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Tytuł artykułu

Energy consumption monitoring system and energy data processing tools

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
It is determined that monitoring system of energy consumption at the enterprises in Lviv region should provide the implementation of the following tasks: energy data collection on a real-time basis; integration and processing of information resources justifying energy consumption at both enterprise and regional levels; communication between regional authorities and entrepreneurs; quick access of regional authorities to the latest information on energy consumption; analysis of energy consumption dynamics, structure and industrial energy efficiency; short-term and medium-term predictions of energy consumption and energy efficiency of regional economy; daily energy audit of enterprises of the region; rapid identification and response to energy loss (accidents, damage, illegal use etc); working out the effective managerial decisions based on processing of large amount of information related to energy consumption. The structure of the system of energy consumption monitoring in Lviv region was developed. It consists of two subsystems - information and analytical ones. The technical basis of the information subsystem comprises wireless sensor networks ensuring energy data collection on a real-time basis. Analytical subsystem consists of energy data warehouse, ETL, OLAP, BI, Data Mining tools, prediction, visualization and decision support tools. The components of the analytical subsystem providing for visualization and evaluation of industrial energy consumption were developed.
Twórcy
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
Bibliografia
  • 1. Rozen V. P., Chernyavskiy A. V., Yachnik E. A., Litvin V .I. 2009 Energy saving programs monitoring in public sector institutions // Visnyk KDPU of Mykhailo Ostrohradskyi. Edition 3 (56). Part 2. P.190- 194.
  • 2. Teslyuk T., Tsmots I., Teslyuk V., Medykovskyy M., Opotyak Y. 2018 Architecture and Models for System-Level Computer-Aided Design of the Management System of Energy Efficiency of Technological Processes at the Enterprise // Advances in Intelligent Systems and Computing II, Advances in Intelligent Systems and Computing 689 Springer International Publishing AG. P.538-557.
  • 3. Medykovskyi M. O., Tsmots I. G., Skorokhoda. O. V. Spectrum neural network filtration technology for improving the forecast accuracy of dynamic processes in economics // Actual Problems of Economics. №12 (162) 2014. Рр. 410-416.
  • 4. Medykovskyi M. O., Tsmots I. G., Skorokhoda O. V., Teslyuk T.V. 2016, Design of Intelligent Component of Hierarchical Control System // Econtechmod. An International Quarterly Journal – Vol.5. No 2.3 - P.3-10.
  • 5. Medykovskyi M. O., Tsmots I. G., Tsymbal Y. V. Intelligent data processing tools in the systems of energy efficiency management for regional economy // Actual Problems of Economics. №12 (150). Р. 271-277.
  • 6. Tsmots I. G., Tsymbal Y. V., Tsmots O. I. 2012, Early-warning systems for enterprises using neural networks tools // Actual Problems of Economics. №10 (136). Р. 283-291.
  • 7. Intelligent Components of Integrated Automated Control Systems: monograph / M. O. Medykovskyi, R. O. Tkachenko, I. H. Tsmots etc. – Lviv: Publishing House of Lviv Polytechnic, 2015. – 315 p.
  • 8. Teslyuk T., Tsmots I., Teslyuk V., Medykovskyi M., Opotyak Y. 2017, Architecture of the management system of energy efficiency of technological processes at the enterprise // Proceedings of XIIth International Scientific and Technical Conference CSIT 2017. 5-8 September. Lviv, Ukraine – P. 429-433.
  • 9. Medykovskyi M. O., Tsmots I. H. Tsymbal Y. V. 2016, Information analytical system for energy efficiency management at enterprises in the city of Lviv (Ukraine) // Actual Problems of Economics. №1 (175). P. 379-384.
  • 10. Medykovskyi M. O., Tsmots I. H., Podolskyi M .R. 2013, Substantiation of development principles and generalized structure construction of the informational analytical system for estimating, forecasting and managing energy efficiency of the region’s economy // Visnyk NU “Lviv Polytechnic” “Computer Science and Information Technology”, № 751. – