Abstract

This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-term strategic uncertainty and short-term operational uncertainty in a single optimization model. The model supports wind farm owners in making strategic decisions regarding the number, placement, charter length, and types of vessels to charter, to meet maintenance demands throughout the lifetime of a wind farm. To evaluate the quality of strategic fleet size and mix decisions, the model also considers the operational decisions of how to utilize the fleet to support maintenance operations. The model accounts for strategic uncertainties that have not been considered in previously developed optimization models for offshore wind, such as uncertainty related to long-term trends in electricity prices and subsidy levels, the stepwise development of wind farms, and technology development in the vessel industry. To solve the proposed stochastic programming model we have developed an ad hoc integer L-shaped method, with customized optimality cuts. The computational experiments show that the proposed method outperforms solving the deterministic equivalent using a commercial MIP solver.

摘要

本文研究了寻找成本最优的船队以支持海上风电场维护操作的战略问题。制定了双级随机模型，在单个优化模型中同时考虑了长期战略不确定性和短期运营不确定性。该模型支持风电场业主就数量、位置、租船长度和租船类型做出战略决策，以满足风电场整个生命周期内的维护需求。为了评估战略车队规模和组合决策的质量，该模型还考虑了如何利用车队来支持维护运营的运营决策。该模型考虑了先前开发的海上风电优化模型中未考虑的战略不确定性，例如与电价和补贴水平的长期趋势、风电场的逐步发展以及船舶行业的技术发展相关的不确定性。为了解决所提出的随机规划模型，我们开发了一种特殊的整数 L 形方法，具有定制的最优切割。计算实验表明，所提出的方法优于使用商业 MIP 求解器求解确定性等价物。