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arXiv 2103.12246eess.SYcs.SY
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气电系统不确定性管理的随机混合逼近

Stochastic Hybrid Approximation for Uncertainty Management in Gas-Electric Systems

Conor O' Malley, Gabriela Hug, Line Roald

摘要:

燃气发电机具有快速增加和减少发电量的能力,在管理可再生能源变化方面发挥着重要作用。然而,电力生产的这些变化转化为天然气消费的变化,并将不确定性从电网传播到天然气系统。为了确保这两个系统安全运行,电力和天然气网络之间越来越需要协调和不确定性管理。这种协调的一个具有挑战性的方面是考虑天然气动力学,这在感兴趣的时间尺度上起着重要作用,但产生了一组非线性和非凸方程,即使在确定性的情况下也难以优化。许多传统的随机优化方法不能使用,因为它们要么直接包含大量的场景,要么要求底层问题是凸的。为了解决这些挑战,我们提出使用随机混合近似算法来更有效地解决这些问题,并研究了该算法的几种不同变体。在一个案例研究中,我们证明了所提出的技术能够快速获得高质量的解决方案,并优于现有的基准,如广义弯曲分解。我们表明,协调的不确定性管理,占天然气系统可以显着减少电力和天然气系统负荷下降的压力条件。

英文摘要:

Gas-fired generators, with their ability to quickly ramp up and down their electricity production, play an important role in managing renewable energy variability. However, these changes in electricity production translate into variability in the consumption of natural gas, and propagate uncertainty from the electric grid to the natural gas system. To ensure that both systems are operating safely, there is an increasing need for coordination and uncertainty management among the electricity and gas networks. A challenging aspect of this coordination is the consideration of natural gas dynamics, which play an important role at the time scale of interest, but give rise to a set of non-linear and non-convex equations that are hard to optimize over even in the deterministic case. Many conventional methods for stochastic optimization cannot be used because they either incorporate a large number of scenarios directly or require the underlying problem to be convex. To address these challenges, we propose using a Stochastic Hybrid Approximation algorithm to more efficiently solve these problems and investigate several different variants of this algorithm. In a case study, we demonstrate that the proposed technique is able to quickly obtain high quality solutions and outperforms existing benchmarks such as Generalized Benders Decomposition. We demonstrate that coordinated uncertainty management that accounts for the gas system can significantly reduce both electric and gas system load shed in stressed conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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