The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Jinjun Zhang - One of the best experts on this subject based on the ideXlab platform.
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A method for the multi-objective optimization of the operation of Natural Gas Pipeline networks considering supply reliability and operation efficiency
Computers & Chemical Engineering, 2019Co-Authors: Enrico Zio, Jinjun Zhang, Lixun Chi, Lin Fan, Zongjie ZhangAbstract:Reliable Gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of Natural Gas Pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the Natural Gas Pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of Gas supply shortage. To quantify the probability of supply interruption in Pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multi-objective optimization problem is solved by the NSGA-II algorithm and its effectiveness is tested on two typical Pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing Gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization resu
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A systematic framework of vulnerability analysis of a Natural Gas Pipeline network
Reliability Engineering and System Safety, 2018Co-Authors: Enrico Zio, Jinjun ZhangAbstract:A systematic framework is developed to assess the vulnerability of Natural Gas Pipeline networks. To measure the impact of accidents on Gas supply service, a consequence model is developed based on a flow algorithm embedded into an optimization scheme, with the consideration of physical constraints. The vulnerability analysis is performed from three viewpoints: global vulnerability analysis, demand robustness and critical Pipeline analysis. The global vulnerability analysis is performed considering hazards and threats in Gas sources, demand and transmission system. The analysis of demand robustness evaluates the capacities of demand sites to withstand the strains imposed on the Pipeline network system and further explains the differences in capacities, from a graph theory perspective. In the critical Pipeline analysis, criticalities of Pipelines are evaluated by considering direct attacks and using a physical flow-based method. The analyses are performed on a relatively complex Gas Pipeline network taken from literature.
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An integrated systemic method for supply reliability assessment of Natural Gas Pipeline networks
Applied Energy, 2018Co-Authors: Jinjun Zhang, Enrico Zio, Nan Yang, Zongjie ZhangAbstract:A systematic method is developed for supply reliability assessment of Natural Gas Pipeline networks. In thedeveloped method, the integration of stochastic processes, graph theory and thermal-hydraulic simulation isperformed accounting for uncertainty and complexity. The supply capacity of a Pipeline network depends on theunit states and the network structure, both of which change stochastically because of stochastic failures of theunits. To describe this, in this work a capacity network stochastic model is developed, based on Markov mod-eling and graph theory. The model is embedded in an optimization algorithm to compute the capacities of thePipeline network under different scenarios and analyze the consequences of failures of units in the system.Indices of supply reliability and risk are developed with respect to two aspects: global system and individualcustomers. In the case study, a Gas Pipeline network is considered and the results are analyzed in detail.
Enrico Zio - One of the best experts on this subject based on the ideXlab platform.
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A method for the multi-objective optimization of the operation of Natural Gas Pipeline networks considering supply reliability and operation efficiency
Computers & Chemical Engineering, 2019Co-Authors: Enrico Zio, Jinjun Zhang, Lixun Chi, Lin Fan, Zongjie ZhangAbstract:Reliable Gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of Natural Gas Pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the Natural Gas Pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of Gas supply shortage. To quantify the probability of supply interruption in Pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multi-objective optimization problem is solved by the NSGA-II algorithm and its effectiveness is tested on two typical Pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing Gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization resu
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A systematic framework of vulnerability analysis of a Natural Gas Pipeline network
Reliability Engineering and System Safety, 2018Co-Authors: Enrico Zio, Jinjun ZhangAbstract:A systematic framework is developed to assess the vulnerability of Natural Gas Pipeline networks. To measure the impact of accidents on Gas supply service, a consequence model is developed based on a flow algorithm embedded into an optimization scheme, with the consideration of physical constraints. The vulnerability analysis is performed from three viewpoints: global vulnerability analysis, demand robustness and critical Pipeline analysis. The global vulnerability analysis is performed considering hazards and threats in Gas sources, demand and transmission system. The analysis of demand robustness evaluates the capacities of demand sites to withstand the strains imposed on the Pipeline network system and further explains the differences in capacities, from a graph theory perspective. In the critical Pipeline analysis, criticalities of Pipelines are evaluated by considering direct attacks and using a physical flow-based method. The analyses are performed on a relatively complex Gas Pipeline network taken from literature.
