Multi-scale design optimization of modern offshore wind farms

Abstract

The traditional optimization of the layout of a farm consisted in arranging the turbines inside a designated area. In contrast, the 2021 tender from the UK government, Offshore Wind Leasing Round 4 (UK Round-4) and upcoming bids only specify large regions where the farm can be built. This leads to the new challenge to select the shape and area of the farm, out of a larger region, to maximize its profitability. We introduce this as the wind farm area selection problem and present a novel optimization framework to efficiently solve it. Specifically, our framework combines three scales of design: (i) on a macro-scale, choosing the approximate location of the farm out of larger regions, (ii) on a meso-scale, generating the optimal shape of the farm, and (iii) on a micro-scale, choosing the exact position of the turbines within the shape. In particular, we propose a new constructive heuristic to choose the best shape of a farm at the meso-scale, which is scarcely studied in literature. Moreover, while macro and micro-scales have already been investigated, our framework is the first to integrate them. We perform a detailed computational analysis using real-life data and constraints from the recent UK Round-4 tender. Compared to the best rectangular-shaped farm at the same location, our results show that optimizing the shape increases profitability by 1.2% on average and up to 2.9%, corresponding to 50 and 112 million Euro respectively.