[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal ...[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal pollution of soil. [Method] The sampling data of soil copper from a county of Liaocheng, Shandong Province was set as the study objective. Kriging interpolation and sequential Gaussian simu- lation were used to simulate the spatial distribution of soil copper. And 30 sampling points were selected as the cross-validation data set to compare the two interpola- tion methods. [Result] Kriging method and Gaussian sequential simulation have their own advantages on simulating mean segment and extreme segment, therefore, re- searchers should choose the proper method based on the characteristics of test data and application purposes. [Conclusion] Analysis of soil heavy metal pollution is the prerequisite for soil management and ecological restoration. The result of this study is of important significance for choosing different interpolating and simulating methods to analyze soil heavy metal pollution based on different purposes.展开更多
Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local o...Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local or global uncertainty by honouring spatial correlation structures.The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit,Turkey.In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area.The simulation results were validated by a number of tests such as descriptive statistics,histogram,variogram and contour map reproductions.The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution.The simulated models can be incorporated into exploration,exploitation and scheduling of the gold deposit.展开更多
The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of ...The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of an open pit slope.For this purpose,spatially conditioned DFN models were developed for the pit walls at Tasiast mine using comprehensive structural data from the mine.Using Sequential Gaussian Simulation(SGS),volumetric fracture intensities(P32)were modeled across the entire mine site in the form of 3D block models.The simulated P32 block models were used as the input constraints for conditional DFN fracture generation,where the DFN grid dimension is the same as the SGS 3D blocks.The spatially constrained DFN models were further calibrated using aerial fracture intensities(P21)data from the pit walls,obtained by a survey of the pit walls using an unmanned aerial vehicle(UAV)and measured traces of joints from 3D point cloud data.The final DFN model is expected to honor the fracture intensities gathered through different means with optimal model accuracy.Finally,bench-scale and interramp scale rock wedge slope stability analyses were conducted using the calibrated conditional DFN models.This work proves the significance of conditioned DFN models in rock wedge stability analysis.Such models provide detailed information regarding rock wedge stability so that site monitoring and prevention plans can be conducted with higher efficiency.展开更多
The component aging has become a significant concern worldwide,and the frequent failures pose a serious threat to the reliability of modern power systems.In light of this issue,this paper presents a power system relia...The component aging has become a significant concern worldwide,and the frequent failures pose a serious threat to the reliability of modern power systems.In light of this issue,this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation(SMCS)to quantify system reliability considering multiple failure modes of components.First,a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure modes.In this model,the impact of each failure mode is decoupled and characterized as the combination of two state duration variables,which are separately modeled using specific probability distributions.Subsequently,SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability evaluation.Therefore,various reliability metrics,including the probability of load curtailment(PLC),expected frequency of load curtailment(EFLC),and expected energy not supplied(EENS),can be estimated.To ensure the applicability of the proposed method,Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational performance.Case studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.展开更多
In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of...In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.展开更多
Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation str...Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strategy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.展开更多
Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian S...Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian Simulation technology, in combination with the restriction of seismic characteristic data. Satisfactory reservoir parameter interpolation results, which are more accurate than those derived only from borehole data, are obtained, giving rise to a reasonable combination of widespread and dense-sampled seismic (soft data) data with borehole data (hard data). A significant effect has been made in reservoir parameter modeling in the Chegu 201 block of the Futai Oilfield by using this technology.展开更多
The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduc...The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduced for the lost-circulation risk sample profile of a drilled well.The model is built taking into account effective data(the Block L).Then,using a three-dimensional geological modeling software,relying on the variation function and sequential Gaussian simulation method,a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses.展开更多
Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ens...Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain(ECMC)is proposed.The ECMC method can effectively reduce redundant information in the data.First,the wind and photovoltaic power time series data were divided into scenarios,and ensemble clustering was used to cluster the divided scenarios.At the same time,the Davies-Bouldin Index(DBI)is adopted to select the optimal number of clusters.Then,according to the temporal correlation between wind and photovoltaic scenarios,the wind and photovoltaic clustering results are merged and reduced to form a set of combined typical day scenarios that can reflect the characteristics of historical data within the calculation period.Finally,based on the Markov Chain,the state transition probability matrix of various combined typical day scenarios is constructed,and the aggregation state sequence of random length is generated,and then,the combined typical day scenarios of wind and photovoltaic were sampled in a sequential one-way sequence according to the state sequence and then are built into a representative wind and photovoltaic power time series aggregation sequence.A provincial power grid was chosen as an example to compare the multiple evaluation indexes of different aggregation methods.The results show that the ECMC aggregation method improves the accuracy and efficiency of time sequential simulations.展开更多
