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Probabilistic Method for Optimizing the Number and Timing of Substation Spare Transformers

机译:变电站备用变压器数量和时序优化的概率方法

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This paper proposes a new probabilistic method based on chronological Monte Carlo simulation for computing optimal distribution substation spare transformers. The method allows the representation of events such as aging process, load growth, and other conditions not supported by traditional methods based on Poisson and Markov processes. The lifetimes of the transformers are represented by discrete probability distributions, determined by an algorithm that combines the aging of the insulating material, estimated by Arrhenius theory, with the loss of life caused by short-circuits, lightning and switching surges. To illustrate the importance of sizing the inventory based on reliability indices and costs, the proposed method is applied to a group of substations with 177 transformers of 138–13.8 kV, with power rating of 25 MVA. Finally, the proposed methodology is used in combination with a metaheuristic algorithm for determining the optimal timing strategy for composing of the stock of spare transformers over a pre-established planning horizon.
机译:本文提出了一种基于时间蒙特卡罗模拟的概率方法,用于计算最优配电变电站的备用变压器。该方法允许表示事件,例如老化过程,负载增长以及基于Poisson和Markov过程的传统方法不支持的其他条件。变压器的寿命由离散概率分布表示,该离散概率分布由一种算法确定,该算法结合了Arrhenius理论估计的绝缘材料的老化与短路,雷电和开关浪涌导致的寿命损失。为了说明根据可靠性指标和成本确定清单大小的重要性,该方法被应用于一组177个138-13.8 kV变压器,额定功率为25 MVA的变电站。最后,所提出的方法与元启发式算法结合使用,以确定在预定的规划范围内组成备用变压器库存的最佳定时策略。

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