Imperial College London

Dr Abhinav Kumar Singh

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Visiting Researcher



a.singh11 Website CV




1108gElectrical EngineeringSouth Kensington Campus





Publication Type

18 results found

Mir AS, Singh AK, Pal BC, Senroy N, Tu Jet al., 2022, Adequacy of lyapunov control of power systems considering modelling details and control indices, IEEE Transactions on Power Systems, Pages: 1-12, ISSN: 0885-8950

Journal article

Zhao J, Gomez-Exposito A, Netto M, Mili L, Abur A, Terzija V, Kamwa I, Pal B, Singh AK, Qi J, Huang Z, Meliopoulos APSet al., 2019, Power system dynamic state estimation: motivations, definitions, methodologies, and future work, IEEE Transactions on Power Systems, Vol: 34, Pages: 3188-3198, ISSN: 0885-8950

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

Journal article

Singh AK, Pal BC, 2019, Rate of change of frequency estimation for power systems using interpolated DFT and Kalman filter, IEEE Transactions on Power Systems, Vol: 34, Pages: 2509-2517, ISSN: 0885-8950

This paper presents a new method for estimating rate of change of frequency (RoCoF) of voltage or current signals measured using instrument transformers. The method is demonstrably superior to currently available methods in literature, in terms of estimation-latency and estimation-error. The estimation is performed in two steps. In the first step, the analog voltage or current signal obtained from an instrument transformer is statistically processed using interpolated discrete Fourier transform in order to obtain the means and variances of the signal parameters. These means and variances are then given as inputs to the second step, in which Kalman filtering is used to find the final RoCoF estimate. Accurate mathematical expressions for the means and variances of signal parameters have been derived and used in the second step, which is the main reason behind the superior performance of the method. The applicability of the method has been demonstrated on a benchmark power system model.

Journal article

Singh AK, Pal BC, 2018, Dynamic Estimation and Control of Power Systems, Publisher: Academic Press, ISBN: 9780128140062

Dynamic estimation and control is a fast growing and widely researched field of study that lays the foundation for a new generation of technologies that can dynamically, adaptively and automatically stabilize power systems. This book provides a comprehensive introduction to research techniques for real-time estimation and control of power systems.Dynamic Estimation and Control of Power Systems coherently and concisely explains key concepts in a step by step manner, beginning with the fundamentals and building up to the latest developments of the field. Each chapter features examples to illustrate the main ideas, and effective research tools are presented for signal processing-based estimation of the dynamic states and subsequent control, both centralized and decentralized, as well as linear and nonlinear. Detailed mathematical proofs are included for readers who desire a deeper technical understanding of the methods.This book is an ideal research reference for engineers and researchers working on monitoring and stability of modern grids, as well as postgraduate students studying these topics. It serves to deliver a clear understanding of the tools needed for estimation and control, while also acting as a basis for readers to further develop new and improved approaches in their own research.


Bhui P, Senroy N, Singh A, Pal Bet al., 2018, Estimation of inherent governor dead-band and regulation using unscented Kalman filter, IEEE Transactions on Power Systems, Vol: 33, Pages: 3546-3558, ISSN: 0885-8950

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 deadband 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

Journal article

Singh AK, Pal BC, 2018, Decentralized robust dynamic state estimation in power systems using instrument transformers, IEEE Transactions on Signal Processing, Vol: 66, Pages: 1541-1550, ISSN: 1053-587X

This paper proposes a decentralized method for estimation of dynamic states of a power system. The method remains robust to time-synchronization errors and high noise levels in measurements. Robustness of the method has been achieved by incorporating internal angle in the dynamic model used for estimation and by decoupling the estimation process into two stages with continuous updation of measurement-noise variances. Additionally, the proposed estimation method does not need measurements obtained from phasor measurement units; instead, it just requires analog measurements of voltages and currents directly acquired from instrument transformers. This is achieved through statistical signal processing of analog voltages and currents to obtain their magnitudes and frequencies, followed by application of unscented Kalman filtering for nonlinear estimation. The robustness and feasibility of the method have been demonstrated on a benchmark power system model.

