Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable ene...Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.展开更多
With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and ...With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.展开更多
Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this ...Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.展开更多
Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation ...Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.展开更多
To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for l...To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.展开更多
Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evo...Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evolution process of ancient coal-bearing strata is characterized by multiple geological times,leading to obvious distinctions in their hydrocarbon generation potential,geological processes,and production,which affect the evaluation and exploration of hydrocarbon resources derived from coaly source rocks worldwide.This study aimed to identify the differences on oil-generated parent macerals and the production of oil generated from different coaly source rocks and through different oil generation processes.Integrating with the analysis of previous tectonic burial history and hydrocarbon generation history,high-temperature and high-pressure thermal simulation experiments,organic geochemistry,and organic petrology were performed on the Carboniferous-Permian(C-P)coaly source rocks in the Huanghua Depression,Bohai Bay Basin.The oil-generated parent macerals of coal's secondary oil generation process(SOGP)were mainly hydrogen-rich collotelinite,collodetrinite,sporinite,and cutinite,while the oil-generated parent macerals of tertiary oil generation process(TOGP)were the remaining small amount of hydrogen-rich collotelinite,sporinite,and cutinite,as well as dispersed soluble organic matter and unexhausted residual hydrocarbons.Compared with coal,the oil-generated parent macerals of coaly shale SOGP were mostly sporinite and cutinite.And part of hydrogen-poor vitrinite,lacking hydrocarbon-rich macerals,and macerals of the TOGP,in addition to some remaining cutinite and a small amount of crude oil and bitumen from SOGP contributed to the oil yield.The results indicated that the changes in oil yield had a good junction between SOGP and TOGP,both coal and coaly shale had higher SOGP aborted oil yield than TOGP starting yield,and coaly shale TOGP peak oil yield was lower than SOGP peak oil yield.There were significant differences in saturated hydrocarbon and aromatic parameters in coal and coaly shale.Coal SOGP was characterized by a lower Ts/Tm and C31-homohopane22S/(22S+22R)and a higher Pr/n C17compared to coal TOGP,while the aromatic parameter methyl dibenzothiophene ratio(MDR)exhibited coaly shale TOGP was higher than coaly shale SOGP than coaly TOGP than coaly SOGP,and coal trimethylnaphthalene ratio(TNR)was lower than coaly shale TNR.Thus,we established oil generation processes and discriminative plates.In this way,we distinguished the differences between oil generation parent maceral,oil generation time,and oil production of coaly source rocks,and therefore,we provided important support for the evaluation,prediction,and exploration of oil resources from global ancient coaly source rocks.展开更多
As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and m...As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.展开更多
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ...Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.展开更多
