Abritta Ramon, Pavlov Alexey, Varagnolo Damiano, Tore Børresen Børre
Department of Geosciences, Norwegian University of Science and Technology, Trondheim, Trøndelag, 7031, Norway.
Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Trøndelag, 7034, Norway.
Open Res Eur. 2024 May 28;3:214. doi: 10.12688/openreseurope.16716.2. eCollection 2023.
The inter-array grid relates to a significant share of the investments into an offshore wind power plant (OWPP). Optimizing the cable connections regarding costs and reliability is a mathematically complex task due to the high variety of possible wind and component (wind turbine or cable) failure scenarios. This paper presents a novel mixed integer linear programming approach to support investment decisions into OWPPs by trading off cabling purchase and installation costs with power capacity risk (PCR), which is defined as a length-weighed cumulative power flow summation that reflects the consequences of cable failures. Then, quasi-random Monte Carlo simulations assess the optimized collection grids (CGs) to quantify their levelized cost of energy (LCOE). To construct relevant case studies, this work investigates the real OWPPs Ormonde, Horns Rev 1, Thanet, and London Array, which contain 30, 80, 100, and 175 wind turbines. The results reveal Pearson correlation coefficients around 0.99 between the proposed PCR and the expected energy not supplied. Furthermore, this paper's findings indicate that minimum-cost CGs do not necessarily present the lowest LCOE.
阵列间电网在海上风电场（OWPP）的投资中占很大比例。由于可能的风况和部件（风力涡轮机或电缆）故障场景种类繁多，在成本和可靠性方面优化电缆连接是一项数学上复杂的任务。本文提出了一种新颖的混合整数线性规划方法，通过权衡电缆采购和安装成本与功率容量风险（PCR）来支持对海上风电场的投资决策，功率容量风险定义为反映电缆故障后果的长度加权累积潮流总和。然后，通过准随机蒙特卡罗模拟评估优化后的集电网络（CG），以量化其平准化度电成本（LCOE）。为构建相关案例研究，本文研究了实际的海上风电场奥蒙德、霍恩斯礁1号、马盖特和伦敦阵列，它们分别包含30、80、100和175台风力涡轮机。结果显示，所提出的功率容量风险与未供应的预期能量之间的皮尔逊相关系数约为0.99。此外，本文的研究结果表明，成本最低的集电网络不一定具有最低的平准化度电成本。
