Greedy robust wind farm layout optimization with feasibility guarantee. Issue 7 (3rd July 2019) - Quan, Ning; Kim, Harrison M.
ABSTRACT: This article proposes a method with light data requirements for generating robust wind farm layouts. Robustness in this work is quantified as the lowest energy conversion efficiency of the wind farm across all wind directions. A quadratic integer programming formulation for generating robustness-maximizing layouts is presented. Small instances of the proposed formulation can be solved to optimality using branch and bound. A modified greedy algorithm that guarantees solution feasibility with regards to inter-turbine safety distance is proposed to find solutions to larger problem instances. A series of experiments were conducted using real world wind data collected at two sites to demonstrate the trade-offs in power generation between robust layouts and power output maximizing layouts. The results show a loss of around 1.1% in hourly power generation in return for an increase in minimum power output of 1% to 45% across all directions for robust layouts generated in the experiments. The increase in robustness largely depends on the shape and orientation of the wind farm relative to the dominant wind direction, as well as the difference between the average wind speed at the site of the wind farm and rated wind speed of the turbines.