The paper is organized as follows: In Section 2, we review the secure state estimation for linear dynamical systems and in Section 3, we introduce the microgrid model adopted in this work. In
The state estimation is a classic problem in power systems. Its origins come back to the 70s with the formalization of the power-flow problem and the introduction of the digital computer for
The real time state estimation is implemented using PMU in Real Time Digital Simulator (RTDS) environment. The proposed method is applied on a modified 14 bus test microgrid. The results
By utilizing phasor measurement units (PMUs), a combined robust cen-tralized dynamic algebraic approach is proposed in this paper for estimating algebraic states (voltage phasors) as well as
Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This
The real time state estimation is implemented using PMU in Real Time Digital Simulator (RTDS) environment. The proposed method is applied on a modified 14 bus test microgrid. The results
Case studies demonstrate the efficiency of the proposed method to be applied for power systems operation in real time. In [ 21 ], a novel microgrid dynamic state estimation is developed for monitoring the system states along the time based on singular perturbation theory.
In [ 21 ], a novel microgrid dynamic state estimation is developed for monitoring the system states along the time based on singular perturbation theory. In this paper, a novel technique is proposed for microgrids state estimation using micro-PMUs and smart meters.
This paper presented a novel methodology for microgrids state estimation based on a Kalman filter model. Voltage magnitudes, angles and system frequency are considered as state variables to be estimated along the time tracking daily load variations.
A distributed state estimation method is presented in [ 20] in which an optimization model is formulated to determine the system states being the Lagrangian relaxation method used to find the optimal solution. The method is useful for AC/DC hybrid microgrids monitoring.
Grid-connected and islanded operation modes are considered for the computational simulations, proving that the methodology is capable of determining system states and frequency with reduced estimation errors.
Although microgrids can operate connected to the main grid, they can also operate in islanded modes in such a way that the loads are still supplied by distributed generators dispersely allocated along the system. When the microgrid is connected to the main grid, it dictates the fundamental frequency value.