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An integrated systemic method for supply reliability assessment of Natural Gas Pipeline networks
Applied Energy, 2018Co-Authors: Jinjun Zhang, Enrico Zio, Nan Yang, Zongjie ZhangAbstract:A systematic method is developed for supply reliability assessment of Natural Gas Pipeline networks. In thedeveloped method, the integration of stochastic processes, graph theory and thermal-hydraulic simulation isperformed accounting for uncertainty and complexity. The supply capacity of a Pipeline network depends on theunit states and the network structure, both of which change stochastically because of stochastic failures of theunits. To describe this, in this work a capacity network stochastic model is developed, based on Markov mod-eling and graph theory. The model is embedded in an optimization algorithm to compute the capacities of thePipeline network under different scenarios and analyze the consequences of failures of units in the system.Indices of supply reliability and risk are developed with respect to two aspects: global system and individualcustomers. In the case study, a Gas Pipeline network is considered and the results are analyzed in detail.
Zongjie Zhang - One of the best experts on this subject based on the ideXlab platform.
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A method for the multi-objective optimization of the operation of Natural Gas Pipeline networks considering supply reliability and operation efficiency
Computers & Chemical Engineering, 2019Co-Authors: Enrico Zio, Jinjun Zhang, Lixun Chi, Lin Fan, Zongjie ZhangAbstract:Reliable Gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of Natural Gas Pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the Natural Gas Pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of Gas supply shortage. To quantify the probability of supply interruption in Pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multi-objective optimization problem is solved by the NSGA-II algorithm and its effectiveness is tested on two typical Pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing Gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization resu
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An integrated systemic method for supply reliability assessment of Natural Gas Pipeline networks
Applied Energy, 2018Co-Authors: Jinjun Zhang, Enrico Zio, Nan Yang, Zongjie ZhangAbstract:A systematic method is developed for supply reliability assessment of Natural Gas Pipeline networks. In thedeveloped method, the integration of stochastic processes, graph theory and thermal-hydraulic simulation isperformed accounting for uncertainty and complexity. The supply capacity of a Pipeline network depends on theunit states and the network structure, both of which change stochastically because of stochastic failures of theunits. To describe this, in this work a capacity network stochastic model is developed, based on Markov mod-eling and graph theory. The model is embedded in an optimization algorithm to compute the capacities of thePipeline network under different scenarios and analyze the consequences of failures of units in the system.Indices of supply reliability and risk are developed with respect to two aspects: global system and individualcustomers. In the case study, a Gas Pipeline network is considered and the results are analyzed in detail.
Wenguo Weng - One of the best experts on this subject based on the ideXlab platform.
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comparison study on qualitative and quantitative risk assessment methods for urban Natural Gas Pipeline network
Journal of Hazardous Materials, 2011Co-Authors: Z.y. Han, Wenguo WengAbstract:In this paper, a qualitative and a quantitative risk assessment methods for urban Natural Gas Pipeline network are proposed. The qualitative method is comprised of an index system, which includes a causation index, an inherent risk index, a consequence index and their corresponding weights. The quantitative method consists of a probability assessment, a consequences analysis and a risk evaluation. The outcome of the qualitative method is a qualitative risk value, and for quantitative method the outcomes are individual risk and social risk. In comparison with previous research, the qualitative method proposed in this paper is particularly suitable for urban Natural Gas Pipeline network, and the quantitative method takes different consequences of accidents into consideration, such as toxic Gas diffusion, jet flame, fire ball combustion and UVCE. Two sample urban Natural Gas Pipeline networks are used to demonstrate these two methods. It is indicated that both of the two methods can be applied to practical application, and the choice of the methods depends on the actual basic data of the Gas Pipelines and the precision requirements of risk assessment.
Anatoly Zlotnik - One of the best experts on this subject based on the ideXlab platform.
