arXiv subjects

Nilanjan Ray Chaudhuri

Publications and source records attributed to Nilanjan Ray Chaudhuri.

17 recordsLinked to original sources

arXiv2026

A Dynamic Phasor Framework for Analysis of Subsynchronous Oscillations in Multi-Machine Systems with IBRs and Large Loads

Although the electromagnetic transient (EMT) framework can capture subsynchronous oscillations (SSOs), it faces scalability issues for large-scale systems. Thus motivated, we propose a generalized dynamic phasor (DP) framework to analyze SSOs in multi-machine systems with inverter-based resources (IBRs) and large loads such as artificial intelligence data centers (AI DCs) under balanced and unbalanced conditions. The grid-following (GFL) and grid-forming (GFM) IBRs are modeled in their respective $dq$-frame DPs. In contrast, the detailed model of multi-mass turbine driven synchronous generators (SGs) along with dynamic transmission network models and loads are represented in $pnz$-frame DPs. The linearizability and time-invariance of the framework enable us to perform eigen decomposition, which is a powerful tool for root-cause analysis of SSO modes and the design of damping controllers. In addition, the DP modeling approach facilitates faster simulation of large-scale systems. The generalized framework is validated with EMTDC/PSCAD simulations using the IEEE first benchmark model for subsynchronous resonance and the modified IEEE 4-machine system. Several use cases are presented on the modified IEEE 68-bus system with two GFL IBRs to show the applicability of the framework. First, time- and frequency-domain analyses of the IBR-induced SSO mode are presented. Then, two solutions are proposed to damp the poorly damped SSO mode: (a) a decentralized controller is designed using particle swarm optimization, and (b) the control of one GFL IBR is replaced by GFM control. Finally, the impact of AI DC load on primary frequency response of the system and the multi-mass turbines of the SGs are studied.

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arXiv2026

Limiting the Impact of AI Data Centers on Fatigue Life of Thermal Turbine Generators in the Grid: A Frequency-Domain Approach

A framework is established that assesses the impact of variations in artificial intelligence (AI) data center (DC) loads on the fatigue damage of steam/gas turbines of the synchronous generators (SGs) from torsional oscillations. Next, a simple three-step process that is supported by frequency-domain analysis is laid out to quantify the limits on fluctuations in AI DC loads. In the first step, the maximum allowable variation in electrical power output at each SG terminal is independently determined from the first principles. This step needs only a lumped multi-mass model of the mechanical side of the SG. In the second step, we propose a new approach that relies on load flow to determine the so-called algebraic `interaction factor' that maps the change in AI DC load at a given bus to the corresponding change in each of the SG power outputs. In the third step, we propose a screening method to rank the candidate buses to site AI DCs and solve an optimization problem to determine the optimal allowable fluctuations in the AI DCs. We demonstrate the applicability of the proposed approach through frequency-domain and time-domain analyses in the modified IEEE 4-machine and IEEE-68 bus systems using a dynamic phasor framework. Finally, we demonstrate the scalability of the proposed approach on the synthetic 2000-bus Texas system.

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arXiv2026

A Dynamic Phasor Framework for Analysis of IBR-Induced SSOs in Multi-Machine Systems

We propose a generalized dynamic phasor (DP) framework to analyze inverter-based resources (IBRs) connected to multi-machine systems under balanced and unbalanced conditions. It captures subsynchronous oscillations (SSOs) induced by grid-following (GFL) IBRs. The linearizability and time invariance of the framework enables us to perform eigen decomposition, which is a powerful tool for root-cause analysis of the SSO modes and damping controller design. The same framework also enables analysis of excitation of the SSO modes in presence of data center (DC) loads. The GFL IBRs are modeled in their respective $dq$-frame DPs and the detailed model of synchronous generators (SGs) along with dynamic transmission network models are represented in $pnz$-frame DPs. Several case studies are performed on the modified IEEE two-area benchmark system, where $2$ SGs are replaced by GFL IBRs and validated with EMTDC/PSCAD simulations. First, time- and frequency-domain analyses of the SSO mode are presented followed by the design of a robust decentralized $\mathcal{H}_\infty$ damping controller based on local signals of the GFL IBRs. Second, the dynamic behavior of the system following an unbalanced fault is demonstrated that is damped by the proposed damping controller. Finally, excitation of the SSO mode in presence of DC load is exhibited and its locational impact is analytically quantified.

