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首页> 外文期刊>Applied Energy >Decentralized wind uncertainty management: Alternating direction method of multipliers based distributionally-robust chance constrained optimal power flow
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Decentralized wind uncertainty management: Alternating direction method of multipliers based distributionally-robust chance constrained optimal power flow

机译：分散风的不确定性管理：基于分布鲁棒机会约束的最优潮流的乘子交替方向方法

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摘要

How to manage wind power uncertainty in system operation is an urgent and important issue, especially under substantially increasing penetration levels of wind generation in electric power systems. With increasing numbers of wind power plants (WPPs) integrated into power systems, their variability and uncertain power outputs become a challenge to maintaining system reliability. Traditional stochastic optimization-based models face the curse of dimensionality when the number of WPPs increases. This paper proposes a novel decentralized wind power uncertainty management model. In this model, conventional generators optimize their power capacity output and their participation to mitigate wind power uncertainty locally with only limited information exchange with the system operators. First, a distributionally-robust chance-constrained optimal power flow (DRCC-OPF) model is deployed to schedule the generation and reserve considering the wind power forecast uncertainty. Then, the alternating direction method of multipliers (ADMM) is used to reformulate the DRCC-OPF model into the distributed optimization model for each conventional generator and WPP. The tests on a small PJM 5-bus system and the IEEE 118-bus system demonstrate that the proposed decentralized model can increase the operation reliability without sacrificing system operating cost, especially when the wind power penetration levels are high. Using the proposed model, the optimal solutions can be obtained within one minute, for all studied cases, which verifies the computation efficiency of the proposed decentralized model. Furthermore, considering a large number of WPPs integrated into the system, the proposed decentralized method obtains a lower operating cost within one minute which demonstrates its efficiency to deal with high dimension of uncertainties.
机译：在系统运行中如何管理风力发电不确定性是一个紧迫而重要的问题，尤其是在风力发电在电力系统中的渗透率大大提高的情况下。随着越来越多的风电厂（WPP）集成到电力系统中，其可变性和不确定的功率输出成为维持系统可靠性的挑战。当WPP数量增加时，基于传统随机优化的模型将面临维度的诅咒。本文提出了一种新型的分散式风电不确定性管理模型。在该模型中，常规发电机优化了其功率输出和参与度，从而仅通过与系统运营商有限的信息交换就可以减轻本地的风力不确定性。首先，考虑风电预测的不确定性，采用分布稳健的机会受限的最优潮流（DRCC-OPF）模型来调度发电和储备。然后，使用乘数交替方向方法（ADMM）将DRCC-OPF模型重新构建为每个常规发电机和WPP的分布式优化模型。在小型PJM 5总线系统和IEEE 118总线系统上进行的测试表明，所提出的分散模型可以在不牺牲系统运行成本的情况下提高运行可靠性，尤其是在风电普及率较高的情况下。使用所提出的模型，对于所有研究案例，可以在一分钟之内获得最优解，从而验证了所提出的分散模型的计算效率。此外，考虑到将大量WPP集成到系统中，所提出的分散方法在一分钟内获得了较低的运营成本，这证明了其在处理高不确定性方面的效率。

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