Traditional thermal power units are continuously replaced by renewable energies,of which fluctuations and intermittence impose pressure on the frequency stability of the power system.Electrolytic aluminum load(EAL)acc...Traditional thermal power units are continuously replaced by renewable energies,of which fluctuations and intermittence impose pressure on the frequency stability of the power system.Electrolytic aluminum load(EAL)accounts for large amount of the local electric loads in some areas.The participation of EAL in local frequency control has huge application prospects.However,the controller design of EAL is difficult due to the measurement noise of the system frequency and the nonlinear dynamics of the EAL’s electric power consumption.Focusing on this problem,this paper proposes a control strategy for EAL to participate in the frequency control.For the controller design of the EAL system,the system frequency response model is established and the EAL transfer function model is developed based on the equivalent circuit of EAL.For the problem of load-side frequency measurement error,the frequency estimation method based on Kalman-filtering is designed.To improve the performance of EAL in the frequency control,a fuzzy EAL controller is designed.The testing examples show that the designed Kalman-filter has good performance in de-noising the measured frequency,and the designed fuzzy controller has better performance in stabilizing system frequency than traditional methods.展开更多
An improved retrieval method, which uses the solution with a Gaussian constraint as the initial state variables for the Kalman Filtering （KF） method, was developed to retrieve the wet refractivity profiles from slan...An improved retrieval method, which uses the solution with a Gaussian constraint as the initial state variables for the Kalman Filtering （KF） method, was developed to retrieve the wet refractivity profiles from slant wet delays （SWD） extracted by the double-differenced （DD） GPS method. The accuracy of the GPS-derived SWDs is also tested in this study against the measurements of a water vapor radiometer （WVR） and a weather model. It is concluded that the GPS-derived SWDs have similar accuracy to those measured with WVR and are much higher in quality than those derived from the weather model used. The developed method is used to retrieve the 3D wet refractivity distribution in the Hong Kong region. The retrieved profiles agree well with the radiosonde observations, with a difference of about 4 mm km^- 1 in the low levels. The accurate profiles obtained with this method are applicable in a number of meteorological applications.展开更多
Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigat...Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigated by researchers, of which Klaman filtering is one of the most important. Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown states of a dynamic system, which has found widespread application in many areas. The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods, then a new method of state fusion is proposed. Finally the simulation results demonstrate the effectiveness of the introduced method.展开更多
基金funded by Science and Technology Project of State Grid Corporation of China:Research on the Construction and Evaluation Technology of the Data-Driven-based Adjustable Resource Pool of Typical Industrial Enterprises,Grant No.1400-202016386A-0-0-00.
文摘Traditional thermal power units are continuously replaced by renewable energies,of which fluctuations and intermittence impose pressure on the frequency stability of the power system.Electrolytic aluminum load(EAL)accounts for large amount of the local electric loads in some areas.The participation of EAL in local frequency control has huge application prospects.However,the controller design of EAL is difficult due to the measurement noise of the system frequency and the nonlinear dynamics of the EAL’s electric power consumption.Focusing on this problem,this paper proposes a control strategy for EAL to participate in the frequency control.For the controller design of the EAL system,the system frequency response model is established and the EAL transfer function model is developed based on the equivalent circuit of EAL.For the problem of load-side frequency measurement error,the frequency estimation method based on Kalman-filtering is designed.To improve the performance of EAL in the frequency control,a fuzzy EAL controller is designed.The testing examples show that the designed Kalman-filter has good performance in de-noising the measured frequency,and the designed fuzzy controller has better performance in stabilizing system frequency than traditional methods.
文摘An improved retrieval method, which uses the solution with a Gaussian constraint as the initial state variables for the Kalman Filtering （KF） method, was developed to retrieve the wet refractivity profiles from slant wet delays （SWD） extracted by the double-differenced （DD） GPS method. The accuracy of the GPS-derived SWDs is also tested in this study against the measurements of a water vapor radiometer （WVR） and a weather model. It is concluded that the GPS-derived SWDs have similar accuracy to those measured with WVR and are much higher in quality than those derived from the weather model used. The developed method is used to retrieve the 3D wet refractivity distribution in the Hong Kong region. The retrieved profiles agree well with the radiosonde observations, with a difference of about 4 mm km^- 1 in the low levels. The accurate profiles obtained with this method are applicable in a number of meteorological applications.
文摘Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigated by researchers, of which Klaman filtering is one of the most important. Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown states of a dynamic system, which has found widespread application in many areas. The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods, then a new method of state fusion is proposed. Finally the simulation results demonstrate the effectiveness of the introduced method.
