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Generation/transmission power system reliability evaluation by Monte-Carlo simulation assuming a fuzzy load description

机译:假设负荷描述模糊的蒙特卡洛模拟发电/输电系统可靠性评估

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This paper presents a Monte-Carlo algorithm considering loads defined by fuzzy numbers. In this methodology states are sampled according to the probabilistic models governing the life cycle of system components while fuzzy concepts are used to model uncertainty related to future load behavior. This model can be used to evaluate generation/transmission power system reliability for long term planning studies as one uses the more adequate uncertainty models for each type of data. For each sampled state a fuzzy optimal power flow is run so that one builds its power nor supplied membership function. The paper proposes new indices reflecting the integration of probabilistic models and fuzzy concepts and discusses the application of variance reduction techniques if loads are defined by fuzzy numbers. A case-study based on the IEEE 30 bus system illustrates this methodology.
机译:本文提出了一种考虑模糊数定义的载荷的蒙特卡洛算法。在这种方法中,根据控制系统组件生命周期的概率模型对状态进行采样,而模糊概念则用于对与未来负载行为有关的不确定性进行建模。该模型可用于评估长期计划研究中的发电/输电系统可靠性,因为对于每种类型的数据都使用更充分的不确定性模型。对于每个采样状态,都会运行一个模糊的最佳功率流,以便建立其功率或提供的隶属函数。本文提出了反映概率模型和模糊概念整合的新指标,并讨论了当负荷由模糊数定义时方差减少技术的应用。基于IEEE 30总线系统的案例研究说明了该方法。

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