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In the article, based on statistics on emergency outages in the Levoberezhniy and Pravoberezhniy districts of Irkutsk and the sums of average daily temperatures in years 2010-2017 regression models are built. As an auxiliary factor for the models built on values that were grouped by year, the seasonality index was calculated using the “Kassandra” model. In the model, built for values that were grouped by month, a trend was added in addition to the seasonal component. A retrospective prediction of emergency outages based on the data of the Levoberezhniy district, gathered in April 2020 showed that a model with a trend and a seasonal component gives a more accurate prediction. Since the sum of the average daily temperatures can be considered a random variable, the proposed factor models can be used to predict emergency outages only with some probability. The solution of inverse problems, when the factor value is determined for a given number of emergency outages, can be used to assess the risks associated with the influence of low and high temperatures on the objects of the electric grid complex.

The paper identifies information that takes into account the heterogeneity of agricultural land on the basis of the use of a precision farming system and geographic information technologies. The tasks of optimizing the production of agricultural products are formulated, describing the heterogeneity of land resources, for averaged and extreme weather and climatic conditions. These models are implemented for an agricultural enterprise in the Irkutsk region. Two variants of the problem are considered: with deterministic and stochastic parameters. As a random variable, the problem uses the crop yield corresponding to the probability of a drought that occurred in the region in 2015. According to the calculations, the use of various technologies of precision farming, taking into account the heterogeneity of arable land, makes it possible to increase the income of the enterprise, reducing the dispersion of the coefficients included in the optimization model agricultural production. At the same time, it is possible to reduce the risks associated with extreme hydrometeorological events, in particular, with drought

The article considers the using intelligent controls possibility in low-voltage rural electric networks to minimize the unbalance modes consequences. The proposed technology includes the digital data transmission compilation on the electrical energy parameters with a new balancing technical means the electrical network operating mode. Digital feedback is provided for changes the balancing device (BD) parameters by the unbalancing power consumption changing level. Based on the developed methods compilation, software for calculating unbalancing modes has been created, which makes it possible to assess the currents and voltages unbalancing effect on the power quality and its additional losses change. The “green” technology proposed version, which increases the economic and the electric energy environmental safety use in the rural electric power industry, contains a new constructive solution for the balancing device implementation. The proposed technology was tested on the measurement data basis in existing electrical networks. Based on the MALAB technologies use, changes studied indicators visualization in the before and after BD integration in the electrical network was carried out and its analysis was makes. Used on the “neural networks” MALAB technology, a preventive assessment of the unbalancing power consumption events development in the investigated operating electrical network is presented, as well as the proposed technology effectiveness assessment was carried out.

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