In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of faul...In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.展开更多
The energy sector in Poland is the source of 81% of greenhouse gas（GHG） emissions. Poland,among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector activ...The energy sector in Poland is the source of 81% of greenhouse gas（GHG） emissions. Poland,among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship（0.97） with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal（0.66）, peat and fuel wood（0.34）, solid waste fuels, as well as other sources（- 0.64） as the most important variables. The adjusted coefficient is suitable and equals R2= 0.90. For N2 O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2 O emission is the peat and wood fuel consumption.展开更多
Based on data of PM2.5 hourly concentration and HYSPLIT model backward trajectory in coastal cities of Fujian Province during January 25 -26, 2014, a typical regional pollution process affecting Fujian from the north ...Based on data of PM2.5 hourly concentration and HYSPLIT model backward trajectory in coastal cities of Fujian Province during January 25 -26, 2014, a typical regional pollution process affecting Fujian from the north to the south and the east to the west on January 26 was investiga- ted. Taking Fuzhou as an example, based on weather situation on the ground and at high altitudes as well as corresponding meteorological data such as wind direction, wind velocity, and visibility, the changes of meteorological elements before, during and after the pollution were compared. Based on the V-3θ atmospheric vertical structure diagrams, the weather reasons for the generation, maintaining and dissipation of the pollution were discussed. The results indicated that the regional pollution was transported from the northeast to the southwest. The northeasterly air flow in front of the cold ridge strengthened and moved toward the east, so that the pollutant from the north affected Fujian form the north to the south and from the east to the west. As a result, there was a dramatic increase of pollutant concentration, rapid drop of visibility, and deterioration of air quality in the affected areas. The heavy pollution process featured high-speed transport and short-time generation. The air quality changed from good state to heavy pollution in just 3 -4 hours. The maximum of IAQIpM2.5 reached 280. The whole pollution process lasted for 14 hours. Solar radiation had been deeply affected by aerosol clouds, so that atmospheric stratification was extremely stable. Along with the eastward movement of cold high pressure into the sea, the dominant wind direction near the ground changed from the northeast to the east, so that the source of the pollutant was cut off , and air quality quickly turned well. The changes of atmospheric vertical structure indicated that the high inversion layer and clouds near 700 hPa kept lower air clean and blocked upper pollution transport. The later sudden increase of wind speed and strengthening of atmospheric mechanical turbu- lent destroyed inversion layer, so that the upper pollutants invaded air near the ground rapidly. During the period of high pollution, the isothermal layer (aerosol clouds) leaded to decrease of wind speed, and the atmosphere became more stable. The pollution ended until the wind field changed.展开更多
Footprint characteristics for passive scalar concentration in the convective boundary layer （CBL） are investigated. A backward Lagrangian stochastic （LS） dispersion model and a large eddy simulation （LES） model ...Footprint characteristics for passive scalar concentration in the convective boundary layer （CBL） are investigated. A backward Lagrangian stochastic （LS） dispersion model and a large eddy simulation （LES） model are used in the investigation. Typical characteristics of the CBL and their responses to the surface heterogeneity are resolved from the LES. Then the turbulence fields are used to drive the backward LS dispersion. To remedy the spoiled description of the turbulence near the surface, MoninObukhov similarity is applied to the lowest LES level and the surface for the modeling of the backward LS dispersion. Simulation results show that the footprint within approximately 1 km upwind predominates in the total contribution. But influence from farther distances also exists and is even slightly greater than that from closer locations. Surface heterogeneity may change the footprint pattern to a certain degree. A comparison to three analytical models provides a validation of the footprint simulations, which shows the possible influence of along-wind turbulence and the large eddies in the CBL, as well as the surface heterogeneity.展开更多
基金the National Natural Science Foundation of China (No. 50677062)the New Century Excellent Talents in Uni-versity of China (No. NCET-07-0745)the Natural Science Foundation of Zhejiang Province, China (No. R107062)
文摘In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
文摘The energy sector in Poland is the source of 81% of greenhouse gas（GHG） emissions. Poland,among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship（0.97） with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal（0.66）, peat and fuel wood（0.34）, solid waste fuels, as well as other sources（- 0.64） as the most important variables. The adjusted coefficient is suitable and equals R2= 0.90. For N2 O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2 O emission is the peat and wood fuel consumption.
文摘Based on data of PM2.5 hourly concentration and HYSPLIT model backward trajectory in coastal cities of Fujian Province during January 25 -26, 2014, a typical regional pollution process affecting Fujian from the north to the south and the east to the west on January 26 was investiga- ted. Taking Fuzhou as an example, based on weather situation on the ground and at high altitudes as well as corresponding meteorological data such as wind direction, wind velocity, and visibility, the changes of meteorological elements before, during and after the pollution were compared. Based on the V-3θ atmospheric vertical structure diagrams, the weather reasons for the generation, maintaining and dissipation of the pollution were discussed. The results indicated that the regional pollution was transported from the northeast to the southwest. The northeasterly air flow in front of the cold ridge strengthened and moved toward the east, so that the pollutant from the north affected Fujian form the north to the south and from the east to the west. As a result, there was a dramatic increase of pollutant concentration, rapid drop of visibility, and deterioration of air quality in the affected areas. The heavy pollution process featured high-speed transport and short-time generation. The air quality changed from good state to heavy pollution in just 3 -4 hours. The maximum of IAQIpM2.5 reached 280. The whole pollution process lasted for 14 hours. Solar radiation had been deeply affected by aerosol clouds, so that atmospheric stratification was extremely stable. Along with the eastward movement of cold high pressure into the sea, the dominant wind direction near the ground changed from the northeast to the east, so that the source of the pollutant was cut off , and air quality quickly turned well. The changes of atmospheric vertical structure indicated that the high inversion layer and clouds near 700 hPa kept lower air clean and blocked upper pollution transport. The later sudden increase of wind speed and strengthening of atmospheric mechanical turbu- lent destroyed inversion layer, so that the upper pollutants invaded air near the ground rapidly. During the period of high pollution, the isothermal layer (aerosol clouds) leaded to decrease of wind speed, and the atmosphere became more stable. The pollution ended until the wind field changed.
基金the National Natural Science Foundation of China under Grant Nos.40275005 , 40233030 the National Basic Research and Development Program under Grant 2002CB410802.
文摘Footprint characteristics for passive scalar concentration in the convective boundary layer （CBL） are investigated. A backward Lagrangian stochastic （LS） dispersion model and a large eddy simulation （LES） model are used in the investigation. Typical characteristics of the CBL and their responses to the surface heterogeneity are resolved from the LES. Then the turbulence fields are used to drive the backward LS dispersion. To remedy the spoiled description of the turbulence near the surface, MoninObukhov similarity is applied to the lowest LES level and the surface for the modeling of the backward LS dispersion. Simulation results show that the footprint within approximately 1 km upwind predominates in the total contribution. But influence from farther distances also exists and is even slightly greater than that from closer locations. Surface heterogeneity may change the footprint pattern to a certain degree. A comparison to three analytical models provides a validation of the footprint simulations, which shows the possible influence of along-wind turbulence and the large eddies in the CBL, as well as the surface heterogeneity.
