Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operat...Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operating costs.Meanwhile,oil depots and pipelines form an entire system,and each operation in a single oil depot may have influence on others.It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration.So far,studies simultaneously considering operating constraints and contaminated oil issues are rare.Aiming at making a scheduling plan with the lowest operating costs,the paper establishes a mixed-integer linear programming model,considering a sequence of operations,such as delivery, export, blending,fractionating and exchanging operations,and batch property differences of the same oil as well as influence of batch migration on contaminated volume.Moreover,the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction.Finally,the model is successfully applied to one of the product pipelines in China and proved to be practical.展开更多
The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manag...The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).展开更多
With the increasing interdependence of various energy carriers,the operation of power systems is found to correlate closely with the limitations on the other energy infrastructures.This paper presents a mixed-integer ...With the increasing interdependence of various energy carriers,the operation of power systems is found to correlate closely with the limitations on the other energy infrastructures.This paper presents a mixed-integer linear programming(MILP)model for the microgrid(MG)optimal scheduling considering technical and economic ties between electricity and natural gas(NG)systems.In the proposed methodology,different energy converters and storages,including combined heat and power(CHP)units,electricity/heat storage units,and distributed energy resources(DERs)are considered.The proposed model allows the MG operator to minimize the operation cost of the MG while different operational limitations on the energy hub are satisfied.The model is developed based on AC power flow constraints so as to respect reactive power and voltage security constraints.The efficiency and robustness of the proposed MILP formulation are successfully verified using a large-scale test MG.展开更多
Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities an...Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities and limited recovery resources.Information and communication technologies(ICTs)have introduced new vulnerabilities that have been widely investigated in previous studies.These vulnerabilities include remote device failures,communication channel disturbances,and cyberattacks.However,only few studies have explored the opportunity offered by communications to improve the resilience of power grids and eliminate the notion that power-telecom interdependencies always pose a threat.This paper proposes a communication-aware restoration approach of smart distribution grids,which leverages power-telecom interdependencies to determine the optimal restoration strategies.The states of grid-energized telecom points are tracked to provide the best restoration actions,which are enabled through the resilience resources of repair,manual switching,remote reconfiguration,and distributed generators.As the telecom network coordinates the allocation of these resilience resources based on their coupling tendencies,different telecom architectures have been introduced to investigate the contribution of private and public ICTs to grid management and restoration operations.System restoration uses the configuration that follows a remote fast response as the input to formulate the problem as mixed-integer linear programming.Results from numerical simulations reveal an enhanced restoration process derived from telecom-aware recovery and the co-optimization of resilience resources.The existing disparity between overhead and underground power line configurations is also quantified.展开更多
This paper analyzes the oligopolistic equilibria of multiple price-maker agents in performance-based regulation(PBR)markets.In these markets,there are price-maker agents representing some frequency regulation(FR)provi...This paper analyzes the oligopolistic equilibria of multiple price-maker agents in performance-based regulation(PBR)markets.In these markets,there are price-maker agents representing some frequency regulation(FR)providers and a number of independent price-taker FR providers.A model of equilibrium problem with equilibrium constraints(EPECs)is employed in this paper to study the equilibria of a PBR market in the presence of price-maker agents and price-taker FR providers.Due to the incorporation of the FR providers’dynamics,the proposed model is reformulated as a mixed-integer linear programming(MILP)problem over innovative mathematical techniques.An optimal equilibrium point is also selected for the market,where none of the agents is the unique deviator and the dynamic performance of power system is improved simultaneously.The effectiveness of the proposed optimal equilibrium point is evaluated by comparing the outputs with the conventional optimal dispatches of the FR providers.展开更多
Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution systems.In this paper,we provide analytical bounds on the performance...Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution systems.In this paper,we provide analytical bounds on the performance of the state estimator as a function of perturbations in the input measurements.It has already been shown that evaluating performance based only on the test dataset might not effectively indicate the ability of a trained DNN to handle input perturbations.As such,we analytically verify the robustness and trustworthiness of DNNs to input perturbations by treating them as mixed-integer linear programming(MILP)problems.The ability of batch normalization in addressing the scalability limitations of the MILP formulation is also highlighted.The framework is validated by performing time-synchronized distribution system state estimation for a modified IEEE 34-node system and a real-world large distribution system,both of which are incompletely observed by micro-phasor measurement units.展开更多
基金part of the Program of ‘‘Study of the mechanism of complex heat and mass transfer during batch transport process in product pipelines’’ funded under the National Natural Science Foundation of China, Grant Number 51474228
文摘Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operating costs.Meanwhile,oil depots and pipelines form an entire system,and each operation in a single oil depot may have influence on others.It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration.So far,studies simultaneously considering operating constraints and contaminated oil issues are rare.Aiming at making a scheduling plan with the lowest operating costs,the paper establishes a mixed-integer linear programming model,considering a sequence of operations,such as delivery, export, blending,fractionating and exchanging operations,and batch property differences of the same oil as well as influence of batch migration on contaminated volume.Moreover,the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction.Finally,the model is successfully applied to one of the product pipelines in China and proved to be practical.
