Throughout the humid tropics of Asia,smallholder dairy(SHD)farmers have developed their production systems largely based on the“traditional way of doing things”.Tradition is a generic word used in this case to mean ...Throughout the humid tropics of Asia,smallholder dairy(SHD)farmers have developed their production systems largely based on the“traditional way of doing things”.Tradition is a generic word used in this case to mean basing farm management decisions and practices on how their father,or friends or even next door neighbours do things.The low levels of milk production and herd fertility,the high incidences of calf mortalities and poor animal health(such as lameness and mastitis)and the inferior quality of much of the milk sourced from these farms are clear indications that many of these traditional farm management practices are in urgent need of re-evaluation.This need not necessarily be the norm and this paper provides two good examples of how innovation can pay off in the humid tropics of Bangladesh.They clearly demonstrated that improving herd management,particularly feeding management,can dramatically increase cow performance with higher milk yields and herd fertility.展开更多
Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known pro...Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known problem.In practice,the operation and usability of DSE depend on not only the estimation accuracy but also the ability to predict error variance.This paper investigates the application of error covariance in DSE by using the augmented complex Kalman filter(ACKF).The Kalman filter method inherently provides state error covariance prediction.It can be utilized to accurately infer the error covariance of other parameters and provide a method to determine optimal measurement locations based on the sensitivity of error covariance to measurement noise covariance.This paper also proposes a generalized formulation of ACKF to allow scalar measurements to be incorporated into the complex-valued estimator.The proposed method is simulated by using modified IEEE 34-bus and IEEE 123-bus test feeders,and randomly generates the load data of complex-valued Wiener process.The ACKF method is compared with an equivalent formulation using the traditional weighted least squares(WLS)method and iterated extended Kalman filter(IEKF)method,which shows improved accuracy and computation performance.展开更多
文摘Throughout the humid tropics of Asia,smallholder dairy(SHD)farmers have developed their production systems largely based on the“traditional way of doing things”.Tradition is a generic word used in this case to mean basing farm management decisions and practices on how their father,or friends or even next door neighbours do things.The low levels of milk production and herd fertility,the high incidences of calf mortalities and poor animal health(such as lameness and mastitis)and the inferior quality of much of the milk sourced from these farms are clear indications that many of these traditional farm management practices are in urgent need of re-evaluation.This need not necessarily be the norm and this paper provides two good examples of how innovation can pay off in the humid tropics of Bangladesh.They clearly demonstrated that improving herd management,particularly feeding management,can dramatically increase cow performance with higher milk yields and herd fertility.
文摘Distribution state estimation(DSE)is an essential part of an active distribution network with high level of distributed energy resources.The challenges of accurate DSE with limited measurement data is a well-known problem.In practice,the operation and usability of DSE depend on not only the estimation accuracy but also the ability to predict error variance.This paper investigates the application of error covariance in DSE by using the augmented complex Kalman filter(ACKF).The Kalman filter method inherently provides state error covariance prediction.It can be utilized to accurately infer the error covariance of other parameters and provide a method to determine optimal measurement locations based on the sensitivity of error covariance to measurement noise covariance.This paper also proposes a generalized formulation of ACKF to allow scalar measurements to be incorporated into the complex-valued estimator.The proposed method is simulated by using modified IEEE 34-bus and IEEE 123-bus test feeders,and randomly generates the load data of complex-valued Wiener process.The ACKF method is compared with an equivalent formulation using the traditional weighted least squares(WLS)method and iterated extended Kalman filter(IEKF)method,which shows improved accuracy and computation performance.