The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, a...The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, and metabolome (multi-layered omics data). In Systems Biology, we try to elucidate various dynamical characteristics of biological functions with applying the omics data to detailed mathematical model based on the central dogma. However, such mathematical models possess multi-time-scale properties which are often accompanied by time-scale differences seen among biological layers. The differences cause time stiff problem, and have a grave influence on numerical calculation stability. In the present conventional method, the time stiff problem remained because the calculation of all layers was implemented by adaptive time step sizes of the smallest time-scale layer to ensure stability and maintain calculation accuracy. In this paper, we designed and developed an effective numerical calculation method to improve the time stiff problem. This method consisted of ahead, backward, and cumulative algorithms. Both ahead and cumulative algorithms enhanced calculation efficiency of numerical calculations via adjustments of step sizes of each layer, and reduced the number of numerical calculations required for multi-time-scale models with the time stiff problem. Backward algorithm ensured calculation accuracy in the multi-time-scale models. In case studies which were focused on three layers system with 60 times difference in time-scale order in between layers, a proposed method had almost the same calculation accuracy compared with the conventional method in spite of a reduction of the total amount of the number of numerical calculations. Accordingly, the proposed method is useful in a numerical analysis of multi-time-scale models with time stiff problem.展开更多
The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustab...The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustable load, DGs, storage and dynamic power price) is studied. A multi-timescale collaborative optimization model is built towards microgrid;main measures in different timescale optimization are realized. An improved adaptive genetic algorithm is used to solve the optimization problem, which improved the efficiency and reliability. The proposed optimization model is simulated in IEEE 33 node system;the results show it’s effective.展开更多
The increasing integration of renewable energy sources and power electronic devices has significantly increased the complexity of modern power systems,making modeling and simulation challenging due to multi-time scale...The increasing integration of renewable energy sources and power electronic devices has significantly increased the complexity of modern power systems,making modeling and simulation challenging due to multi-time scale dynamics and multi-physics coupling.To address these challenges,this paper proposes a multi-level simulation framework based on unified energy flow theory.The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports,ensuring compatibility with artificial intelligence algorithms.By integrating AI techniques,such as back propagation neural networks,the framework predicts variables with high computational complexity,improving accuracy and simulation efficiency.A multi-level simulation architecture leveraging Field Programmable Gate Arrays(FPGAs)enables faster-than-real-time system-level simulation and real-time component-level modeling with time resolution as small as 5 nanoseconds.A DC microgrid case study with photovoltaic generation,battery storage,and power electronic converters demonstrates the proposed method,achieving up to a 500×speedup over traditional Simulink models while maintaining high accuracy.The results confirm the framework’s ability to capture multiphysics interactions,optimize energy distribution,and ensure system stability under dynamic conditions,providing an efficient and scalable solution for advanced DC microgrid simulations.展开更多
Electric power infrastructure has recently undergone a comprehensive transformation from electromagnetics to semiconductors. Such a development is attributed to the rapid growth of power electronic converter applicati...Electric power infrastructure has recently undergone a comprehensive transformation from electromagnetics to semiconductors. Such a development is attributed to the rapid growth of power electronic converter applications in the load side to realize energy conservation and on the supply side for renewable generations and power transmissions using high voltage direct current transmission. This transformation has altered the fundamental mechanism of power system dynamics, which demands the establishment of a new theory for power system control and protection. This paper presents thoughts on a theoretical framework for the coming semiconducting power systems.展开更多
Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control str...Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control structure,which successively requires a correction between schedule plans within multi-time scale.In order to address this problem,this paper develops an information integration method integrating complicated relationships among fuel cost,total thermal power output,reserve capacity,owned reserves and expectations of load shedding and wind curtailment,into three types of time-related relationship curves・Furthermore,a multi-time scale tieline energy and reserves allocation model is proposed,which contains two levels in the control structure,two time scales in dispatch sequence and multiple areas integrated within wind farms as scheduling objects・The efficiency of the proposed method is tested in a 9-bus test system and IEEE 118-bus system.The results show that a cross-regional control center is able to approach the optimal scheduling results of the whole system with the integrated uploaded relationship curves.The proposed model not only relieves energy and reserve shortages in partial areas but also allocates them to more urgent need areas in a high effectivity manner in both day-ahead and intraday time scales.展开更多
针对可再生能源高比例渗透下多区域综合能源互联系统(Multi-region integrated energy interconnection system,MRIEIS)所面临的消纳与经济性挑战,构建了一个包含电、氢、热、冷多能流的多时间尺度优化调度模型。该模型以系统日总运行...针对可再生能源高比例渗透下多区域综合能源互联系统(Multi-region integrated energy interconnection system,MRIEIS)所面临的消纳与经济性挑战,构建了一个包含电、氢、热、冷多能流的多时间尺度优化调度模型。该模型以系统日总运行成本最低为目标,建立动态多能流枢纽深度集成了电转氢(Power to hydrogen,P2H)、储氢罐、氢气管网以及燃气轮机(GT)掺氢等动态调度关键技术。通过日前、日内、实时三阶段滚动优化对系统进行精细化调度。算例分析基于一个包含居民、工业和混合型区域的典型场景,结果表明,该模型能够有效实现系统经济性与环保性的统一,总运行成本控制在56.48万元,同时系统总可再生能源利用率高达98.53%。氢能作为灵活的能量载体,其时空价值得到了充分发挥。掺氢策略有效刺激了氢能消耗,形成了“制-储-输-用”的闭环,为构建以新能源为主体的新型电力系统提供了可行的技术路径和调度策略参考。展开更多
滚动轴承是机械设备中的常见关键部件,准确预测其剩余使用寿命对机械设备的安全稳定运行至关重要。针对目前轴承寿命预测存在的轴承退化特征不明显、模型泛化能力差以及数据长期依赖关系难以捕捉的问题,提出基于时频域信号优化器(Time-F...滚动轴承是机械设备中的常见关键部件,准确预测其剩余使用寿命对机械设备的安全稳定运行至关重要。针对目前轴承寿命预测存在的轴承退化特征不明显、模型泛化能力差以及数据长期依赖关系难以捕捉的问题,提出基于时频域信号优化器(Time-Frequency domain signal Ratio Optimizer,TFRO)的多重膨胀多核时间卷积网络(Multi inflated Multi kernel Time Convolutional Network,Mi-MkTCN)模型。TFRO优化器为了精准记忆重要信息,在每一个时间节点上,将过去信息和当前信息重组,其中过去信息中的重要的时频域特征经过了有比例的分配。Mi-MkTCN利用多重膨胀确保重要特征不丢失,再利用多核时间卷积网络实现对不同尺度特征的提取。最终的消融对比实验验证了改进方法的有效性,模型的平均绝对误差、均方误差及均方根误差指标分别为0.00145、0.05069和0.12045。实验结果表明,所提方法显著提升了轴承剩余使用寿命的预测精度,为轴承剩余使用寿命预测提供了高精度、高鲁棒性的解决方案。展开更多
导航系统依赖传感器感知周围环境。当前,基于单一传感器的导航系统已难以满足各类复杂场景下的导航需求,导航系统正朝传感器多源化方向发展。在多源传感器数据融合过程中,图像数据的处理最消耗时间和资源,对系统性能影响最大。为解决这...导航系统依赖传感器感知周围环境。当前,基于单一传感器的导航系统已难以满足各类复杂场景下的导航需求,导航系统正朝传感器多源化方向发展。在多源传感器数据融合过程中,图像数据的处理最消耗时间和资源,对系统性能影响最大。为解决这些问题,设计智能导航平台的硬件控制终端,利用基于全球卫星导航系统(Global Navigation Satellite System,GNSS)秒脉冲(Pulse Per Second,PPS)的时间同步,实现多源传感器数据融合;设计用于同步定位与地图构建(Simultaneous Localization And Mapping,SLAM)前端ORB(Oriented FAST and Rotated BRIEF)特征提取加速器,加速图像处理过程,提高SLAM系统的实时性。实验结果表明,硬件平台不仅支持GNSS、惯性测量单元(Inertial Measurement Unit,IMU)、视觉和激光雷达的数据采集和融合,还能加速图像ORB特征点提取。在执行图像ORB特征提取任务时,与CPU和GPU平台上的实现相比,该加速器的帧率分别达到了它们的2.7倍和1.8倍,而功耗仅为它们的5.1%和2.9%。展开更多
基金supported by Science and Technology Standard Project of Guangdong Electric Power Design Institute(ER11301W,ER11811W).
文摘Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.
基金supported partly by the National Key R&D Program of China(2018YFA0702200)the Science and Technology Project of State Grid Shandong Electric Power Company(520604190002)。
文摘With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.
基金supported by the Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.22IRTSTHN016)the Hubei Natural Science Foundation(No.2021CFB156)the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)(No.JP21K17737).
文摘Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.
基金National Key Project of ScientificTechnical Supporting Programs Funded by Ministry of Science & Technology of China during the 11th Five-Year Plan Period (Grant No. 2006BCA01A07-2).
