GridCal
matplotlib_3_0_3
  • About GridCal
  • Getting Started
  • API reference
  • Theory behind GridCal
    • The assets manager: from objects to matrices
    • Universal Branch Model
    • Transformer definition from SC test values
    • Power Flow
      • Newton-Raphson
      • Levenberg-Marquardt
      • DC approximation
      • Linear AC Power Flow
      • Holomorphic Embedding
      • Post Power Flow (Loading and Losses)
      • Continuation power flow
    • Optimal power flow
      • Linear optimal power flow
      • Linear optimal power flow time series
    • Short Circuit
      • 3-Phase Short Circuit
  • Graphical User Interface
  • Development
  • Change log
GridCal
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  • Theory behind GridCal »
  • Power Flow
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Power Flow¶

The following subsections include theory about the power flow algorithms supported by GridCal. For control modes (both reactive power control and transformer OLTC control), refer to the Power Flow Driver API Reference.

  • Newton-Raphson
    • Canonical Newton-Raphson
    • Jacobian in power equations
    • Newton-Raphson-Iwamoto
    • Newton-Raphson Line Search
    • Newton-Raphson in Current Equations
  • Levenberg-Marquardt
  • DC approximation
  • Linear AC Power Flow
  • Holomorphic Embedding
    • Concepts
    • Fundamentals
    • Padè approximation
    • Formulation with PV nodes
  • Post Power Flow (Loading and Losses)
  • Continuation power flow
    • Predictor
    • Corrector

Optimal power flow¶

  • Linear optimal power flow
    • Objective function
    • Power injections
    • Nodal power balance
    • Branch loading restriction
  • Linear optimal power flow time series
    • Objective function
    • Power injections
    • Nodal power balance
    • Branch loading restriction
    • Battery discharge restrictions

Short Circuit¶

  • 3-Phase Short Circuit
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© Copyright 2019, Santiago Peñate Vera Revision 14c51273.

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