ThinkTankTalk: Daniel Molzahn (Georgia Tech)

Event Details
  • Date/Time:
    • Monday October 5, 2020
      11:00 am - 12:00 pm
  • Location: Virtual via Bluejeans
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Summaries

Summary Sentence: Applications of Polynomial Optimization in Electric Power Systems: Virtual via Bluejeans at 11:00am

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Algorithms & Randomness Center (ARC)

ThinkTankTalk

Daniel Molzahn (Georgia Tech)

Monday, October 5, 2020

Virtual via Bluejeans - 11:00 am

 

Title: Applications of Polynomial Optimization in Electric Power Systems

Abstract:  Electric power systems are critical infrastructure that underlie almost all aspects of modern society. With rapidly increasing quantities of renewable generation and the continuing expansion of electricity markets, electric power systems are undergoing significant changes. New algorithms for optimizing the design and operation of electric power systems are needed in order to enable these transformational changes.

The so-called “power flow equations” are at the heart of power system optimization problems. These equations, which model the physics of electric power grids, can be represented as systems of polynomials. This presentation describes recent work and open questions in applying polynomial optimization theory to power system optimization problems. Some open questions involve developing efficient methods for computing multiple real solutions to the power flow equations for given choices of parameters (load demands and generator outputs). When these parameters are allowed to vary, the Lasserre hierarchy of moment/sum-of-squares relaxations can be applied to compute the global optima of optimization problems constrained by the power flow equations. Relevant questions include deriving sufficient conditions which ensure tightness of these relaxations and developing efficient methods for scaling these relaxations to large systems.

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Seminar/Lecture/Colloquium
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Status
  • Created By: Francella Tonge
  • Workflow Status: Published
  • Created On: Sep 1, 2020 - 9:24am
  • Last Updated: Sep 28, 2020 - 9:04am