文摘Morlet wavelet transformation is used in this paper to analyze the multi time scale characteristics of pre cipitation data series from 1957 to 2005 in Guyuan region.The results showed that(1) the annual precipitation evo lution process had obvious multi time scale variation characteristics of 15 25 years,7 12 years and 3 6 years,and different time scales had different oscillation energy densities;(2) the periods at smaller time scales changed more frequently,which often nested in a biggish quasi periodic oscillations,so the concrete time domain should be ana lyzed if necessary;(3) the precipitation had three main periods(22 year,9 year and 4 year) and the 22 year period was especially outstanding,and the analysis of this main period reveals that the precipitation would be in a relative high water period until about 2012.
基金provided by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China under Grant Nos.51261120375 and 51421064
文摘To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.
基金supported by the Certificate of National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2016ZX05006007-004)the National Natural Science Foundation of China(Nos.42172145,42072130)。
文摘Coal is a solid combustible mineral,and coal-bearing strata have important hydrocarbon generation potential and contribute to more than 12%of the global hydrocarbon resources.However,the deposition and hydrocarbon evolution process of ancient coal-bearing strata is characterized by multiple geological times,leading to obvious distinctions in their hydrocarbon generation potential,geological processes,and production,which affect the evaluation and exploration of hydrocarbon resources derived from coaly source rocks worldwide.This study aimed to identify the differences on oil-generated parent macerals and the production of oil generated from different coaly source rocks and through different oil generation processes.Integrating with the analysis of previous tectonic burial history and hydrocarbon generation history,high-temperature and high-pressure thermal simulation experiments,organic geochemistry,and organic petrology were performed on the Carboniferous-Permian(C-P)coaly source rocks in the Huanghua Depression,Bohai Bay Basin.The oil-generated parent macerals of coal's secondary oil generation process(SOGP)were mainly hydrogen-rich collotelinite,collodetrinite,sporinite,and cutinite,while the oil-generated parent macerals of tertiary oil generation process(TOGP)were the remaining small amount of hydrogen-rich collotelinite,sporinite,and cutinite,as well as dispersed soluble organic matter and unexhausted residual hydrocarbons.Compared with coal,the oil-generated parent macerals of coaly shale SOGP were mostly sporinite and cutinite.And part of hydrogen-poor vitrinite,lacking hydrocarbon-rich macerals,and macerals of the TOGP,in addition to some remaining cutinite and a small amount of crude oil and bitumen from SOGP contributed to the oil yield.The results indicated that the changes in oil yield had a good junction between SOGP and TOGP,both coal and coaly shale had higher SOGP aborted oil yield than TOGP starting yield,and coaly shale TOGP peak oil yield was lower than SOGP peak oil yield.There were significant differences in saturated hydrocarbon and aromatic parameters in coal and coaly shale.Coal SOGP was characterized by a lower Ts/Tm and C31-homohopane22S/(22S+22R)and a higher Pr/n C17compared to coal TOGP,while the aromatic parameter methyl dibenzothiophene ratio(MDR)exhibited coaly shale TOGP was higher than coaly shale SOGP than coaly TOGP than coaly SOGP,and coal trimethylnaphthalene ratio(TNR)was lower than coaly shale TNR.Thus,we established oil generation processes and discriminative plates.In this way,we distinguished the differences between oil generation parent maceral,oil generation time,and oil production of coaly source rocks,and therefore,we provided important support for the evaluation,prediction,and exploration of oil resources from global ancient coaly source rocks.
基金supported by the State Grid Science and Technology Project (Title: Technology Research On Large Scale EMT Real-time simulation customized platform, FX71-17-001)
文摘As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.
文摘Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.
