Photovoltaic(PV)power forecasting is essential for secure operation of a power system.Effective prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smar...Photovoltaic(PV)power forecasting is essential for secure operation of a power system.Effective prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smart grids,and ultimately support construction of smart energy cities.However,different from centralized PV power forecasts,three critical challenges are encountered in distributed PV power forecasting:1)lack of on-site meteorological observation,2)leveraging extraneous data to enhance forecasting performance,3)spatial-temporal modelling methods of meteorological information around the distributed PV stations.To address these issues,we propose a Graph Spatial-Temporal Attention Neural Network(GSTANN)to predict the very short-term power of distributed PV.First,we use satellite remote sensing data covering a specific geographical area to supplement meteorological information for all PV stations.Then,we apply the graph convolution block to model the non-Euclidean local and global spatial dependence and design an attention mechanism to simultaneously derive temporal and spatial correlations.Subsequently,we propose a data fusion module to solve the time misalignment between satellite remote sensing data and surrounding measured on-site data and design a power approximation block to map the conversion from solar irradiance to PV power.Experiments conducted with real-world case study datasets demonstrate that the prediction performance of GSTANN outperforms five state-of-the-art baselines.展开更多
Focusing on its main requirements and challenges and by analyzing the characteristics of different space platforms,an overall architecture for space information networks is proposed based on national strategic plannin...Focusing on its main requirements and challenges and by analyzing the characteristics of different space platforms,an overall architecture for space information networks is proposed based on national strategic planning and the present development status of associated technologies.Furthermore,the core scientific problems that need to be solved are expounded.In addition,the primary considerations and a preliminary integrated demonstration environment for verification of key technologies are presented.展开更多
Formation flying orbit design is one of the key technologies for system design and performance analysis of the distributed SAR satellites. The approximately analytic solution of the passive stable formation flying orb...Formation flying orbit design is one of the key technologies for system design and performance analysis of the distributed SAR satellites. The approximately analytic solution of the passive stable formation flying orbit elements is explored based on the expansion form of Kepler's equation. A new method of orbital parameters design for three-dimensional formation flying SAR satellites is presented, and the precision of the orbital elements is analyzed. Formation flying orbit elements are calculated for the L-Band distributed SAR satellites using the formulas deduced in this paper. The accuracy of the orbital elements is validated by the computer simulation results presented in this paper.展开更多
In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite li...In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite links handover number. To optimize the route based on the simplified topology, we considered not only the transmission delay but also the queuing delay and the processing delay, which were analyzed using Markov chain and determined using a novel methodology. The DRBST algorithm was simulated in a LEO satellite networks model built using OPNET. The simulation results demonstrate that the low complexity DRBST algorithm can guarantee end-to-end delay bound. Moreover, the muting protocol cost is much less than traditional algorithms.展开更多
基金supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA27000000)。
文摘Photovoltaic(PV)power forecasting is essential for secure operation of a power system.Effective prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smart grids,and ultimately support construction of smart energy cities.However,different from centralized PV power forecasts,three critical challenges are encountered in distributed PV power forecasting:1)lack of on-site meteorological observation,2)leveraging extraneous data to enhance forecasting performance,3)spatial-temporal modelling methods of meteorological information around the distributed PV stations.To address these issues,we propose a Graph Spatial-Temporal Attention Neural Network(GSTANN)to predict the very short-term power of distributed PV.First,we use satellite remote sensing data covering a specific geographical area to supplement meteorological information for all PV stations.Then,we apply the graph convolution block to model the non-Euclidean local and global spatial dependence and design an attention mechanism to simultaneously derive temporal and spatial correlations.Subsequently,we propose a data fusion module to solve the time misalignment between satellite remote sensing data and surrounding measured on-site data and design a power approximation block to map the conversion from solar irradiance to PV power.Experiments conducted with real-world case study datasets demonstrate that the prediction performance of GSTANN outperforms five state-of-the-art baselines.
基金supported by the National Natural Science Foundation of China(Nos.61231011,61671478)。
文摘Focusing on its main requirements and challenges and by analyzing the characteristics of different space platforms,an overall architecture for space information networks is proposed based on national strategic planning and the present development status of associated technologies.Furthermore,the core scientific problems that need to be solved are expounded.In addition,the primary considerations and a preliminary integrated demonstration environment for verification of key technologies are presented.
文摘Formation flying orbit design is one of the key technologies for system design and performance analysis of the distributed SAR satellites. The approximately analytic solution of the passive stable formation flying orbit elements is explored based on the expansion form of Kepler's equation. A new method of orbital parameters design for three-dimensional formation flying SAR satellites is presented, and the precision of the orbital elements is analyzed. Formation flying orbit elements are calculated for the L-Band distributed SAR satellites using the formulas deduced in this paper. The accuracy of the orbital elements is validated by the computer simulation results presented in this paper.
基金Supported by the National Science Foundation of China （No. 60873219）.
文摘In this paper, a distributed muting strategy based on simplified topology （DRBST） was proposed for LEO satellite networks. The topology of LEO satellite networks was simplified aiming at minimizing intersatellite links handover number. To optimize the route based on the simplified topology, we considered not only the transmission delay but also the queuing delay and the processing delay, which were analyzed using Markov chain and determined using a novel methodology. The DRBST algorithm was simulated in a LEO satellite networks model built using OPNET. The simulation results demonstrate that the low complexity DRBST algorithm can guarantee end-to-end delay bound. Moreover, the muting protocol cost is much less than traditional algorithms.
