![]() Secondly, it explains a method to speed up the annual energy production, allowing the algorithm to optimize the wind farm site and layout within an unlimited space, with unlimited number of turbines, and considering seabed characteristics, depth and cable prices.įinally, it presents a multi-objective optimization algorithm based on Pareto fronts. First, it introduces an innovative method of assessing the visual impact of an offshore wind farm, integrated in a optimization algorithm. Three are the main contributions of this paper. Unfortunately, there is a lack of objective indicators to quantify it. Optimization algorithms must consider the techno-economic aspect, but also the expected visual impact. However, and despite of their usual good social acceptance, wind farms must overcome the displeasure of some neighbouring residents, mainly due to the natural landscape alteration. ![]() The investment profitability is the strongest economic driver when deciding the location, and optimizing the orientation and layout of a wind power plant. In conclusion, the proposed multi-objective optimization framework represents a mind shift in design tools for OWFs which allows cost savings in the design and operation phases. OWFs with similar energy production and investment cost as layouts designed with standard sequential strategies were obtained through the framework, meaning that the proposed framework has the capability to create different OWF layouts that would have been missed by the designers. A wide range of OWF layouts were obtained through the optimization framework. The proposed framework was applied to the Dutch Borssele areas I and II. Furthermore, the proposed framework is independent of economic assumptions, meaning that no a priori values such as the interest rate or energy price, are needed. The proposed framework optimizes simultaneously different goals (e.g., annual energy delivered and investment cost) which leads to efficient trade-offs during the design phase, e.g., reduction of wake losses vs collection system length. This article presents a framework to integrate, automate and optimize the design of OWF layouts and the respective electrical infrastructures. ![]() Current offshore wind farms (OWFs) design processes are based on a sequential approach which does not guarantee system optimality because it oversimplifies the problem by discarding important interdependencies between design aspects. ![]()
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