文摘The improvements of high-throughput experimental devices such as microarray and mass spectrometry have allowed an effective acquisition of biological comprehensive data which include genome, transcriptome, proteome, and metabolome (multi-layered omics data). In Systems Biology, we try to elucidate various dynamical characteristics of biological functions with applying the omics data to detailed mathematical model based on the central dogma. However, such mathematical models possess multi-time-scale properties which are often accompanied by time-scale differences seen among biological layers. The differences cause time stiff problem, and have a grave influence on numerical calculation stability. In the present conventional method, the time stiff problem remained because the calculation of all layers was implemented by adaptive time step sizes of the smallest time-scale layer to ensure stability and maintain calculation accuracy. In this paper, we designed and developed an effective numerical calculation method to improve the time stiff problem. This method consisted of ahead, backward, and cumulative algorithms. Both ahead and cumulative algorithms enhanced calculation efficiency of numerical calculations via adjustments of step sizes of each layer, and reduced the number of numerical calculations required for multi-time-scale models with the time stiff problem. Backward algorithm ensured calculation accuracy in the multi-time-scale models. In case studies which were focused on three layers system with 60 times difference in time-scale order in between layers, a proposed method had almost the same calculation accuracy compared with the conventional method in spite of a reduction of the total amount of the number of numerical calculations. Accordingly, the proposed method is useful in a numerical analysis of multi-time-scale models with time stiff problem.
文摘The distribution loads, output of distributed generations (DGs) and dynamic power price present obvious time-sequence property, the typical property is studied in this paper. The model of microgrid (including adjustable load, DGs, storage and dynamic power price) is studied. A multi-timescale collaborative optimization model is built towards microgrid;main measures in different timescale optimization are realized. An improved adaptive genetic algorithm is used to solve the optimization problem, which improved the efficiency and reliability. The proposed optimization model is simulated in IEEE 33 node system;the results show it’s effective.
基金support by National Natural Science Foundation of China,Grant agreement No:52107216.
文摘The increasing integration of renewable energy sources and power electronic devices has significantly increased the complexity of modern power systems,making modeling and simulation challenging due to multi-time scale dynamics and multi-physics coupling.To address these challenges,this paper proposes a multi-level simulation framework based on unified energy flow theory.The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports,ensuring compatibility with artificial intelligence algorithms.By integrating AI techniques,such as back propagation neural networks,the framework predicts variables with high computational complexity,improving accuracy and simulation efficiency.A multi-level simulation architecture leveraging Field Programmable Gate Arrays(FPGAs)enables faster-than-real-time system-level simulation and real-time component-level modeling with time resolution as small as 5 nanoseconds.A DC microgrid case study with photovoltaic generation,battery storage,and power electronic converters demonstrates the proposed method,achieving up to a 500×speedup over traditional Simulink models while maintaining high accuracy.The results confirm the framework’s ability to capture multiphysics interactions,optimize energy distribution,and ensure system stability under dynamic conditions,providing an efficient and scalable solution for advanced DC microgrid simulations.
基金This work was supported in part by the National Basic Research Program of China （973 Program） （Grant No. 2012CB215100）, and the Major Program of the National Natural Science Foundation of China （Grant No. 51190104）.
文摘Electric power infrastructure has recently undergone a comprehensive transformation from electromagnetics to semiconductors. Such a development is attributed to the rapid growth of power electronic converter applications in the load side to realize energy conservation and on the supply side for renewable generations and power transmissions using high voltage direct current transmission. This transformation has altered the fundamental mechanism of power system dynamics, which demands the establishment of a new theory for power system control and protection. This paper presents thoughts on a theoretical framework for the coming semiconducting power systems.
基金supported in part by the Science and Technology Project of Central Branch of SGCC(SGHZ0000DKJS 1900228)in part by the National Natural Science Foundation of China(51707136).