At present, the problem of abandoning wind and PV power in “Three North” region of China is particularly significant, and how to alleviate this problem has become the focus of universal attention. Calculation of ren...At present, the problem of abandoning wind and PV power in “Three North” region of China is particularly significant, and how to alleviate this problem has become the focus of universal attention. Calculation of renewable energy accommodation capacity is the basis to solve the problem of abandoning wind and PV power. Main problems of Chinese renewable energy accommodation is analyzed from power supply, power grid and load side aspects, and it focuses on the effect of inter-provincial tie-line to renewable energy accommodation capacity. At present, the inter-provincial tie-line utilization level is limited, which affected renewable energy accommodation to a certain extent. Based on the sequential production simulation model, a new kind of renewable energy accommodation capacity model is put forward considering the utilization level of inter-provincial tie-line. According to different system stability constraints and different electricity constraints of inter-provincial tie-line, 4 schemes are designed for comparative analysis, and the evaluation model is used to calculate renewable energy accommodation capacity of “Three North” region of China in 2020. Example analysis results verify validity of the model that releasing curve constraints, electricity constraints and stability constraints in turn can significantly enhance renewable energy accommodation capacity through effective use of inter-provincial tie-line transmission capacity. Research work in this paper can provide strong support for the planning and scheduling control of power grid.展开更多
The research on reliability evaluation of an integrated energy system(IES)is of great significance to system planning and operations.The differences of multiple energy subsystems must be considered in reliability eval...The research on reliability evaluation of an integrated energy system(IES)is of great significance to system planning and operations.The differences of multiple energy subsystems must be considered in reliability evaluation of an IES,in which energy quality differences of various energy resources is critical.Current reliability evaluation of an IES cannot uniformly evaluate the reliability of multiple energy subsystems due to neglecting the energy quality differences of various energy resources.To address this problem,a novel reliability evaluation method for IESs based on exergy is proposed for the first time in this paper.The exergy of an energy resource or a substance is a measure of its usefulness,quality or potential to cause change.The models of exergy not supplied minimization and exergy efficiency maximization are proposed to alleviate energy capacity deficiency and transmission component overload in the reliability evaluation of an IES.These two models are compared to analyze exergy efficiency for the proposed method.The energy supply priority strategy of an IES is proposed considering energy quality differences of various energy resources,in which electricity,gas and heating/cooling subsystems are supplied in an orderly manner.Furthermore,a reliability evaluation indices system of an IES based on exergy is proposed in this paper.An extensive case study on an actual IES demonstrates the feasibility and effectiveness of the proposed reliability evaluation method.展开更多
Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)tech...Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.展开更多
Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need t...Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.展开更多
Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly ...Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly influenced by three-dimensional(3D)microstructures of porous media.In this study,fractal models are developed to investigate contaminant transport and surfactant-enhanced aquifer remediation(SEAR)for the regular tetrahedron microstructure(RTM)and right square pyramid microstructure(RSPM).The relationships of permeability and entry pressure are derived for these two kinds of 3D microstructures of granular porous media.Afterward,the difference in perchloroethylene(PCE)migration and SEAR efficiency between RTM and RSPM is investigated by the numerical simulation based on a synthetic heterogeneous granular aquifer.Results indicate that PCE penetrates faster and spreads farther in RSPM-based aquifers compared with RTM-based aquifers.Further,SEAR in RTM-based aquifers can achieve remediation efficiencies of 66.129%-92.214%with a mean of 84.324%,which is clearly lower than the SEAR efficiency of 70.149%-94.773%(with a mean of 89.122%)in RSPM-based aquifers.Findings are significant for understanding the 3D microstructure of porous media and how the microstructure of porous media affects macroscopic contaminant behaviors and remediation.展开更多
基金Supported by the Science and Technology Development Program of Shandong Province (Soft Science) (2009RKB220),China~~
文摘[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal pollution of soil. [Method] The sampling data of soil copper from a county of Liaocheng, Shandong Province was set as the study objective. Kriging interpolation and sequential Gaussian simu- lation were used to simulate the spatial distribution of soil copper. And 30 sampling points were selected as the cross-validation data set to compare the two interpola- tion methods. [Result] Kriging method and Gaussian sequential simulation have their own advantages on simulating mean segment and extreme segment, therefore, re- searchers should choose the proper method based on the characteristics of test data and application purposes. [Conclusion] Analysis of soil heavy metal pollution is the prerequisite for soil management and ecological restoration. The result of this study is of important significance for choosing different interpolating and simulating methods to analyze soil heavy metal pollution based on different purposes.
