Open AccessWind Farm Energy Production Optimization Via Wake Steering
Author(s) -
Luiz Andre Moyses Lima,
A. K. Blatt,
Mônica Machuca
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1618/2/022016
Subject(s) - wake , wind power , maximization , computer science , minification , production (economics) , wind speed , mathematical optimization , control theory (sociology) , marine engineering , meteorology , engineering , mathematics , aerospace engineering , control (management) , electrical engineering , physics , artificial intelligence , economics , macroeconomics
The wake steering technique consists in misaligning turbines with respect to the incoming wind with the goal of displacing their wake region and reducing the wake wind speed deficit, thus increasing the power production of other turbines downwind. In this paper, an algorithm is proposed to estimate the amount of production gain a wind farm could achieve by employing this technique. Details about data treatment are provided and an analytical wake model that can represent the wakes displacement is described. A minimization algorithm to calibrate the wake model parameters based on SCADA data is presented, and the complete math needed to solve this problem is developed. Similarly, to find the optimal yaw angle values that maximize the wind farm production, a maximization problem is described along with the full development of the equations behind it. Insights on an efficient computational implementation to solve these problems are shown, based on matrix representation of the described variables. A case study is presented for a small wind farm owned by Voltalia, consisting of five turbines. Results point to an AEP gain in the order of 1%, a relevant value over the course of a project’s lifetime.