiency and rheomolding quality are put forward. Therefore, an energy-efficient enhancement method for viscoelastic injection molding using hierarchy orthogonal optimization (HOO) is proposed. Based on the thermoplastic rheomolding theory and considering the viscoelastic effects in injection molding, a set of partial differential equations (PDE) describing the physical coupling behavior of the mold-melt-injection molding machine is established. The fuzzy sliding mode control (FSMC) is used to reduce the energy consumption in the control system of the injection molding machine's clamping force. Then, the HOO model of viscoelastic injection rheomolding is built in terms of thermoplastic rheomolding parameters and injection machine parameters. In initial hierarchy, through Taguchi orthogonal experiment and Analysis of Variance (ANOVA), the amount of gate, melt temperature, mold temperature, and packing pressure are extracted as the significant influence parameters. In periodical hierarchy, the multiobjective optimization model takes the forming time, warping deformation, and energy consumption of injection molding as the multiple objectives. The NSGA-II (Nondominated Sorting Genetic Algorithm II) optimization is employed to obtain the optimal solution through the global Pareto front. In ultimate hierarchy, three candidate schemes are compared on multiple objectives to determine the final energy-efficient enhancement scheme. A typical temperature controller part is analyzed and the energy consumption of injection molding is reduced by 41.85%. Through the physical experiment of injection process, the proposed method is further verified.

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“…Natural gas is a kind of high-quality, efficient, clean energy and raw material. Since the 1970s, the development of natural gas in the world has been accelerated, and the research on gas exploitation, transportation, and storage has received increasing attention [1][2][3][4][5][6][7]. Nowadays, natural gas pipelines account for almost half of the total length of pipelines in the world.…”

Section: Introductionmentioning

confidence: 99%

An EKF-Based Method and Experimental Study for Small Leakage Detection and Location in Natural Gas Pipelines

Hou

Zhu

2019

Applied Sciences

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Small leaks in natural gas pipelines are hard to detect, and there are few studies on this problem in the literature. In this paper, a method based on the extended Kalman filter (EKF) is proposed to detect and locate small leaks in natural gas pipelines. First, the method of a characteristic line is used to establish a discrete model of transient pipeline flow. At the same time, according to the basic idea of EKF, a leakage rate is distributed to each segment of the discrete model to obtain a model with virtual multi-point leakage. As such, the virtual leakage rate becomes a component of the state variables in the model. Secondly, system noise and measurement noise are considered, and the optimal hydraulic factors such as leakage rate are estimated using EKF. Finally, by using the idea of an equivalent pipeline, the actual leakage rate is calculated and the location of leakage on the pipeline is assessed. Simulation and experimental results show that this method can consistently predict the leakage rate and location and is sensitive to small leakages in a natural gas pipeline.

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A multi-objective optimization model for gas pipeline operations

Cited by 84 publications

References 19 publications

Dynamic optimization for gas blending in pipeline networks with gas interchangeability control

Dynamic optimization for gas blending in pipeline networks with gas interchangeability control

Energy-Efficient Enhancement for Viscoelastic Injection Rheomolding Using Hierarchy Orthogonal Optimization

An EKF-Based Method and Experimental Study for Small Leakage Detection and Location in Natural Gas Pipelines

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