This paper studies a distributed state estimation problem for a network of linear dynamic systems (called nodes), which evolve autonomously, but their measurements are coupled through neighborhood interactions. Power networks are typical networked systems obeying such features, with other examples including traffic networks, sensor networks and many multi-agent systems. We develop a new distributed state estimation approach, for each node to update its local state. The core of this distributed approach is a distributed maximum a posteriori (MAP) estimation technique, which delivers a globally optimal estimate under certain assumptions. We apply the distributed approach to an IEEE 118-bus system, and compare it with a centralized approach, w...
© 2017 In contrast to the traditional centralised power system state estimation methods, this paper ...
This dissertation is aimed at developing optimal and distributed state estimation algorithms for a t...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
This paper studies a distributed state estimation problem for a network of linear dynamic systems (c...
This paper studies a state estimation problem for a networked dynamic system characterized by a comm...
This paper studies a dynamic state estimation problem for power systems, which can be seen as the qu...
This work presents a distributed method for control centers to monitor the operating condition of a ...
This work presents a distributed method for control centers to monitor the operating condition of a ...
In this study, we present methods of optimization-based power system state estimation over sensor ne...
This work presents a distributed method for control centers to monitor the operating condition of a ...
© 2017 IEEE. In contrast to the traditional centralized power system state estimation methods, this ...
In this thesis, the topics of state estimation for large-scale systems (LSSs) with distributed obser...
In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is pro...
Large number of physical systems such as electric vehicles and energy storage elements are connected...
State estimation of linear time-invariant (LTI) systems by using a network of distributed observers ...
© 2017 In contrast to the traditional centralised power system state estimation methods, this paper ...
This dissertation is aimed at developing optimal and distributed state estimation algorithms for a t...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
This paper studies a distributed state estimation problem for a network of linear dynamic systems (c...
This paper studies a state estimation problem for a networked dynamic system characterized by a comm...
This paper studies a dynamic state estimation problem for power systems, which can be seen as the qu...
This work presents a distributed method for control centers to monitor the operating condition of a ...
This work presents a distributed method for control centers to monitor the operating condition of a ...
In this study, we present methods of optimization-based power system state estimation over sensor ne...
This work presents a distributed method for control centers to monitor the operating condition of a ...
© 2017 IEEE. In contrast to the traditional centralized power system state estimation methods, this ...
In this thesis, the topics of state estimation for large-scale systems (LSSs) with distributed obser...
In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is pro...
Large number of physical systems such as electric vehicles and energy storage elements are connected...
State estimation of linear time-invariant (LTI) systems by using a network of distributed observers ...
© 2017 In contrast to the traditional centralised power system state estimation methods, this paper ...
This dissertation is aimed at developing optimal and distributed state estimation algorithms for a t...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...