文摘The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).
文摘With the increasing interdependence of various energy carriers,the operation of power systems is found to correlate closely with the limitations on the other energy infrastructures.This paper presents a mixed-integer linear programming(MILP)model for the microgrid(MG)optimal scheduling considering technical and economic ties between electricity and natural gas(NG)systems.In the proposed methodology,different energy converters and storages,including combined heat and power(CHP)units,electricity/heat storage units,and distributed energy resources(DERs)are considered.The proposed model allows the MG operator to minimize the operation cost of the MG while different operational limitations on the energy hub are satisfied.The model is developed based on AC power flow constraints so as to respect reactive power and voltage security constraints.The efficiency and robustness of the proposed MILP formulation are successfully verified using a large-scale test MG.
基金supported by EDF/Orange/SNCF in the framework of the Chair on Risk and Resilience of Complex Systems(CentraleSupelec,EDF,Orange,SNCF).
文摘Although power grids have become safer with increased situational awareness,major extreme events still pose reliability and resilience challenges,primarily at the distribution level,due to increased vulnerabilities and limited recovery resources.Information and communication technologies(ICTs)have introduced new vulnerabilities that have been widely investigated in previous studies.These vulnerabilities include remote device failures,communication channel disturbances,and cyberattacks.However,only few studies have explored the opportunity offered by communications to improve the resilience of power grids and eliminate the notion that power-telecom interdependencies always pose a threat.This paper proposes a communication-aware restoration approach of smart distribution grids,which leverages power-telecom interdependencies to determine the optimal restoration strategies.The states of grid-energized telecom points are tracked to provide the best restoration actions,which are enabled through the resilience resources of repair,manual switching,remote reconfiguration,and distributed generators.As the telecom network coordinates the allocation of these resilience resources based on their coupling tendencies,different telecom architectures have been introduced to investigate the contribution of private and public ICTs to grid management and restoration operations.System restoration uses the configuration that follows a remote fast response as the input to formulate the problem as mixed-integer linear programming.Results from numerical simulations reveal an enhanced restoration process derived from telecom-aware recovery and the co-optimization of resilience resources.The existing disparity between overhead and underground power line configurations is also quantified.
文摘This paper analyzes the oligopolistic equilibria of multiple price-maker agents in performance-based regulation(PBR)markets.In these markets,there are price-maker agents representing some frequency regulation(FR)providers and a number of independent price-taker FR providers.A model of equilibrium problem with equilibrium constraints(EPECs)is employed in this paper to study the equilibria of a PBR market in the presence of price-maker agents and price-taker FR providers.Due to the incorporation of the FR providers’dynamics,the proposed model is reformulated as a mixed-integer linear programming(MILP)problem over innovative mathematical techniques.An optimal equilibrium point is also selected for the market,where none of the agents is the unique deviator and the dynamic performance of power system is improved simultaneously.The effectiveness of the proposed optimal equilibrium point is evaluated by comparing the outputs with the conventional optimal dispatches of the FR providers.
基金supported in part by the Department of Energy(No.DE-AR-0001001,No.DE-EE0009355)the National Science Foundation(NSF)(No.ECCS-2145063)。
文摘Recently,we demonstrated the success of a time-synchronized state estimator using deep neural networks(DNNs)for real-time unobservable distribution systems.In this paper,we provide analytical bounds on the performance of the state estimator as a function of perturbations in the input measurements.It has already been shown that evaluating performance based only on the test dataset might not effectively indicate the ability of a trained DNN to handle input perturbations.As such,we analytically verify the robustness and trustworthiness of DNNs to input perturbations by treating them as mixed-integer linear programming(MILP)problems.The ability of batch normalization in addressing the scalability limitations of the MILP formulation is also highlighted.The framework is validated by performing time-synchronized distribution system state estimation for a modified IEEE 34-node system and a real-world large distribution system,both of which are incompletely observed by micro-phasor measurement units.
