Models, systems, networks in economics, engineering, nature and society
Background. The aim of the research is to reduce electricity losses in the power system of railway transport. Losses are defined as the imbalance between the supplied and consumed electricity recorded by means of commercial electricity metering. At the moment, there are no technical and software too...
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| Format: | Article |
| Language: | English |
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Penza State University Publishing House
2024-11-01
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| Series: | Модели, системы, сети в экономике, технике, природе и обществе |
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| author | D.N. Frantasov Yu.V. Kudryashova E.V. Voronina |
| author_facet | D.N. Frantasov Yu.V. Kudryashova E.V. Voronina |
| author_sort | D.N. Frantasov |
| collection | DOAJ |
| description | Background. The aim of the research is to reduce electricity losses in the power system of railway transport. Losses are defined as the imbalance between the supplied and consumed electricity recorded by means of commercial electricity metering. At the moment, there are no technical and software tools for analyzing the losses structure and causes of their occurrence. Materials and methods. To achieve this goal the main factors that lead to a significant increase in electricity losses have been identified. The factors for all automated systems for commercial metering of electricity used in railway transport have been determined. Results. A block diagram of an information and measurement system for metering electricity losses has been developed, which allows using the equipment in operation without replacing or modernizing, which contributes to getting new technical capabilities. A method is proposed for the intellectualization of the process of classification of factors causing the growth of unnormalized energy losses, based on artificial neural networks. Conclusions. The intelligent unit allows you to replace the person who makes organizational and technical decisions to minimize the consequences of emergency situations leading to an increase in non-standardized losses. This solution is applicable in departments without qualified specialists. The results of training an artificial neural network are considered, the main parameters of the efficiency of the information and measurement system for recording losses at a real object of railway transport are determined. |
| format | Article |
| id | doaj-art-b7af76b0924b457f8b9cfbbb52702682 |
| institution | Kabale University |
| issn | 2227-8486 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Penza State University Publishing House |
| record_format | Article |
| series | Модели, системы, сети в экономике, технике, природе и обществе |
| spelling | doaj-art-b7af76b0924b457f8b9cfbbb527026822025-01-30T12:28:38ZengPenza State University Publishing HouseМодели, системы, сети в экономике, технике, природе и обществе2227-84862024-11-01311612510.21685/2227-8486-2024-3-10Models, systems, networks in economics, engineering, nature and societyD.N. Frantasov0Yu.V. Kudryashova1E.V. Voronina2Samara State University of EconomicsVolga State University of Railway TransportSamara State University of EconomicsBackground. The aim of the research is to reduce electricity losses in the power system of railway transport. Losses are defined as the imbalance between the supplied and consumed electricity recorded by means of commercial electricity metering. At the moment, there are no technical and software tools for analyzing the losses structure and causes of their occurrence. Materials and methods. To achieve this goal the main factors that lead to a significant increase in electricity losses have been identified. The factors for all automated systems for commercial metering of electricity used in railway transport have been determined. Results. A block diagram of an information and measurement system for metering electricity losses has been developed, which allows using the equipment in operation without replacing or modernizing, which contributes to getting new technical capabilities. A method is proposed for the intellectualization of the process of classification of factors causing the growth of unnormalized energy losses, based on artificial neural networks. Conclusions. The intelligent unit allows you to replace the person who makes organizational and technical decisions to minimize the consequences of emergency situations leading to an increase in non-standardized losses. This solution is applicable in departments without qualified specialists. The results of training an artificial neural network are considered, the main parameters of the efficiency of the information and measurement system for recording losses at a real object of railway transport are determined.power lossespower imbalancesmart power systemsartificial neural networks |
| spellingShingle | D.N. Frantasov Yu.V. Kudryashova E.V. Voronina Models, systems, networks in economics, engineering, nature and society Модели, системы, сети в экономике, технике, природе и обществе power losses power imbalance smart power systems artificial neural networks |
| title | Models, systems, networks in economics, engineering, nature and society |
| title_full | Models, systems, networks in economics, engineering, nature and society |
| title_fullStr | Models, systems, networks in economics, engineering, nature and society |
| title_full_unstemmed | Models, systems, networks in economics, engineering, nature and society |
| title_short | Models, systems, networks in economics, engineering, nature and society |
| title_sort | models systems networks in economics engineering nature and society |
| topic | power losses power imbalance smart power systems artificial neural networks |
| work_keys_str_mv | AT dnfrantasov modelssystemsnetworksineconomicsengineeringnatureandsociety AT yuvkudryashova modelssystemsnetworksineconomicsengineeringnatureandsociety AT evvoronina modelssystemsnetworksineconomicsengineeringnatureandsociety |