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The Markov Chain of Energy Carryover Reserves in Models of Power Supply Reliability in Remote

机译:偏远地区供电可靠性模型中的能量携带马尔可夫链

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We consider mathematical models for analyzing the energy supply reliability of isolated systems and propose a three-level complex of nested models. The lower level represents the model of functioning of the energy supply system during the period under review. The second level is a model of the energy supply reliability analysis. This analysis is based on multiple simulations of functioning of the energy supply system in randomly formed conditions. The energy sources demand and supply, as well as the amount of carryover reserves of energy in storage, are assumed to be random values. To simulate functioning, the values of energy demand and production are formed using the Monto-Carlo method following their laws of probability. The random value of the carryover reserves is formed using the algorithm that generates the Markov sequence of these reserves. The upper level is represented by the model for selecting the optimal composition of the means ensuring reliability, i.e. energy reserves in the energy production and storage capacity. It was revealed that the algorithm for generating the random value of the energy sources carryover reserves yields the homogenous Markov sequence. Sufficient conditions for uniqueness of the stationary state were determined. Based on the experimental calculations, we estimated the number of iterations required to reach the stationary ergodic state.
机译:我们考虑数学模型来分析隔离系统的能源供应可靠性,并提出了三层嵌套模型。较低的水平代表了本报告所述期间能源供应系统的功能模型。第二级是能源供应可靠性分析的模型。该分析基于随机形成条件下能源供应系统功能的多种模拟。能源需求和供应以及存储的结转能源量被假定为随机值。为了模拟功能,使用蒙托-卡洛方法遵循其概率定律来形成能量需求和生产的值。结转储备金的随机值是使用生成这些储备金的马尔可夫序列的算法形成的。上级由用于选择确保可靠性的装置的最佳组成的模型表示,即在能量生产和存储容量中的能量储备。结果表明,产生能源结转储备量随机值的算法产生了均匀的马尔可夫序列。确定了固定状态唯一性的充分条件。根据实验计算,我们估算了达到稳态遍历状态所需的迭代次数。

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