This paper applied an integrated method combining grey relation analysis, wavelet analysis and statistical analysis to study climate change and its effects on runoff of the Kaidu River at multi-time scales. Major find...This paper applied an integrated method combining grey relation analysis, wavelet analysis and statistical analysis to study climate change and its effects on runoff of the Kaidu River at multi-time scales. Major findings are as follows: 1) Climatic factors were ranked in the order of importance to annual runoff as average annual temperature, average temperature in autumn, average temperature in winter, annual precipitation, precipitation in flood season, average temperature in summer, and average temperature in spring. The average annual temperature and annual precipi- tation were selected as the two representative factors that impact the annual runoff. 2) From the 32-year time scale, the annual runoff and the average annual temperature presented a significantly rising trend, whereas the annual precipita- tion showed little increase over the period of 1957-2002. By changing the time scale from 32-year to 4-year, we ob- served nonlinear trends with increasingly obvious oscillations for annual runoff, average annual temperature, and annual precipitation. 3) The changes of the runoff and the regional climate are closely related, indicating that the runoff change is the result of the regional climate changes. With time scales ranging from 32-year, 16-year, 8-year and to 4-year, there are highly significant linear correlations between the annual runoff and the average annual temperature and the annual precipitation.展开更多
The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi...The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.展开更多
基金Under the auspices of Second-stage Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX2-XB2-03)the major direction of Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX2-YW- 127)Shanghai Academic Discipline Project (Human Geography) (No. B410)
文摘This paper applied an integrated method combining grey relation analysis, wavelet analysis and statistical analysis to study climate change and its effects on runoff of the Kaidu River at multi-time scales. Major findings are as follows: 1) Climatic factors were ranked in the order of importance to annual runoff as average annual temperature, average temperature in autumn, average temperature in winter, annual precipitation, precipitation in flood season, average temperature in summer, and average temperature in spring. The average annual temperature and annual precipi- tation were selected as the two representative factors that impact the annual runoff. 2) From the 32-year time scale, the annual runoff and the average annual temperature presented a significantly rising trend, whereas the annual precipita- tion showed little increase over the period of 1957-2002. By changing the time scale from 32-year to 4-year, we ob- served nonlinear trends with increasingly obvious oscillations for annual runoff, average annual temperature, and annual precipitation. 3) The changes of the runoff and the regional climate are closely related, indicating that the runoff change is the result of the regional climate changes. With time scales ranging from 32-year, 16-year, 8-year and to 4-year, there are highly significant linear correlations between the annual runoff and the average annual temperature and the annual precipitation.
基金Supported by the National Natural Science Foundation of China(60974119)
文摘The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.
