Abhinav Kumar Singh

Decentralized Dynamic State Estimation in Power Systems Using Unscented Transformation

This paper proposes a decentralized algorithm for real-time estimation of the dynamic states of a power system. The scheme employs phasor measurement units (PMUs) for the measurement of local signals at each generation unit, and subsequent state estimation using unscented Kalman filtering (UKF). The novelty of the scheme is that the state estimation at one generation unit is independent from the estimation at other units, and therefore the transmission of remote signals to a central estimator is not required. This in turn reduces the complexity of each distributed estimator, and makes the estimation process highly efficient, accurate and easily implementable. The applicability of the proposed algorithm has been thoroughly demonstrated on a representative model.

Stability Analysis of Networked Control in Smart Grids

A suitable networked control scheme and its stability analysis framework have been developed for controlling inherent electromechanical oscillatory dynamics observed in power systems. It is assumed that the feedback signals are obtained at locations away from the controller/actuator and transmitted over a communication network with the help of phasor measurement units (PMUs). Within the generic framework of networked control system (NCS), the evolution of power system dynamics and associated control actions through a communication network have been modeled as a hybrid system. The data delivery rate has been modeled as a stochastic process. The closed-loop stability analysis framework has considered the limiting probability of data dropout in computing the stability margin. The contribution is in quantifying allowable data-dropout limit for a specified closed loop performance. The research findings are useful in specifying the requirement of communication infrastructure and protocol for operating future smart grids.

Benchmark Models for the Analysis and Control of Small-Signal Oscillatory Dynamics in Power Systems

This paper summarizes a set of six benchmark systems for the analysis and control of electromechanical oscillations in power systems, recommended by the IEEE Task Force on Benchmark Systems for Stability Controls of the Power System Dynamic Performance Committee. The benchmark systems were chosen for their tutorial value and particular characteristics leading to control the system design problems relevant to the research community. For each benchmark, the modeling guidelines are provided, along with eigenvalues and time-domain results produced with at least two simulation softwares, and one possible control approach is provided for each system as well. Researchers and practicing engineers are encouraged to use these benchmark systems when assessing new oscillation damping control strategies.

Decentralized Control of Oscillatory Dynamics in Power Systems Using an Extended LQR

This paper proposes a decentralized algorithm for real-time control of oscillatory dynamics in power systems. The algorithm integrates dynamic state estimation (DSE) with an extended linear quadratic regulator (ELQR) for optimal control. The control for one generation unit only requires measurements and parameters for that unit, and hence the control at a unit remains completely independent of other units. The control gains are updated in real-time, therefore the control scheme remains valid for any operating condition. The applicability of the proposed algorithm has been demonstrated on a representative power system model.

Decentralized Nonlinear Control for Power Systems Using Normal Forms and Detailed Models

This paper proposes a decentralized method for nonlinear control of oscillatory dynamics in power systems. The method is applicable for ensuring both transient stability as well as small-signal stability. The method uses an optimal control law which has been derived in the general framework of nonlinear control using normal forms. The model used to derive the control law is the detailed subtransient model of synchronous machines as recommended by IEEE. Minimal approximations have been made in either the derivation or the application of the control law. The developed method also requires the application of dynamic state estimation technique. As the employed control and estimation schemes only need local measurements, the method remains completely decentralized. The method has been demonstrated as an effective tool to prevent blackouts by simulating a major disturbance in a benchmark power system model and its subsequent control using the proposed method.

Estimation of Inherent Governor Dead-Band and Regulation Using Unscented Kalman Filter

The inclusion of the governor droop and dead-band in dynamic models helps to reproduce the measured frequency response accurately and is a key aspect of model validation. Often, accurate and detailed turbine-governor information are not available for various units in an area control centre. The uncertainty in the droop also arise from the nonlinearity due to the governor valves. The droop and dead-band are required to tune the secondary frequency bias factors, and to determine the primary frequency reserve. Earlier research on droop estimation did not adequately take into account the effect of dead-band and other nonlinearities. In this paper, unscented Kalman filter is used in conjunction with continuously available measurements to estimate the governor droop and the dead-band width. The effectiveness of the approach is demonstrated through simulations.

An extended linear quadratic regulator for LTI systems with exogenous inputs

This paper proposes a cost effective control law for a linear time invariant (LTI) system having an extra set of exogenous inputs (or external disturbances) besides the traditional set of control inputs. No assumption is made with regard to a priori knowledge of the modeling equations for the exogenous inputs. The problem of optimal control for such a system is defined in the standard framework of linear quadratic control and an extended linear quadratic regulator (ELQR) is proposed as the solution to the problem. The ELQR approach is demonstrated through an example and is shown to be significantly more cost effective than currently available approaches for linear quadratic control.

Decentralized control of oscillatory dynamics in power systems using an extended LQR

This paper proposes a decentralized algorithm for real-time control of oscillatory dynamics in power systems. The algorithm integrates dynamic state estimation (DSE) with an extended linear quadratic regulator (ELQR) for optimal control. The control for one generation unit only requires measurements and parameters for that unit, and hence the control at a unit remains completely independent of other units. The control gains are updated in real-time, therefore the control scheme remains valid for any operating condition. The applicability of the proposed algorithm has been demonstrated on a representative power system model.

Estimating dynamic model parameters for adaptive protection and control in power system

Summary form only given. This paper presents a new approach in estimating important parameters of power system transient stability model such as inertia constant

Estimating Dynamic Model Parameters for Adaptive Protection and Control in Power System

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