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This paper presents an approach for dynamic state estimation of aggregated generators by introducing a new correction factor for equivalent inter-area power flows. The spread of generators from the center of inertia of each area is summarized by the correction term α on the equivalent power flow between the areas and is applied to the identification and estimation process. A nonlinear time varying...
The Kalman filter is a set of mathematical equations which are used to estimate the state of a system by minimizes the mean of the squared error. In this paper Kalman filtering is used for the estimation of states of IEEE 14 bus power system network. Here we considered dynamic states i.e. rotor angle in radians and speed in rad/sec of all the generators present in the system. We mainly focus on the...
Phase measurement units make it possible to measure and transmit voltage vectors with high transmission rates. The applications for monitoring and control purposes are in need of development. The paper presents a dynamic observer which is able to estimate magnitude and phase of grid node voltages by appling of a dynamic network model. Furthermore, the rotor speed of synchronous generators can be estimated...
Load models are commonly approximated by fixed impedance type loads when formulating dynamic simulations. This is an acceptable approximation when using dynamic simulation for a specific initial operating condition and the study runs for a brief period typically to check system stability. When implementing an on-line dynamic estimator such assumptions may not be viable due to the load dynamics which...
In this paper, an algorithm based on Least-Square Method (LSM), Newton-Raphson Method (NRM) and Modal Assurance Criterion (MAC) was developed to update Near-Real-Time (NRT) inertia constants in large power systems using Wide Area Measurements (WAM). This enables the update of power system dynamic models for system dynamic stability analysis. An inaccurate baseline power system dynamic model is used...
The complexity of power systems continue to increase as load demands grow and new energy technologies emerge. Efficient methodologies and instrumentation are needed for real-time monitoring and control of power systems. Accurately tracking the state variables (rotor angle and speed) is necessary for monitoring system stability conditions and assessing the risks of large-scale system collapse. Previous...
This paper presents a predictive energy based Out of Step Protection scheme. It is based on real time dynamic monitoring of the system achieved through the implementation of a distributed, substation based dynamic state estimator. The estimator utilizes only local measurements and requires PMU synchronized measurements; additional measurements from non-GPS synchronized relays are also utilized and...
Applying Kalman filtering techniques to dynamic state estimation is a developing research area in modern power systems. Compared to traditional steady state estimators, the Kalman filter is able to track dynamic state variables both efficiently and accurately. However, in large-scale and wide-area interconnected power systems, the combination of computational complexity—primarily due to the very large...
GPS synchronized measurements are becoming common and there is tremendous activity to develop applications and utilize these measurements. While, presently the applications lag the hardware developments, there is a great activity towards development of a variety of applications and utilization of GPS synchronized data. The paper provides a brief overview of GPS synchronized measurements and past projects...
This paper provides a methodology to extract the dynamic real time model of an electric power system using phasor measurement unit (PMU) data (GPS-synchronized) and other SCADA data that are available in substations. In addition to typical voltage and current measurements, PMU data include frequency and rate of change of frequency. Such data are available in raw form, as time-stamped instantaneous...
The state estimation tools which are currently deployed in power system control rooms are based on a quasi-steady-state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper presents an overview of the Kalman filtering process and then focuses on the implementation...
Wide area measurement system (WAMS) has been widely used in power system dynamic monitoring and control, such as low frequency identification and control, stability analysis and control, etc. However, as a measurement tool, WAMS has the measurement error and bad data unavoidably. If the raw data is applied directly, the unpredictable consequence will be resulted in. Aiming at this problem, a novel...
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