# Machine Learning in Electric Power Systems Adequacy Assessment Using Monte-Carlo Method

D.A. Boyarkin, D.S. Krupenev, D.V. IakubovskiiThe article considers the question of increasing the computational efficiency ofFull text

the procedure for electric power systems adequacy assessment using the Monte Carlo method.

In the framework of using this method, it is necessary to randomly generate a certain number

of system states. As it is known the speed and accuracy of the calculation depends on the number

of such states to be analyzed, so one of the ways to solve this problem is to reduce the this

number while observing the required accuracy of the estimate. For this purpose it is proposed

to use machine learning methods, whose task is to classify the calculated states of the electric

power system. During the experiment, the support vector machines method and the random forest

method were applied. The results of the calculations showed that these methods using allowed to

reduce the number of random states of the system to be analyzed, thereby reducing the total time

spent on calculations in general and proving the effectiveness of the proposed approach. Wherein

the best results were obtained while using the random forest method.

- Keywords
- electric power systems; adequacy assessment; Monte Carlo method; machine learning.
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