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an adversarial model for attack vector vulnerability analysis on power and Gas delivery operations
Electric Power Systems Research, 2020Co-Authors: Ignacio Losada Carreno, Anatoly Zlotnik, Anna Scaglione, Deepjyoti Deka, Kaarthik SundarAbstract:Abstract Power systems often rely on Natural Gas Pipeline networks to supply fuel for Gas-fired generation. Market inefficiencies and a lack of formal coordination between the wholesale power and Gas delivery infrastructures may magnify the broader impact of a cyber-attack on a Natural Gas Pipeline. In this study we present a model that can be used to quantify the impact of cyber-attacks on electricity and Gas delivery operations. We model activation of cyber-attack vectors that attempt to gain access to Pipeline Gas compressor controls using a continuous-time Markov chain over a state space based on the Gas operator Industrial Control System firewall zone partition. Our approach evaluates the operating states and decision-making in the networks using physically realistic and operationally representative models. We summarize these models, the sequence of analyses used to quantify the impacts of a cyber-incident, and propose a Monte Carlo simulation approach to quantify the resulting effect on the reliability of the bulk power system by the increase in operational cost. The methodology is applied to a case study of interacting power, Gas, and cyber test networks.
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state and parameter estimation for Natural Gas Pipeline networks using transient state data
IEEE Transactions on Control Systems and Technology, 2019Co-Authors: Kaarthik Sundar, Anatoly ZlotnikAbstract:We formulate two estimation problems for Pipeline systems in which measurements of the compressible Gas flowing through a network of pipes are affected by time-varying injections, withdrawals, and compression. We consider a state estimation problem that is then extended to a joint state and parameter estimation problem that can be used for data assimilation. In both formulations, the flow dynamics are described on each pipe by space- and time-dependent densities and mass flux which evolve according to a system of coupled partial differential equations, in which momentum dissipation is modeled using the Darcy–Wiesbach friction approximation. These dynamics are first spatially discretized to obtain a system of nonlinear ordinary differential equations on which state and parameter estimation formulations are given as nonlinear least squares problems. A rapid, scalable computational method for performing a nonlinear least squares estimation is developed. Extensive simulations and computational experiments on multiple Pipeline test networks demonstrate the effectiveness of the formulations in obtaining state and parameter estimates in the presence of measurement and process noise.
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dynamic compressor optimization in Natural Gas Pipeline systems
Informs Journal on Computing, 2019Co-Authors: Terrence W K Mak, Pascal Van Hentenryck, Anatoly Zlotnik, Russell BentAbstract:The growing dependence of electric power systems on Gas-fired generators to balance fluctuating and intermittent production by renewable energy sources has increased the variation and volume of flo...
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state and parameter estimation for Natural Gas Pipeline networks using transient state data
arXiv: Systems and Control, 2018Co-Authors: Kaarthik Sundar, Anatoly ZlotnikAbstract:We formulate two estimation problems for Pipeline systems in which measurements of compressible Gas flow through a network of pipes is affected by time-varying injections, withdrawals, and compression. We consider a state estimation problem that is then extended to a joint state and parameter estimation problem that can be used for data assimilation. In both formulations, the flow dynamics are described on each pipe by space- and time-dependent density and mass flux that evolve according to a system of coupled partial differential equations, in which momentum dissipation is modelled using the Darcy-Wiesbach friction approximation. These dynamics are first spatially discretized to obtain a system of nonlinear ordinary differential equations on which state and parameter estimation formulations are given as nonlinear least squares problems. A rapid, scalable computational method for performing a nonlinear least squares estimation is developed. Extensive simulations and computational experiments on multiple Pipeline test networks demonstrate the effectiveness of the formulations in obtaining state and parameter estimates in the presence of measurement and process noise.
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operator splitting method for simulation of dynamic flows in Natural Gas Pipeline networks
Physica D: Nonlinear Phenomena, 2017Co-Authors: Sergey A Dyachenko, Anatoly Zlotnik, A O Korotkevich, Michael ChertkovAbstract:Abstract We develop an operator splitting method to simulate flows of isothermal compressible Natural Gas over transmission Pipelines. The method solves a system of nonlinear hyperbolic partial differential equations (PDEs) of hydrodynamic type for mass flow and pressure on a metric graph, where turbulent losses of momentum are modeled by phenomenological Darcy–Weisbach friction. Mass flow balance is maintained through the boundary conditions at the network nodes, where Natural Gas is injected or withdrawn from the system. Gas flow through the network is controlled by compressors boosting pressure at the inlet of the adjoint pipe. Our operator splitting numerical scheme is unconditionally stable and it is second order accurate in space and time. The scheme is explicit, and it is formulated to work with general networks with loops. We test the scheme over range of regimes and network configurations, also comparing its performance with performance of two other state of the art implicit schemes.