Journal article

Singh AK, Pal BC, 2017, Decentralized nonlinear control for power systems using normal forms and detailed models, IEEE Transactions on Power Systems, Vol: 33, Pages: 1160-1172, ISSN: 1558-0679

This paper proposes a decentralized method fornonlinear control of oscillatory dynamics in power systems. Themethod is applicable for ensuring both transient stability as wellas small-signal stability. The method uses an optimal control lawwhich has been derived in the general framework of nonlinearcontrol using normal forms. The model used to derive the controllaw is the detailed subtransient model of synchronous machinesas recommended by IEEE. Minimal approximations have beenmade in either the derivation or the application of the controllaw. The developed method also requires the application ofdynamic state estimation technique. As the employed control andestimation schemes only need local measurements, the methodremains completely decentralized. The method has been demon-strated as an effective tool to prevent blackouts by simulating amajor disturbance in a benchmark power system model and itssubsequent control using the proposed method.

Journal article

Singh A, Pal B, 2016, An extended linear quadratic regulator for LTI systems with exogenous inputs, Automatica, Vol: 76, Pages: 10-16, ISSN: 0005-1098

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

Journal article

Canizares C, Farnandes T, Gerladi E, Lajoie-Gerin E, Gibbard M, Hiskens I, Kersulis J, Kuiava R, Lima L, De Marco F, Martins N, Pal BC, Piardi A, Ramos R, dos Santos J, Silva D, Singh AK, Tamimi B, Vowels Det al., 2016, Benchmark models for the analysis and control of small-signal oscillatory dynamics in power systems, IEEE Transactions on Power Systems, Vol: 32, Pages: 715-722, ISSN: 1558-0679

This paper summarizes a set of six benchmark systemsfor the analysis and control of electromechanical oscillationsin power systems recommended by the IEEE Task Force onBenchmark Systems for Stability Controls of the Power SystemDynamic Performance Committee. The benchmark systems werechosen for their tutorial value and particular characteristicsleading to control system design problems relevant to the researchcommunity. For each benchmark, the modelling guidelinesare provided, along with eigenvalues and time-domain resultsproduced with at least two simulation software, and onepossible control approach is provided for each system as well.Researchers and practicing engineers are encouraged to use thesebenchmark systems when assessing new oscillation dampingcontrol strategies.

Journal article

Singh A, Pal B, 2016, An extended linear quadratic regulator and its application for control of power system dynamics, IEEE First International Conference on Control, Measurement and Instrumentation (CMI), Publisher: IEEE, Pages: 110-114

This paper presents a generalized solution to the problem of optimal control of systems having an extra set of exogenous inputs besides control inputs. The solution is derived in the framework of linear quadratic control and it is termed `extended linear quadratic regulator (ELQR)'. The ELQR is applied for control of unstable or poorly damped oscillatory dynamics occurring in a power system and is shown to be significantly more cost effective than the classical power system stabilizer (PSS) based approach.

Conference paper

Canizares C, Fernandes T, Geraldi Jr E, Gerin-Lajoie L, Gibbard M, Hiskens I, Kersulis J, Kuiava R, Lima L, Marco FD, Martins N, Pal BC, Piardi A, Ramos R, Santos JD, Silva D, Singh AK, Tamimi B, Vowels Det al., 2015, Benchmark Systems for Small-Signal Stability Analysis and Control, Publisher: IEEE Power and Energy Society

This report documents the work of the IEEE PES Task Force (TF) on Benchmark Systems for Stability Controls. The following sections present the objectives of the TF, the guidelines used to select the benchmarks, a brief description of each benchmark system so the reader can select the most suitable system for the intended application, the input data and results for each benchmark system, and a set of conclusions.Detailed descriptions of each system are also presented in the Appendices to this report and in the website created by this Task Force to share the data and simulation results related to the benchmark systems.


Singh AK, Pal BC, 2015, Decentralized Control of Oscillatory Dynamics in Power Systems using an Extended LQR, IEEE Transactions on Power Systems, Vol: 31, Pages: 1715-1728, ISSN: 1558-0679

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.

