基于年风分布不确定集的风电场布局优化

Ying Wen, Mengxuan Song, Jun Wang
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引用次数: 0

摘要

提出了一种不确定风力条件下风电场年发电量最大化的鲁棒布局优化方法。提出了一种基于年风分布变异性的描述风分布不确定集的新方法。假定未来的风况在不确定性范围内变化。以未来可能的最低年发电量为目标函数。优化问题采用线性规划和遗传算法求解。鲁棒优化布局降低了能源生产的不确定性和可变性,并通过不确定性集的合理构造补偿了鲁棒性成本,从而减少了能源生产的损失。并与不同的优化策略进行了比较。仿真结果表明,所提出的优化方法能够在限制不确定风的影响和最大化总体发电量之间实现平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wind-Farm Layout Optimization based on Uncertain Set of Yearly Wind Distributions
This paper proposes a robust layout optimization method for maximizing the annual energy production of a wind farm under uncertain wind conditions. A novel method for describing the uncertainty set of wind distribution is proposed based on the variability of yearly wind distributions. Future wind conditions are assumed to vary within the uncertainty set. The lowest possible annual energy production in the future is set as the objective function. The optimization problem is solved by linear programming and genetic algorithms. The uncertainty and variability of energy production is reduced with the robust optimal layout and loss of energy production as the cost of robustness is compensated by the proper construction of uncertainty set. The proposed optimization method is compared with different optimization strategies. The simulation results demonstrate that the proposed optimization method can achieve a trade-off between limiting the influence of uncertain wind and maximizing overall energy production.
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