Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms

Jennifer King, Christopher Bay, Emiliano Dall'Anese, Mingyi Hong

Research output: Contribution to conferencePaperpeer-review

8 Scopus Citations

Abstract

This paper presents a distributed approach to performing real-time optimization of large wind farms. Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. This paper optimizes the overall power produced by a wind farm by formulating and solving a nonconvex optimization problem where the yaw angles are optimized to allow some turbines to operate in misaligned conditions and shape the aerodynamic interactions in a favorable way. The solution of the nonconvex smooth problem is tackled using a proximal primal-dual gradient method, which provably identifies a first-order stationary solution in a global sublinear manner. By adding auxiliary optimization variables for every pair of turbines that are coupled aerodynamically, and properly adding consensus constraints into the underlying problem, a distributed algorithm with turbine-to-turbine message passing is obtained; this allows for turbines to be optimized in parallel using local information rather than information from the whole wind farm. This algorithm is computationally light, as it involves closed-form updates. This approach is demonstrated on a large wind farm with 60 turbines. The results indicate that similar performance can be achieved as with finite-difference gradient-based optimization at a fraction of the computational time and thus approaching real-time control/optimization.

Original languageAmerican English
Pages4173-4178
Number of pages6
DOIs
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: 10 Jul 201912 Jul 2019

Conference

Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States
CityPhiladelphia
Period10/07/1912/07/19

Bibliographical note

See NREL/CP-5000-73395 for preprint

NREL Publication Number

  • NREL/CP-5000-75051

Keywords

  • distributed optimization
  • optimization
  • performance
  • wind energy
  • wind farm control

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