ANALYSIS OF SUBSYNCHRONOUS INTERACTION AND ITS MITIGATION FOR IMPROVING POWER SYSTEM PERFORMANCE

Abstract

The global transition toward low-carbon and sustainable power systems has accelerated the large-scale integration of renewable energy sources, particularly Doubly-Fed Induction Generator (DFIG)-based wind farms. These systems are often connected to distant load centres through long transmission corridors equipped with fixed series compensation to enhance power transfer capability. While this configuration improves efficiency and reduces infrastructure costs, it has simultaneously introduced new dynamic stability challenges collectively termed Subsynchronous Interaction (SSI). SSI represents a broad class of oscillatory phenomena involving energy exchange between the electrical network and mechanical or control subsystems at frequencies below the fundamental grid frequency. Numerous historical disturbances in the U.S., China, and Europe have confirmed that SSI remains one of the most critical threats to modern power system security, often leading to shaft failures, equipment damage, forced wind farm outages, and severe power quality deterioration. Despite widespread research on Sub-Synchronous Resonance (SSR) in conventional generator systems, the progression toward converter-dominated grids has revealed new SSI mechanisms—Sub-Synchronous Converter Control Interaction (SSCCI) and Sub-Synchronous Torsional Control Interaction (SSTCI)—that are not adequately captured by traditional IEEE classifications. A critical review of existing literature indicates that earlier studies commonly oversimplified DFIG behaviour by modeling rotor- and grid-side converters as ideal voltage sources, thereby neglecting essential controller dynamics that significantly influence SSI. Furthermore, mitigation strategies proposed in past studies relied heavily on FACTS devices, parameter tuning, or protection-based approaches, many of which are either economically impractical, sensitive to parameter variations, or insufficient under weak-grid and high compensation conditions. This gap in modelling accuracy, classification clarity, and adaptive mitigation strategy motivates the present research. This thesis develops a comprehensive framework that reclassifies SSI mechanisms, models the complete dynamics of DFIG-based wind power plants (WPPs), and vi proposes a robust control-oriented mitigation solution. A new SSI taxonomy is established, categorizing phenomena into SSR, SSCCI, and SSTCI based on dominant interaction pathways. This classification fills the conceptual gap left by traditional IEEE standards and provides a clearer foundation for understanding modern converter driven instabilities. A high-fidelity mathematical model of a 100 MW aggregated DFIG-based WPP connected through a 161 kV series-compensated transmission line is then developed. Unlike simplified approaches, this model explicitly includes turbine aerodynamics, two-mass drive-train shaft dynamics, the sixth-order DFIG electrical model, Rotor Side Converter (RSC) and Grid-Side Converter (GSC) controllers, DC-link dynamics, and the RLC behaviour of the compensated line. State-space equations for the complete system are derived to perform small-signal stability analysis. Eigenvalue analysis reveals the emergence of unstable subsynchronous modes—particularly a dominant SSR mode—whose severity increases with higher compensation levels and fluctuating wind speeds. Complementary time-domain simulations validate the predicted instability, confirming the accuracy of the developed model. To address these stability concerns, a Battery Energy Storage System–based Damping Controller (BESDC) is proposed. Owing to its bidirectional active power capability and fast converter response, BESS is well-suited for providing supplemental damping to suppress oscillations. The BESDC is first designed using a classical lead–lag structure and integrated into the power electronic interface of the BESS. Simulation results demonstrate that the controller significantly enhances damping ratios, stabilizes critical subsynchronous modes, and mitigates oscillatory behaviour under varying wind speeds and partial compensation. However, conventional fixed-parameter controllers exhibit performance degradation under off-nominal conditions, as real-world wind farms operate under wide variations in grid strength and wind profiles. To overcome this limitation, an advanced Upgraded Particle Swarm Optimization (UPSO)-based approach is introduced to optimally tune the BESDC parameters. UPSO integrates global and local search strategies, effectively resolving premature convergence issues associated with standard PSO and ensuring vii fast, accurate parameter optimization. Comparative studies confirm that UPSO-based BESDC offers superior robustness, higher damping, and faster convergence across a broad operational spectrum. Beyond electrical and mechanical interactions, the thesis also investigates transformer saturation during SSI events—a significantly underexplored phenomenon. Using a flux–voltage integral model, it is shown that subsynchronous components of voltage introduce deep flux excursions, accelerating core saturation even when the system operates within nominal limits. These flux distortions increase harmonic content, degrade power quality, elevate thermal stress, and compromise transformer lifespan. Findings emphasize that transformers, being indispensable grid interface components, must be included in SSI studies to avoid misinterpretation of system behaviour and underestimation of stability risks. Overall, this research advances the state of the art by: 1. Proposing a modern SSI classification framework tailored to renewable-rich, converter-dominated networks. 2. Developing a detailed nonlinear model of DFIG-based WPPs including all critical dynamic subsystems. 3. Identifying SSR modes through small-signal and time-domain analysis using the IEEE First Benchmark Model. 4. Designing and validating a BESS-based damping controller capable of effectively mitigating SSR in wind-integrated systems. 5. Introducing a UPSO-based optimization strategy that delivers superior damping performance and robust stability. 6. Providing new insights into transformer saturation mechanisms induced by SSI. The outcomes present a unified and practically deployable approach for enhancing SSI resilience in modern grids. The proposed UPSO-optimized BESS solution offers a scalable, fast-response, and economically viable strategy for future renewable dominated power systems, ensuring stable operation even under high converter penetration and deep series compensation.