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A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions

机译:在极端天气条件下遭受级联故障的输电电网可靠性/可用性评估的建模和仿真框架

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Electrical power transmission networks of many developed countries are undergoing deep transformations aimed at (i) facing the challenge offered by the stochastically fluctuating power contributions due to the continuously growing connections of renewable power generating units and (ii) decreasing their vulnerability to failures or malicious attacks and improving their resilience, in order to provide more reliable services, thus increasing both safety and profits. In this complex context, one of the major concerns is that related to the potentially catastrophic consequences of cascading failures triggered by rare and difficult to predict extreme weather events. In this work, we originally propose to combine an extreme weather stochastic model of literature to a realistic cascading failure simulator based on a direct current (DC) power flow approximation and a proportional re-dispatch strategy. The description of the dynamics of the network is completed by the introduction of a novel restoration model accounting for the operating conditions that a repair crew may encounter during an extreme weather event. The resulting model is solved by a customized sequential Monte Carlo scheme in order to quantify the impact of extreme weather events on the reliability/availability performances of the power grid. The approach is demonstrated with reference to the test case of the IEEE14 power transmission network. (C) 2016 Elsevier Ltd. All rights reserved.
机译:许多发达国家的电力传输网络正在经历着深刻的变革,其目的是:(i)面对由于可再生能源发电设备的连接不断增长而导致的电力供应随机波动所带来的挑战,以及(ii)降低其遭受故障或恶意攻击的脆弱性并提高其弹性,以提供更可靠的服务,从而提高安全性和利润。在这种复杂的情况下,主要关注点之一是与罕见的且难以预测的极端天气事件触发的级联故障的潜在灾难性后果有关。在这项工作中,我们最初建议将极端的天气随机模型与基于直流(DC)潮流近似和比例重新分配策略的实际级联故障模拟器相结合。通过引入一种新颖的恢复模型来完成网络动态的描述,该模型考虑了维修人员在极端天气事件中可能遇到的工作条件。通过定制的顺序蒙特卡洛方案解决了所得模型,以便量化极端天气事件对电网可靠性/可用性性能的影响。参考IEEE14功率传输网络的测试案例演示了该方法。 (C)2016 Elsevier Ltd.保留所有权利。

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