文摘Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control structure,which successively requires a correction between schedule plans within multi-time scale.In order to address this problem,this paper develops an information integration method integrating complicated relationships among fuel cost,total thermal power output,reserve capacity,owned reserves and expectations of load shedding and wind curtailment,into three types of time-related relationship curves・Furthermore,a multi-time scale tieline energy and reserves allocation model is proposed,which contains two levels in the control structure,two time scales in dispatch sequence and multiple areas integrated within wind farms as scheduling objects・The efficiency of the proposed method is tested in a 9-bus test system and IEEE 118-bus system.The results show that a cross-regional control center is able to approach the optimal scheduling results of the whole system with the integrated uploaded relationship curves.The proposed model not only relieves energy and reserve shortages in partial areas but also allocates them to more urgent need areas in a high effectivity manner in both day-ahead and intraday time scales.
文摘针对可再生能源高比例渗透下多区域综合能源互联系统(Multi-region integrated energy interconnection system,MRIEIS)所面临的消纳与经济性挑战,构建了一个包含电、氢、热、冷多能流的多时间尺度优化调度模型。该模型以系统日总运行成本最低为目标,建立动态多能流枢纽深度集成了电转氢(Power to hydrogen,P2H)、储氢罐、氢气管网以及燃气轮机(GT)掺氢等动态调度关键技术。通过日前、日内、实时三阶段滚动优化对系统进行精细化调度。算例分析基于一个包含居民、工业和混合型区域的典型场景,结果表明,该模型能够有效实现系统经济性与环保性的统一,总运行成本控制在56.48万元,同时系统总可再生能源利用率高达98.53%。氢能作为灵活的能量载体,其时空价值得到了充分发挥。掺氢策略有效刺激了氢能消耗,形成了“制-储-输-用”的闭环,为构建以新能源为主体的新型电力系统提供了可行的技术路径和调度策略参考。
文摘滚动轴承是机械设备中的常见关键部件,准确预测其剩余使用寿命对机械设备的安全稳定运行至关重要。针对目前轴承寿命预测存在的轴承退化特征不明显、模型泛化能力差以及数据长期依赖关系难以捕捉的问题,提出基于时频域信号优化器(Time-Frequency domain signal Ratio Optimizer,TFRO)的多重膨胀多核时间卷积网络(Multi inflated Multi kernel Time Convolutional Network,Mi-MkTCN)模型。TFRO优化器为了精准记忆重要信息,在每一个时间节点上,将过去信息和当前信息重组,其中过去信息中的重要的时频域特征经过了有比例的分配。Mi-MkTCN利用多重膨胀确保重要特征不丢失,再利用多核时间卷积网络实现对不同尺度特征的提取。最终的消融对比实验验证了改进方法的有效性,模型的平均绝对误差、均方误差及均方根误差指标分别为0.00145、0.05069和0.12045。实验结果表明,所提方法显著提升了轴承剩余使用寿命的预测精度,为轴承剩余使用寿命预测提供了高精度、高鲁棒性的解决方案。
文摘导航系统依赖传感器感知周围环境。当前,基于单一传感器的导航系统已难以满足各类复杂场景下的导航需求,导航系统正朝传感器多源化方向发展。在多源传感器数据融合过程中,图像数据的处理最消耗时间和资源,对系统性能影响最大。为解决这些问题,设计智能导航平台的硬件控制终端,利用基于全球卫星导航系统(Global Navigation Satellite System,GNSS)秒脉冲(Pulse Per Second,PPS)的时间同步,实现多源传感器数据融合;设计用于同步定位与地图构建(Simultaneous Localization And Mapping,SLAM)前端ORB(Oriented FAST and Rotated BRIEF)特征提取加速器,加速图像处理过程,提高SLAM系统的实时性。实验结果表明,硬件平台不仅支持GNSS、惯性测量单元(Inertial Measurement Unit,IMU)、视觉和激光雷达的数据采集和融合,还能加速图像ORB特征点提取。在执行图像ORB特征提取任务时,与CPU和GPU平台上的实现相比,该加速器的帧率分别达到了它们的2.7倍和1.8倍,而功耗仅为它们的5.1%和2.9%。
