The electrification of surface mining increasingly proceeds on weak, reconfigurable feeders, where large induction-motor transients trigger deep voltage sags that disrupt production. Operators and equipment manufacturers, therefore, require insights into mining machine configurations that ensure dynamic stability and ride-through on weak grids. This thesis develops a system-level modeling and simulation framework for electrified drill rigs that compares front-end topologies and support strategies under representative operating scenarios. The framework formulates the nonlinear state-space model of the drill rig and its grid interface, covering direct-on-line induction motors, passive rectifier, active front-ends plus variable-speed drive, with an optional directcurrent link battery. The stability of such models is assessed with small-signal eigenvalue analysis and large-signal Lyapunov analysis with a reduced-order model. The performance is screened across operating points that include start events and load steps to obtain the dynamic response. The results provide maps of stability and ride-through boundaries over feeder strength and line impedance characteristics. Apart from the comparison of interface choices, potential voltage sag mitigation methods are discussed and tested via case studies based on validated drill rig models. Key findings indicate that direct-current-link battery support enlarges the stable region and helps drill rigs to ride through severe voltage sags and enhance synchronization. At the site level, shifting selected drill rigs to gridforming control enables fast reactive injection that lifts multiple non-compliant scenarios toward SEMI F47 tolerance. The contributions of this thesis are (i) a validated, modular drill rig model that connects component-level models to feeder-level behavior, (ii) reduced-order models that explain the dominant large signal dynamics, and (iii) decision maps and practical guidelines for drill rig topology selection to enhance voltage-sag ride-through and defer upstream reinforcement.
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Zheng Yan
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Zheng Yan (Wed,) studied this question.