文摘Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local or global uncertainty by honouring spatial correlation structures.The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit,Turkey.In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area.The simulation results were validated by a number of tests such as descriptive statistics,histogram,variogram and contour map reproductions.The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution.The simulated models can be incorporated into exploration,exploitation and scheduling of the gold deposit.
基金Kinross Gold and MITACS for their financial support(Grant No.FR42880).
文摘The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of an open pit slope.For this purpose,spatially conditioned DFN models were developed for the pit walls at Tasiast mine using comprehensive structural data from the mine.Using Sequential Gaussian Simulation(SGS),volumetric fracture intensities(P32)were modeled across the entire mine site in the form of 3D block models.The simulated P32 block models were used as the input constraints for conditional DFN fracture generation,where the DFN grid dimension is the same as the SGS 3D blocks.The spatially constrained DFN models were further calibrated using aerial fracture intensities(P21)data from the pit walls,obtained by a survey of the pit walls using an unmanned aerial vehicle(UAV)and measured traces of joints from 3D point cloud data.The final DFN model is expected to honor the fracture intensities gathered through different means with optimal model accuracy.Finally,bench-scale and interramp scale rock wedge slope stability analyses were conducted using the calibrated conditional DFN models.This work proves the significance of conditioned DFN models in rock wedge stability analysis.Such models provide detailed information regarding rock wedge stability so that site monitoring and prevention plans can be conducted with higher efficiency.
基金supported by the National Natural Science Foundation of China(No.52022016)the Fundamental Research Funds for the Central Universities(No.2023CDJYXTD-004)the Graduate Research and Innovation Foundation of Chongqing(No.CYB22014)。
文摘The component aging has become a significant concern worldwide,and the frequent failures pose a serious threat to the reliability of modern power systems.In light of this issue,this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation(SMCS)to quantify system reliability considering multiple failure modes of components.First,a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure modes.In this model,the impact of each failure mode is decoupled and characterized as the combination of two state duration variables,which are separately modeled using specific probability distributions.Subsequently,SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability evaluation.Therefore,various reliability metrics,including the probability of load curtailment(PLC),expected frequency of load curtailment(EFLC),and expected energy not supplied(EENS),can be estimated.To ensure the applicability of the proposed method,Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational performance.Case studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant(51777066).
文摘In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.
基金Supported by the National Basic Research Program of China(2013CB733600)
文摘Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strategy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.
文摘Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian Simulation technology, in combination with the restriction of seismic characteristic data. Satisfactory reservoir parameter interpolation results, which are more accurate than those derived only from borehole data, are obtained, giving rise to a reasonable combination of widespread and dense-sampled seismic (soft data) data with borehole data (hard data). A significant effect has been made in reservoir parameter modeling in the Chegu 201 block of the Futai Oilfield by using this technology.
文摘The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduced for the lost-circulation risk sample profile of a drilled well.The model is built taking into account effective data(the Block L).Then,using a three-dimensional geological modeling software,relying on the variation function and sequential Gaussian simulation method,a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses.
基金supported by the National Key R&D Program of China(2017YFB0902200)Science and Technology Project of State Grid Corporation of China(4000-202255057A-1-1-ZN,5228001700CW).
文摘Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain(ECMC)is proposed.The ECMC method can effectively reduce redundant information in the data.First,the wind and photovoltaic power time series data were divided into scenarios,and ensemble clustering was used to cluster the divided scenarios.At the same time,the Davies-Bouldin Index(DBI)is adopted to select the optimal number of clusters.Then,according to the temporal correlation between wind and photovoltaic scenarios,the wind and photovoltaic clustering results are merged and reduced to form a set of combined typical day scenarios that can reflect the characteristics of historical data within the calculation period.Finally,based on the Markov Chain,the state transition probability matrix of various combined typical day scenarios is constructed,and the aggregation state sequence of random length is generated,and then,the combined typical day scenarios of wind and photovoltaic were sampled in a sequential one-way sequence according to the state sequence and then are built into a representative wind and photovoltaic power time series aggregation sequence.A provincial power grid was chosen as an example to compare the multiple evaluation indexes of different aggregation methods.The results show that the ECMC aggregation method improves the accuracy and efficiency of time sequential simulations.
