Synchronization-aware and algorithm-efficient chance constrained optimal power flow

Russell Bent, Daniel Bienstock, Michael Chertkov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

One of the most common control decisions faced by power system operators is the question of how to dispatch generation to meet demand for power. This is a complex optimization problem that includes many nonlinear, non convex constraints as well as inherent uncertainties about future demand for power and available generation. In this paper we develop convex formulations to appropriately model crucial classes of nonlinearities and stochastic effects. We focus on solving a nonlinear optimal power flow (OPF) problem that includes loss of synchrony constraints and models wind-farm caused fluctuations. In particular, we develop (a) a convex formulation of the deterministic phase-difference nonlinear Optimum Power Flow (OPF) problem; and (b) a probabilistic chance constrained OPF for angular stability, thermal overloads and generation limits that is computationally tractable.

Original languageEnglish (US)
Title of host publicationProceedings of IREP Symposium
Subtitle of host publicationBulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, IREP 2013
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IREP Symposium on Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, IREP 2013 - Rethymno, Greece
Duration: Aug 25 2013Aug 30 2013

Publication series

NameProceedings of IREP Symposium: Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, IREP 2013

Conference

Conference2013 IREP Symposium on Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, IREP 2013
Country/TerritoryGreece
CityRethymno
Period8/25/138/30/13

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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