Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispen...Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can repre展开更多
The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such ...The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such as the failure of the equipment,hostile weather conditions,etc.These faults if not detected in the real-time may lead to cascading failures resulting in a blackout.These blackouts have catastrophic consequences which result in a huge loss of resources.For example,a blackout in 2004 caused an economic loss of 10 billion U.S dollars as per the report of the Electricity Consumers Resource Council.Subsequent investigation of the blackout revealed that the catastrophe could have been prevented if there was an early warning system.Similar other blackouts across the globe forced the power system engineers to devise an effective solution for real-time monitoring and control of the power system.The consequence of these efforts is the wide area measurement system(WAMS).The WAMS consists of several sensors known as the phasor measurement units(PMUs)that collect the real information pertaining to the health of the power grid.This information in the form time synchronized voltage and current phasors is communicated to the central control center or the phasor data concentrator(PDC)where the data is analyzed for detection of power system anomalies.The communication of the synchrophasor data from each PMU to the PDC constitutes the synchrophasor communication system(SPCS).Thus,the SPCS can be considered as the edifice of the WAMS and its reliable operation is essential for the effective monitoring and control of the power system.This paper presents a comprehensive review of the various synchrophasor communication technologies,communication standards and applications.It also identifies the existing knowledge gaps and the scope for future research work.展开更多
Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey corr...Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey correlation analysis. The results show that: 1) the grain yield per unit area has been taking on an increasing trend in the recent 20 years. It increased from 2519.80kg/ha in 1980 to 4216.11kg/ha in 2003, with an increasing rate of 67.32%; 2) the variation of grain yield per unit area is considerably prominent and its range is also very great, with the maximal increase rate of 42.59% and maximal decrease rate of 21.13%, respectively, which are far above the whole Chinese average level; 3) the variation of main crops' yield per unit area is remarkable, which takes on the character that the yield of corn is much higher than that of soybean and rice; and 4) the grey correlation analysis shows that the most important factors impacting the variation of grain yield per unit area are the total power of agricultural machinery, the consumption of chemical fertilizer and effective irrigated area. However, the influence of natural disaster and income level should not be ignored. Effective ways to improve grain yield per unit area are to construct farmland improvement groundwork, reclaim the middle- and low-yield farmland, etc.展开更多
基金Foundation： National Natural Science Foundation of China, No.41171299, No.41171320, No.41401237
文摘Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their dif- ferences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area （SSCA）. SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km^2 to 35.1 km^2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force （Td） and slope of slope （SOS）, were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force （Td） and SOS and a loga- rithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can repre
文摘The present-day power system is a complex network that caters to the demands of several applications with diverse energy requirements.Such a complex network is susceptible to faults caused due to several reasons such as the failure of the equipment,hostile weather conditions,etc.These faults if not detected in the real-time may lead to cascading failures resulting in a blackout.These blackouts have catastrophic consequences which result in a huge loss of resources.For example,a blackout in 2004 caused an economic loss of 10 billion U.S dollars as per the report of the Electricity Consumers Resource Council.Subsequent investigation of the blackout revealed that the catastrophe could have been prevented if there was an early warning system.Similar other blackouts across the globe forced the power system engineers to devise an effective solution for real-time monitoring and control of the power system.The consequence of these efforts is the wide area measurement system(WAMS).The WAMS consists of several sensors known as the phasor measurement units(PMUs)that collect the real information pertaining to the health of the power grid.This information in the form time synchronized voltage and current phasors is communicated to the central control center or the phasor data concentrator(PDC)where the data is analyzed for detection of power system anomalies.The communication of the synchrophasor data from each PMU to the PDC constitutes the synchrophasor communication system(SPCS).Thus,the SPCS can be considered as the edifice of the WAMS and its reliable operation is essential for the effective monitoring and control of the power system.This paper presents a comprehensive review of the various synchrophasor communication technologies,communication standards and applications.It also identifies the existing knowledge gaps and the scope for future research work.
基金Under the auspices of the National Natural Science Foundation of China (No. 40601027)
文摘Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey correlation analysis. The results show that: 1) the grain yield per unit area has been taking on an increasing trend in the recent 20 years. It increased from 2519.80kg/ha in 1980 to 4216.11kg/ha in 2003, with an increasing rate of 67.32%; 2) the variation of grain yield per unit area is considerably prominent and its range is also very great, with the maximal increase rate of 42.59% and maximal decrease rate of 21.13%, respectively, which are far above the whole Chinese average level; 3) the variation of main crops' yield per unit area is remarkable, which takes on the character that the yield of corn is much higher than that of soybean and rice; and 4) the grey correlation analysis shows that the most important factors impacting the variation of grain yield per unit area are the total power of agricultural machinery, the consumption of chemical fertilizer and effective irrigated area. However, the influence of natural disaster and income level should not be ignored. Effective ways to improve grain yield per unit area are to construct farmland improvement groundwork, reclaim the middle- and low-yield farmland, etc.