基金supported by project of the National Key Research and Development Program Foundation of China(2016YFB0900100).
文摘At present, the problem of abandoning wind and PV power in “Three North” region of China is particularly significant, and how to alleviate this problem has become the focus of universal attention. Calculation of renewable energy accommodation capacity is the basis to solve the problem of abandoning wind and PV power. Main problems of Chinese renewable energy accommodation is analyzed from power supply, power grid and load side aspects, and it focuses on the effect of inter-provincial tie-line to renewable energy accommodation capacity. At present, the inter-provincial tie-line utilization level is limited, which affected renewable energy accommodation to a certain extent. Based on the sequential production simulation model, a new kind of renewable energy accommodation capacity model is put forward considering the utilization level of inter-provincial tie-line. According to different system stability constraints and different electricity constraints of inter-provincial tie-line, 4 schemes are designed for comparative analysis, and the evaluation model is used to calculate renewable energy accommodation capacity of “Three North” region of China in 2020. Example analysis results verify validity of the model that releasing curve constraints, electricity constraints and stability constraints in turn can significantly enhance renewable energy accommodation capacity through effective use of inter-provincial tie-line transmission capacity. Research work in this paper can provide strong support for the planning and scheduling control of power grid.
基金supported in part by the National Natural Science Foundation of China under Grant No.51637008 and No.U1610122.
文摘The research on reliability evaluation of an integrated energy system(IES)is of great significance to system planning and operations.The differences of multiple energy subsystems must be considered in reliability evaluation of an IES,in which energy quality differences of various energy resources is critical.Current reliability evaluation of an IES cannot uniformly evaluate the reliability of multiple energy subsystems due to neglecting the energy quality differences of various energy resources.To address this problem,a novel reliability evaluation method for IESs based on exergy is proposed for the first time in this paper.The exergy of an energy resource or a substance is a measure of its usefulness,quality or potential to cause change.The models of exergy not supplied minimization and exergy efficiency maximization are proposed to alleviate energy capacity deficiency and transmission component overload in the reliability evaluation of an IES.These two models are compared to analyze exergy efficiency for the proposed method.The energy supply priority strategy of an IES is proposed considering energy quality differences of various energy resources,in which electricity,gas and heating/cooling subsystems are supplied in an orderly manner.Furthermore,a reliability evaluation indices system of an IES based on exergy is proposed in this paper.An extensive case study on an actual IES demonstrates the feasibility and effectiveness of the proposed reliability evaluation method.
文摘Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.
文摘Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.
基金supported by the National Key Research and Development Plan of China (no.2019YFC1804302)the Natural Science Foundation of Guangdong Province (no.2023A1515012228)Guangdong Provincial Environmental Protection Fund (Guangdong Financial Budget 20244).
文摘Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly influenced by three-dimensional(3D)microstructures of porous media.In this study,fractal models are developed to investigate contaminant transport and surfactant-enhanced aquifer remediation(SEAR)for the regular tetrahedron microstructure(RTM)and right square pyramid microstructure(RSPM).The relationships of permeability and entry pressure are derived for these two kinds of 3D microstructures of granular porous media.Afterward,the difference in perchloroethylene(PCE)migration and SEAR efficiency between RTM and RSPM is investigated by the numerical simulation based on a synthetic heterogeneous granular aquifer.Results indicate that PCE penetrates faster and spreads farther in RSPM-based aquifers compared with RTM-based aquifers.Further,SEAR in RTM-based aquifers can achieve remediation efficiencies of 66.129%-92.214%with a mean of 84.324%,which is clearly lower than the SEAR efficiency of 70.149%-94.773%(with a mean of 89.122%)in RSPM-based aquifers.Findings are significant for understanding the 3D microstructure of porous media and how the microstructure of porous media affects macroscopic contaminant behaviors and remediation.