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arXiv2025

A Dynamic Phasor Framework for Analysis of Grid-Forming Converter Connected to Series-Compensated Line

A dynamic phasor (DP) framework for time-domain and frequency-domain analyses of grid-forming converters (GFCs) connected to series-compensated transmission lines is proposed. The proposed framework can capture the behavior of GFCs subjected to unbalanced short circuit faults in presence of different current limiting strategies. Moreover, the linearizability and time invariance of this framework allows us to perform eigen decomposition, which is a powerful tool for root-cause analysis and control design. We show that a certain degree of series compensation may result in poorly-damped oscillations in presence of the grid-forming converter. A participation factor analysis using the DP model reveals that the point of interconnection voltage angle is dominant in this mode. Eigenvalue sensitivity analysis of controller parameters shows that reducing the power-frequency droop coefficient is most effective in stabilizing the poorly-damped mode. Detailed validation with electromagnetic transient model demonstrates the accuracy of the proposed framework.

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arXiv2025

Robust Adaptive Supplementary Control for Damping Weak-Grid SSOs Involving IBRs

Subsynchronous oscillations (SSOs) involving grid-following converters (GFLCs) connected to weak grids are a relatively new phenomena observed in modern power systems. SSOs are further exacerbated when grids become weaker because lines are disconnected due to maintenance or following faults. Such undesirable oscillations have also led to curtailment of inverter-based resource (IBR) outputs. In contrast to most literature addressing the issue by retuning/redesigning of standard IBR controllers, we propose a robust adaptive supplementary control for damping of such SSOs while keeping standard controls unaltered. As a result, uncertainty in system conditions can be handled without negatively impacting the nominal IBR performance. To that end, the adaptive control law is derived for a GFLC connected to the grid, where the grid is modeled by the Thevenin's equivalent representation with uncertainty and disturbances. The theoretical result provides dissipativity certificate for the closed-loop error dynamics with sufficient conditions for stability. The effectiveness of the developed controller is validated with several case studies conducted on a single-GFLC-infinite-bus test system, the IEEE $2$-area test system, wherein some of the synchronous generators are replaced by GFLCs, and a modified IEEE $5$-area test system with two GFLCs. The findings demonstrate that under very weak grid conditions, the proposed robust adaptive control performs well in stabilizing SSO modes, which a classical state-feedback control method fails to address.

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arXiv2024

Discovery and Characterization of Cross-Area and Intra-Area SSOs Sensitive to Delay in Droop Control of Grid-Forming Converters

Subsynchronous oscillations (SSOs) involving grid-forming converters (GFCs) are in a less familiar territory of power system dynamics. This letter reports a new phenomenon namely cross-area SSOs in grids with 100% droop-controlled GFC-based renewable penetration, which was discovered during our study on evaluating the adequacy of quasistationary phasor calculus (QPC) and space phasor calculus (SPC)-based models in capturing SSOs. We present frequency-domain characterization of such oscillatory modes in addition to intra-area SSOs in grids involving GFCs and study the impact of a delay in power-frequency droop feedback loop in regards to their stability. Electromagnetic transient (EMT) simulations validate our findings.

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arXiv2024

An Approach to Evaluate Modeling Adequacy for Small-Signal Stability Analysis of IBR-related SSOs in Multimachine Systems

Time-varying phasor-based analysis of subsynchronous oscillations (SSOs) involving grid-following converters (GFLCs) and its benchmarking with electromagnetic transient (EMT) models have so far been restricted to highly simplified grid models with constant voltage sources behind series R-L circuits. In this paper, modeling adequacy of bulk power systems with synchronous generators (SGs), transmission systems, loads, and GFLCs are considered. To this end, we revisit the notions of time-varying phasor calculus, highlighting the distinction between space-phasor-calculus (SPC) and two often interchangeably used frameworks namely baseband-abc and generalized averaging. We present the models of grids in SPC framework that include transmission line dynamics, load dynamics, and SG stator transients. Next, we propose a generic approach to study modeling adequacy in small-signal sense by (a) identifying critical modes through eigenvalue and singular value analysis followed by (b) using weighted maximum singular value error magnitudes as metrics, and (c) further cross-validation. Using a modified 4-machine IEEE benchmark model with up to 3 GFLCs we show that SPC framework can be used for analysis of SSOs. Further, we consider the quasistationary phasor calculus (QPC) framework that neglects transmission line, load, and SG stator dynamics to show its adequacy in SSO modeling and analysis. Time-domain and frequency-domain results with EMT models are also presented.

