Оригинал (Original)
Автори: В. Б., Андреев, О. Д., Ценов, Г. Ц.
Заглавие: СЪЗДАВАНЕ НА ПРОФИЛ ЗА ДНЕВНАТА ЕЛЕКТРИЧЕСКА КОНСУМАЦИЯ НА ПРЕДПРИЯТИЯ С ИЗПОЛЗВАНЕ НА НЕВРОННИ МРЕЖИ
Ключови думи: time series, forecasts, electric loads, neural networks, plant optimization

Абстракт: In the modern free electricity market, the successful electricity consumption forecasting of is important aspect in the optimization of the production activity and the production plan costs. The forecasting of electrical loads can be done daily or hourly using the methods of artificial intelligence for training and setting up a forecasting module, which can be set up with data accumulated on the basis of reports of consumed electricity in short periods of time. These forecasts would be used in the formation of electricity prices in the interstate markets for the purchase / sale of electricity. This article presents the results for creating an energy user profile of an plant, by implementing forecasts of the electrical loads, presented as time series using the neural network package from Neural Networks Toolbox in the MATLAB when capturing data on current consumption at 15 minute time intervals.

Библиография

  1. Правила за управление на електроразпределителните мрежи, Издадени от ДКЕВР Приложение към т. 1 на Решение № П-6 от 18 юни 2007 г., Обн. ДВ. бр.66 от 14 Август 2007г.
  2. Младенов В., Йорданова С., 2006, Размито управление и невронни мрежи, София, ТУ-София
  3. Ценов.Г, Петрова Р., Младенов В., Йорданова С., 2008, Размито управление и невронни мрежи, София, ТУ-София
  4. Danilo Bassi, Oscar Olivares, 2006, Medium Term Electric Load Forecasting Using TLFN Neural Networks, International Journal of Computers, Communications & Control, том 1/2, стр. стр. 23-32

Издание

XIII МЕЖДУНАРОДНА НАУЧНА КОНФЕРЕНЦИЯ „Е-управление и Е-комуникации”, 26-28 юни 2021 г., том 1, стр. стр. 167-174, 2021, България, Созопол, ТУ-София, ISBN ISSN 2534-8523

Пълен текст на публикацията

Autors: Tsenova, V. B., Andreev, O. D., Tsenov, G. T.
Title: Generation of Plant Electric Consumption Profile with Use of Neural Networks
Keywords: time series, forecasts, electric loads, neural networks, plant optimization

Abstract: In the modern free electricity market, the successful electricity consumption forecasting of is important aspect in the optimization of the production activity and the production plan costs. The forecasting of electrical loads can be done daily or hourly using the methods of artificial intelligence for training and setting up a forecasting module, which can be set up with data accumulated on the basis of reports of consumed electricity in short periods of time. These forecasts would be used in the formation of electricity prices in the interstate markets for the purchase / sale of electricity. This article presents the results for creating an energy user profile of an plant, by implementing forecasts of the electrical loads, presented as time series using the neural network package from Neural Networks Toolbox in the MATLAB when capturing data on current consumption at 15 minute time intervals.

References

  1. Правила за управление на електроразпределителните мрежи, Издадени от ДКЕВР Приложение към т. 1 на Решение № П-6 от 18 юни 2007 г., Обн. ДВ. бр.66 от 14 Август 2007г.
  2. Младенов В., Йорданова С., 2006, Размито управление и невронни мрежи, София, ТУ-София
  3. Ценов.Г, Петрова Р., Младенов В., Йорданова С., 2008, Размито управление и невронни мрежи, София, ТУ-София
  4. Danilo Bassi, Oscar Olivares, 2006, Medium Term Electric Load Forecasting Using TLFN Neural Networks, International Journal of Computers, Communications & Control, том 1/2, стр. стр. 23-32

Issue

XIII-th INTERNATIONAL SCIENTIFIC CONFERENCE “E-Governance and E-Communications” 26-28 June, 2021, vol. 1, pp. 167-174, 2021, Bulgaria, Sozopol, TU-Sofia, ISBN ISSN 2534-8523

Full text of the publication

Вид: публикация в международен форум