Multi-scale design optimization of modern offshore wind farms

Abstract

The traditional optimization of the layout of a wind farm consisted in arranging the wind 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 wind farm can be built. This leads to the new challenge to select the shape and area of the wind farm, out of a larger region, to maximize its profitability. We introduce this problem 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 wind farm out of larger regions, (ii) on a meso-scale, generating the optimal shape of the wind 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 wind 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 wind 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.