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Risk assessment of stochastic spinning reserve of a wind-integrated multi-state generating system based on a cross-entropy method

机译:基于交叉熵方法的风电多状态发电系统随机旋转储备风险评估

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摘要

Challenges of unprecedented proportions face the electric power industry who takes on the responsibility for scheduling spinning reserve of a wind-integrated power system in an economical and reliable way. This study proposed a cross-entropy (CE) based simulation method to evaluate two indices of loss of load probability and expected demand not supplied, as well as the empirical distribution of demand not supplied. The triple together could be used for predictively sketching a full picture of spinning reserve inadequacy risk of a wind-integrated power system at an imminent operating time instance. The stochastic feature of the concerned multi-state system is modelled with a discrete-state continuous-time Markov process. Case studies based on the RTS-79 were carried out to illustrate the spinning reserve adequacy fluctuation given different present states of a rapid-start unit combined with or without considering the wind power penetration. Meanwhile, the advantage of the proposed CE simulation method over the exact convolution method and classical Monte Carlo simulation method in case of adequate spinning reserve is also demonstrated.
机译:电力行业面临着前所未有的挑战,电力行业担负着以经济,可靠的方式安排风力发电系统旋转储备的责任。这项研究提出了一种基于交叉熵(CE)的仿真方法,用于评估负载损失概率和未提供的预期需求的两个指标,以及未提供的需求的经验分布。三元组可以用于预测性地勾勒出在即将到来的运行时间情况下风力发电系统的旋转储备不足风险的全貌。用离散状态连续时间马尔可夫过程对相关多状态系统的随机特征进行建模。进行了基于RTS-79的案例研究,以说明在考虑或不考虑风能渗透的情况下,给定快速启动单元当前状态不同时纺丝储备充足性的波动。同时,还证明了在足够的纺丝储备情况下,所提出的CE模拟方法优于精确卷积方法和经典Monte Carlo模拟方法的优势。

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