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arXiv2024

A Case Study on Modeling Adequacy of a Grid with Subsynchronous Oscillations Involving IBRs

A case study on modeling adequacy of a grid in presence of renewable resources based on grid-forming converters (GFCs) is the subject matter of this paper. For this purpose, a 4-machine 11-bus IEEE benchmark model is modified by considering GFCs replacing synchronous generators that led to unstable subsynchronous oscillations (SSOs). We aim to: (a) understand if transmission network dynamics should be considered in such cases, (b) revisit the space-phasor-calculus (SPC) in d-q frame under balanced condition that captures such phenomena and lends itself to eigenvalue analysis, and (c) emphasize limitations of such models while underscoring their importance for large-scale power system simulations. Time-domain and frequency-domain results from SPC and quasistationary phasor calculus (QPC) models are compared with electromagnetic transient (EMT)-based simulations. It is shown that models with transmission line dynamics in SPC framework can capture the SSO mode while QPC models that neglect these dynamics fail to do so.

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arXiv2022

An Approach for Fast Cascading Failure Simulation in Dynamic Models of Power Systems

The ground truth for cascading failure in power system can only be obtained through a detailed dynamic model involving nonlinear differential and algebraic equations whose solution process is computationally expensive. This has prohibited adoption of such models for cascading failure simulation. To solve this, we propose a fast cascading failure simulation approach based on implicit Backward Euler method (BEM) with stiff decay property. Unfortunately, BEM suffers from hyperstability issue in case of oscillatory instability and converges to the unstable equilibrium. We propose a predictor-corrector approach to fully address the hyperstability issue in BEM. The predictor identifies oscillatory instability based on eigendecomposition of the system matrix at the post-disturbance unstable equilibrium obtained as a byproduct of BEM. The corrector uses right eigenvectors to identify the group of machines participating in the unstable mode. This helps in applying appropriate protection schemes as in ground truth. We use Trapezoidal method (TM)-based simulation as the benchmark to validate the results of the proposed approach on the IEEE 118-bus network, 2,383-bus Polish grid, and IEEE 68-bus system. The proposed approach is able to track the cascade path and replicate the end results of TM-based simulation with very high accuracy while reducing the average simulation time by approximately 10-35 fold. The proposed approach was also compared with the partitioned method, which led to similar conclusions.

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arXiv2022

Preventing Outages under Coordinated Cyber-Physical Attack with Secured PMUs

Due to the potentially severe consequences of coordinated cyber-physical attacks (CCPA), the design of defenses has gained significant attention. A popular approach is to eliminate the existence of attacks by either securing existing sensors or deploying secured PMUs. In this work, we improve this approach by lowering the defense target from eliminating attacks to preventing outages and reducing the required number of PMUs. To this end, we formulate the problem of PMU Placement for Outage Prevention (PPOP) under DC power flow model as a tri-level non-linear optimization problem and transform it into a bi-level mixed-integer linear programming (MILP) problem. Then, we propose an alternating optimization framework to solve PPOP by iteratively adding constraints, for which we develop two constraint generation algorithms. In addition, for large-scale grids, we propose a polynomial-time heuristic algorithm to obtain suboptimal solutions. Next, we extend our solution to achieve the defense goal under AC power flow model. Finally, we evaluate our algorithm on IEEE 30-bus, 57-bus, 118-bus, and 300-bus systems, which demonstrates the potential of the proposed approach in greatly reducing the required number of PMUs.

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arXiv2021

Extending the Dissipating Energy Flow Method to Flexible AC Transmission Systems

In recent years, the dissipating energy flow (DEF) method has emerged as a promising tool for online localization of oscillation sources. In literature, the mathematical foundations of this method are well-studied for networks with synchronous generators. In this paper, we extend the analysis to flexible AC transmission systems (FACTS). To that end, we derive the DEF-expressions for a thyristor controlled series capacitor (TCSC) and a static synchronous compensator (STATCOM) operating with conventional control strategies. Analyzing their respective DEFs, we obtain the conditions for which these FACTS devices could behave as the sources of oscillation energy. Our findings are structured into propositions and are supported through numerical case studies on IEEE test systems.

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arXiv2021

Dissipation of Oscillation Energy and Distribution of Damping Power in a Multimachine Power System: A Small-signal Analysis

This paper revisits the concept of damping torque in a multimachine power system and its relation to the dissipation of oscillation energy in synchronous machine windings. As a multimachine extension of an existing result on a single-machine-infinite-bus (SMIB) system, we show that the total damping power for a mode stemming from the interaction of electromagnetic torques and rotor speeds is equal to the sum of average power dissipations in the generator windings corresponding to the modal oscillation. Further, counter-intuitive to the SMIB result, we demonstrate that, although the equality holds on an aggregate, such is not the case for individual machines in an interconnected system. To that end, distribution factors are derived for expressing the average damping power of each generator as a linear combination of average powers of modal energy dissipation in the windings of all machines in the system. These factors represent the distribution of damping power in a multimachine system. The results are validated on IEEE 4-machine and 16-machine test systems.

