Modeling of electricity consumption in the systems with smart equipment

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Modeling of electricity consumption in the systems with smart equipment

Danilov K., Барахнин В. Б.

Big data is the foundation of modern energy management systems. There are two energy consumption models where systems are one of the consumers with intelligent equipment: static and dynamic. The dynamic model uses a two-tariff closed-loop accounting scheme, which implies changes in tariffs based on the analysis of current consumption. The results of an experimental study of both models using energy consumption data are presented. The influence of the number of such devices on the possibility of achieving uniform consumption when using the second model is shown. Usage of machine learning for generation a consumption forecast based on time series is shown

Language: English

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INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS 2021 SPECIAL INTEREST GROUP ON BIG DATA PROCEEDINGS

[б.и.], 2022.

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Temirkhanov A., Костромина А. М., Цымбой О. А. et al., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2025 Т. 527 № S С. 485–494

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Pankratova Y., Trofimova I., Firyago U. et al., Lecture Notes in Networks and Systems 2023 Vol. 596 P. 277–287

In this paper, models for forecasting the dynamics of demand for products with a short expiration date are constructed. Here we propose to construct models for time series forecasting using the decomposition method and taking into account the assumptions of experts about the influence of certain factors on the behavior of product consumers. These models ...

Added: March 20, 2024

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Bufalo M., Orlando G., Tourism Review 2024 Vol. 79 No. 2 P. 445–464

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a ...

Added: February 16, 2024

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Sizykh N., Orshanskaya E., Sizykh D., , in: 2022 15th International Conference Management of large-scale system development (MLSD).: M.: IEEE, 2022. P. 1–6.

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Added: November 14, 2022

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Danilov K., Maltseva S. V., , in: 2021 IEEE 23rd Conference on Business Informatics.: IEEE, 2021.

Added: June 13, 2022

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

Moiseev N., Sorokin A., Zvezdina N. et al., Mathematics 2021 No. 9(19) Article 2423

The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period. In this paper, a new method of dealing with ...

Added: October 1, 2021

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Petrovskiy M., Korolev V., Korchagin A. et al., Programming and Computer Software 2018 Vol. 44 No. 5 P. 353–362

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Меланко А. Г., Аудит и финансовый анализ 2016 № 6 С. 337–346

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Added: March 12, 2017