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An Efficient Method Based on Adaptive Time Resolution for the Unit Commitment Problem

机译:基于单位承诺问题的自适应时间分辨率的一种有效方法

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Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1%.
机译:单位承诺(UC)是一个计算密集型问题,这在前面的日期调度和单个方案模拟中已经足够好了。然而,由于在保留间隔间约束的同时,引入可再生能源和存储在计算时间内暴露了计算时间的新挑战。为了解决这个问题,我们介绍了一种具有自适应时间分辨率的新方法,可以提高仿真速度并保持精度。我们通过将连续的时间间隔分组具有类似的净需求水平来减少问题的大小,形成一个新的更长的间隔。与传统的UC解决方案相比,所提出的方法是计算地更有效的,因为它避免了类似间隔的重复优化。我们使用6公交车分析解决方案的质量,以及IEEE 118总线测试系统作为两个案例研究。数值结果表明,可以在计算速度下具有显着的增益,特别是对于更困难的IEEE 118-母线壳体来获得高质量的解决方案,其最大误差小于±1%。

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