时空相关风力发电对气电网络相互依赖运行的影响

Max Csef, Andrea Antenucci, G. Sansavini
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引用次数: 3

摘要

间歇性可再生能源(RES)的高渗透影响了以发电和需求平衡为任务的电厂的运行,并可能导致相互依赖的能源基础设施处于临界状态。在这篇文章中,从运行风险的角度对不同水平的风能整合进行了相互依赖的电力和天然气传输网络的评估。本文以英国天然气和电力输送网络为例进行了研究。提出了一种用于产生时空相关风速时间序列的d -藤联结法。与用自回归技术建立的多变量模型或单参数多维联结模型相比,藤联结模型在建模依赖关系方面具有很高的灵活性。当燃气发电厂(GFPPs)需要快速增加以补偿风力发电的相关波动时,可能会发生风力发电在天然气网络中运行约束违规的大量渗透,例如压力违规或压缩机关闭。结果表明,较大的风力发电斜坡下降率可能导致电网中较大的不服务能量(ENS)。对于高水平的风能整合,不利的上升和下降组合是一个现实的故障级联的起点,导致电网中高水平的需求得不到服务,以及天然气网络中的削减和组件故障。对燃气管网中易发生故障的部件进行了识别。
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Impact of spatio-temporally correlated wind generation on the interdependent operations of gas and electric networks
High penetrations of intermittent renewable energy sources (RES) affect the operations of power plants whose task is the balancing of generation and demand, and may induce critical states in interdependent energy infrastructures. In this contribution, the interdependent electric power and gas transmission networks are assessed under an operational risk perspective for different levels of wind energy integration. This investigation is exemplified with reference to a case study of the gas and electric transmission network of Great Britain (GB). A D-vine copula is developed for producing spatio-temporally correlated wind speed time series. In contrast to multivariate models built with autoregressive techniques or one-parameter multidimensional copulas which are restricted to modelling linear dependence or one type of dependence respectively, vine copulas offer high flexibility in modelling dependence. Due to large penetrations of wind power operational constraint violations in the gas network, e.g. pressure violations or compressor shut-downs, may occur when gas-fired power plants (GFPPs) need to ramp up quickly to compensate correlated fluctuations in wind generation. Results identify that large ramp-down rates of wind generation may cause large energy-not-served (ENS) in the electric network. For high levels of wind energy integration, unfavorable combinations of ramp-up and ramp-down are a realistic starting point of failure cascades leading to high levels of demand-not-served in the electric grid and curtailments and component failures in the gas network. Failure prone components in the gas network are identified.
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