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Continuously Differentiable Analytical Models for Implicit Control within Power Flow

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arxiv 1811.02000 v1 pith:DBK6FBCE submitted 2018-11-05 eess.SP

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keywords powerflowmodelscontrolconvergencesolutioncasescontinuously
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Achieving robust and scalable convergence for simulation of realistic power flow cases can be challenging. One specific issue relates to the disconnected solution space that is created by the use of piecewise-discontinuous models of power grid devices that perform control mechanisms. These models are generally resolved by outer iteration loops around power flow, which can result in solution oscillations, increased iteration count, divergence or even convergence to a solution in an unstable operational region. This paper introduces a continuously differentiable model for device control mechanisms that is incorporated within the power flow formulation. To ensure robust power flow convergence properties, recently introduced homotopy methods are extended to include these continuous models. The scalability and efficacy of the proposed formulation is demonstrated on several large-scale test cases that represent the US Eastern Interconnect network, the Synthetic USA, and the Nigerian grid.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. PACR: Parameter-Optimized AC Power Flow Restoration for AC Feasible DCOPF Dispatch

    eess.SY 2026-06 unverdicted novelty 6.0 of 10

    PACR optimizes parameters in a differentiable AC power-flow restoration procedure using the implicit function theorem to map DCOPF dispatches to AC-feasible points, reporting improved recovery on IEEE, ACTIVSg, and PE...

  2. Towards AC Feasibility of DCOPF Dispatch

    eess.SY 2025-11 conditional novelty 5.0 of 10

    A two-stage pipeline pairing a loss-augmented DCOPF with an AC power flow using distributed slack and PV/PQ switching restores AC feasibility for most tested DCOPF dispatches, cutting cost error by 93% on a 13,659-bus case.

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