Journal article

Singh AK, 2015, Decentralized Estimation and Control for Power Systems

This thesis presents a decentralized alternative to the centralized state-estimation and control technologies used in current power systems. Power systems span over vast geographical areas, and therefore require a robust and reliable communication network for centralized estimation and control. The supervisory control and data acquisition (SCADA) systems provide such a communication architecture and are currently employed for centralized estimation and control of power systems in a static manner. The SCADA systems operate at update rates which are not fast enough to provide appropriate estimation or control of transient or dynamic events occurring in power systems. Packet-switching based networked control system (NCS) is a faster alternative to SCADA systems, but it suffers from some other problems such as packet dropouts, random time delays and packet disordering. A stability analysis framework for NCS in power systems has been presented in the thesis considering these problems. Some other practical limitations and problems associated with real-time centralized estimation and control are computational bottlenecks, cyber threats and issues in acquiring system-wide parameters and measurements.The aforementioned problems can be solved by a decentralized methodology which only requires local parameters and measurements for estimation and control of a local unit in the system. The cumulative effect of control at all the units should be such that the global oscillations and instabilities in the power system are controlled. Such a decentralized methodology has been presented in the thesis. The method for decentralization is based on a new concept of `pseudo-inputs' in which some of the measurements are treated as inputs. Unscented Kalman filtering (UKF) is applied on the decentralized system for dynamic state estimation (DSE). An extended linear quadratic regulator (ELQR) has been proposed for the optimal control of each local unit such that the whole power system is sta

Thesis dissertation

Ariff MAM, Pal BC, Singh AK, 2014, Estimating Dynamic Model Parameters for Adaptive Protection and Control in Power System, IEEE Transactions on Power Systems, ISSN: 0885-8950

This paper presents a new approach in estimating important parameters of power system transient stability model such as inertia constant H and direct axis transient reactance x′d in real time. It uses a variation of unscented Kalman filter (UKF) on the phasor measurement unit (PMU) data. The accurate estimation of these parameters is very important for assessing the stability and tuning the adaptive protection system on power swing relays. The effectiveness of the method is demonstrated in asimulated data from 16-machine 68-bus system model. The paper also presents the performance comparison between the UKF and EKF method in estimating the parameters. The robustness of method is further validated in the presence of noise that is likely to be in the PMU data in reality.

Journal article

Singh A, Pal BC, Singh R, 2014, Stability Analysis of Networked Control in Smart Grids, IEEE Transactions on Smart Grid, Vol: 6, Pages: 381-390, ISSN: 1949-3053

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.

Journal article

Singh A, Pal BC, 2014, Decentralized Dynamic State Estimation in Power Systems Using Unscented Transformation, IEEE Transactions on Power Systems, Vol: 29, Pages: 794-804, ISSN: 0885-8950

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.

Journal article

Singh AK, Pal BC, 2013, IEEE PES Task Force on Benchmark Systems for Stability Controls - Report on the 68-Bus, 16-Machine, 5-Area System, Publisher: IEEE Power and Energy Society

This report refers to a small-signal stability study carried over the 68-Bus, 16-Machine, 5-Area Sys-tem and validated on a widely known software package: MATLAB-Simulink (ver. 2012b). The 68-bus sys-tem is a reduced order equivalent of the inter-connected New England test system (NETS) and New York power system (NYPS), with five geographical regions out of which NETS and NYPS are represented by a group of generators whereas, the power import from each of the three other neighboring areas are approxi-mated by equivalent generator models. This report has the objective to show how the simulation of this system must be done using MATLAB in order to get results that are comparable (and exhibit a good match with respect to the electromechanical modes) with the ones obtained using other commercial software packages and presented on the PES Task Force website on Benchmark Systems for Stability Controls (


Singh AK, Sawan S, Hanmandlu M, Madasu VK, Lovell BCet al., 2009, An Abandoned Object Detection System Based on Dual Background Segmentation, Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009. AVSS '09., Publisher: IEEE, Pages: 352-357

An abandoned object detection system is presented and evaluated using benchmark datasets. The detection is based on a simple mathematical model and works efficiently at QVGA resolution at which most CCTV cameras operate. The pre-processing involves a dual-time background subtraction algorithm which dynamically updates two sets of background, one after a very short interval (less than half a second) and the other after a relatively longer duration. The framework of the proposed algorithm is based on the Approximate Median model. An algorithm for tracking of abandoned objects even under occlusion is also proposed. Results show that the system is robust to variations in lighting conditions and the number of people in the scene. In addition, the system is simple and computationally less intensive as it avoids the use of expensive filters while achieving better detection results.

Conference paper

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