Forecasting consumption of electric energy by using wavelet transform
Forecasting electricity consumption is an urgent task for generating companies, since it is currently impossible to accumulate electricity on an industrial scale. Also, the forecast is necessary for consumers to carry out technical work and other activities. The purpose of this work is to make...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Omsk State Technical University, Federal State Autonoumos Educational Institution of Higher Education
2021-06-01
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| Series: | Омский научный вестник |
| Subjects: | |
| Online Access: | https://www.omgtu.ru/general_information/media_omgtu/journal_of_omsk_research_journal/files/arhiv/2021/%E2%84%96%203%20(177)%20(%D0%9E%D0%9D%D0%92)/75-78%20%D0%A1%D0%BA%D0%BE%D1%80%D0%BE%D1%85%D0%BE%D0%B4%D0%BE%D0%B2%20%D0%92.%20%D0%98.,%20%D0%9B%D1%8B%D1%81%D0%B5%D0%BD%D0%BA%D0%BE%20%D0%9E.%20%D0%90.,%20%D0%A1%D0%B8%D0%BC%D0%B0%D0%BA%D0%BE%D0%B2%20%D0%90.%20%D0%92.%20%D0%B8%20%D0%B4%D1%80..pdf |
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| Summary: | Forecasting electricity consumption is an urgent task for
generating companies, since it is currently impossible
to accumulate electricity on an industrial scale. Also,
the forecast is necessary for consumers to carry out
technical work and other activities. The purpose of this
work is to make a forecast of electric energy consumption
using the wavelet transform, and to select the optimal
wavelet function for forecasting. Data for forecasting is
a schedule of the load of the shop, which plays the role
of a household room, warehouse, as well as a working
office for personnel who service electrical installations at
a production enterprise. Based on the results of the work,
the optimal wavelet function is selected. The result of the
work is a representation of the trend of electric energy
consumption by the object under consideration, i.e. a
forecast presented in the form of a graph, and a detailed
component of the projected consumption is obtained,
which in theory is justified as interference and sharply
variable nature of electricity consumption. |
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| ISSN: | 1813-8225 2541-7541 |