Analysis of modern approaches for the prediction of electric energy consumption
A review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy system...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2020-04-01
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| Series: | Open Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/eng-2020-0028 |
| _version_ | 1819139196062793728 |
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| author | Kalimoldayev Maksat Drozdenko Aleksey Koplyk Igor Marinich T. Abdildayeva Assel Zhukabayeva Tamara |
| author_facet | Kalimoldayev Maksat Drozdenko Aleksey Koplyk Igor Marinich T. Abdildayeva Assel Zhukabayeva Tamara |
| author_sort | Kalimoldayev Maksat |
| collection | DOAJ |
| description | A review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy systems of Ukraine and Kazakhstan,are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed. |
| first_indexed | 2024-12-22T11:18:49Z |
| format | Article |
| id | doaj.art-58b994f287364a71936c5c7fef7ed245 |
| institution | Directory Open Access Journal |
| issn | 2391-5439 |
| language | English |
| last_indexed | 2024-12-22T11:18:49Z |
| publishDate | 2020-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Engineering |
| spelling | doaj.art-58b994f287364a71936c5c7fef7ed2452022-12-21T18:27:55ZengDe GruyterOpen Engineering2391-54392020-04-0110135036110.1515/eng-2020-0028eng-2020-0028Analysis of modern approaches for the prediction of electric energy consumptionKalimoldayev Maksat0Drozdenko Aleksey1Koplyk Igor2Marinich T.3Abdildayeva Assel4Zhukabayeva Tamara5Institute of Information and Computational Technologies of the Cabinet of Sciences of the Ministry of Education and Science of Kazakhstan, AstanaKazakhstanSumy State University, SumyUkraineSumy State University, SumyUkraineSumy State University, SumyUkraineInstitute of Information and Computational Technologies of the Cabinet of Sciences of the Ministry of Education and Science of Kazakhstan,Department of Information Technologies, L.N. Gumilyov Eurasian National University, 010008, Astana, KazakhstanInstitute of Information and Computational Technologies of the Cabinet of Sciences of the Ministry of Education and Science of Kazakhstan,Department of Information Technologies, L.N. Gumilyov Eurasian National University, 010008, Astana, KazakhstanA review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy systems of Ukraine and Kazakhstan,are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed.https://doi.org/10.1515/eng-2020-0028predictionpower consumptionpanel modelsautoregression modelsneural networks |
| spellingShingle | Kalimoldayev Maksat Drozdenko Aleksey Koplyk Igor Marinich T. Abdildayeva Assel Zhukabayeva Tamara Analysis of modern approaches for the prediction of electric energy consumption Open Engineering prediction power consumption panel models autoregression models neural networks |
| title | Analysis of modern approaches for the prediction of electric energy consumption |
| title_full | Analysis of modern approaches for the prediction of electric energy consumption |
| title_fullStr | Analysis of modern approaches for the prediction of electric energy consumption |
| title_full_unstemmed | Analysis of modern approaches for the prediction of electric energy consumption |
| title_short | Analysis of modern approaches for the prediction of electric energy consumption |
| title_sort | analysis of modern approaches for the prediction of electric energy consumption |
| topic | prediction power consumption panel models autoregression models neural networks |
| url | https://doi.org/10.1515/eng-2020-0028 |
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