Knowledge Management Subsystem of the Intellectual Situational Center

Симанков, Владимир Сергеевич; Buchatskiy, Pavel Yu.; Teploukhov, Semen V.; Buchatskaya, Victoria V.

doi:10.1109/itqmis56172.2022.9976535

Cited by 2 publications

(1 citation statement)

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“…Various types of models were identified, from the simplest ones, which allow calculating solar radiation under conditions of an absent region, to more complex ones, which allow taking into account such factors as atmospheric turbidity. The use of these models is a prerequisite for the implementation of a forecasting subsystem [Simankov et al, 2021a[Simankov et al, , 2022 as part of a general information-analytical system for assessing renewable energy [Simankov et al, 2021b] which allows assessing the efficiency of RES for a certain level of terrain scaling (local, regional). However, such a system should be based not only on classical models for assessing energy potential, but also on modern approaches based on methods of data mining and artificial intelligence, which results in improved forecasting accuracy and the ability to determine the required level of scaling of this subsystem.…”

Section: Resultsmentioning

confidence: 99%

Review of Models for Estimating and Predicting the Amount of Energy Produced by Solar Energy Systems

Simankov,

Buchatskiy,

Onishchenko

et al. 2023

Russian Journal of Earth Sciences

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Energy production based on renewable sources is a fundamental aspect of society’s sustainable development. The involvement of renewable energy sources in the implementation of modern energy systems can significantly reduce the amount of harmful emissions into the atmosphere and provide greater flexibility of energy infrastructure. The first step in determining the feasibility of involving a particular energy source in the overall energy system of the region is a preliminary assessment of the energy potential to determine the possible percentage of substitution of traditional energy. To solve this problem, it is necessary to use the models of energy supply, which are currently presented in a wide variety. In this regard, this paper proposes to consider various models for estimating the solar energy potential, which can be divided into empirical models and models based on the application of modern intelligent data analysis technologies. Such models are based on many different climatic and geographical indicators, such as: longitude of sunshine, ambient temperature, serial number of the day of the current year, amount of precipitation, average and maximum values of wind speed and so on. The paper analyzed the existing models for estimating the amount of energy, which can be used in the system designed to determine the most optimal configuration of the energy system based on the use of various conversion technologies most relevant to the case under study, and also serve as the basis for creating digital twins designed to model and optimize the operation of the projected energy complex

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Section: Resultsmentioning

confidence: 99%