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arXiv2021

Topology Estimation Following Islanding and its Impact on Preventive Control of Cascading Failure

Knowledge of power grid's topology during cascading failure is an essential element of centralized blackout prevention control, given that multiple islands are typically formed, as a cascade progresses. Moreover, academic research on interdependency between cyber and physical layers of the grid indicate that power failure during a cascade may lead to outages in communication networks, which progressively reduce the observable areas. These challenge the current literature on line outage detection, which assumes that the grid remains as a single connected component. We propose a new approach to eliminate that assumption. Following an islanding event, first the buses forming that connected components are identified and then further line outages within the individual islands are detected. In addition to the power system measurements, observable breaker statuses are integrated as constraints in our topology identification algorithm. The impact of error propagation on the estimation process as reliance on previous estimates keeps growing during cascade is also studied. Finally, the estimated admittance matrix is used in preventive control of cascading failure, creating a closed-loop system. The impact of such an interlinked estimation and control on that total load served is studied for the first time. Simulations in IEEE-118 bus system and 2,383-bus Polish network demonstrate the effectiveness of our approach.

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arXiv2021

On Stability Analysis of Power Grids with Synchronous Generators and Grid-Forming Converters under DC-side Current Limitation

Stability of power grids with synchronous generators (SGs) and renewable generation interfaced with grid-forming converters (GFCs) under dc-side current limitation is studied. To that end, we first consider a simple 2-bus test system and reduced-order models to highlight the fundamental difference between two classes of GFC controls -- (A) droop, dispatchable virtual oscillator control (dVOC) and virtual synchronous machine (VSM), and (B) matching control. Next, we study Lyapunov stability and input-output stability of the dc voltage dynamics of class-A GFCs for the simple system and extend it to a generic system. Next, we provide a sufficiency condition for input-to-state stability of the 2-bus system with a class-B GFC and extend it for a generic system. Finally, time-domain simulations from a reduced-order averaged model of the simple test system and a detailed switched model of the GFC validate the proposed conditions.

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arXiv2021

Power Grid State Estimation under General Cyber-Physical Attacks

Effective defense against cyber-physical attacks in power grid requires the capability of accurate damage assessment within the attacked area. While some solutions have been proposed to recover the phase angles and the link status (i.e., breaker status) within the attacked area, existing solutions made the limiting assumption that the grid stays connected after the attack. To fill this gap, we study the problem of recovering the phase angles and the link status under a general cyber-physical attack that may partition the grid into islands. To this end, we (i) show that the existing solutions and recovery conditions still hold if the post-attack power injections in the attacked area are known, and (ii) propose a linear programming-based algorithm that can perfectly recover the link status under certain conditions even if the post-attack power injections are unknown. Our numerical evaluations based on the Polish power grid demonstrate that the proposed algorithm is highly accurate in localizing failed links once the phase angles are known.

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arXiv2021

Verifiable Failure Localization in Smart Grid under Cyber-Physical Attacks

Cyber-physical attacks impose a significant threat to the smart grid, as the cyber attack makes it difficult to identify the actual damage caused by the physical attack. To defend against such attacks, various inference-based solutions have been proposed to estimate the states of grid elements (e.g., transmission lines) from measurements outside the attacked area, out of which a few have provided theoretical conditions for guaranteed accuracy. However, these conditions are usually based on the ground truth states and thus not verifiable in practice. To solve this problem, we develop (i) verifiable conditions that can be tested based on only observable information, and (ii) efficient algorithms for verifying the states of links (i.e., transmission lines) within the attacked area based on these conditions. Our numerical evaluations based on the Polish power grid and IEEE 300-bus system demonstrate that the proposed algorithms are highly successful in verifying the states of truly failed links, and can thus greatly help in prioritizing repairs during the recovery process.

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arXiv2020

Power System Disturbance Classification with Online Event-Driven Neuromorphic Computing

Accurate online classification of disturbance events in a transmission network is an important part of wide-area monitoring. Although many conventional machine learning techniques are very successful in classifying events, they rely on extracting information from PMU data at control centers and processing them through CPU/GPUs, which are highly inefficient in terms of energy consumption. To solve this challenge without compromising accuracy, this paper presents a novel methodology based on event-driven neuromorphic computing architecture for classification of power system disturbances. A Spiking Neural Network (SNN)-based computing framework is proposed, which exploits sparsity in disturbances and promotes local event driven operation for unsupervised learning and inference from incoming data. Spatio-temporal information of PMU signals is first extracted and encoded into spike trains and classification is achieved with SNN-based supervised and unsupervised learning framework. Moreover, a QR decomposition-based selection technique is proposed to identify signals participating in the low rank subspace of multiple disturbance events. Performance of the proposed method is validated on data collected from a 16-machine, 5-area New England-New York system.

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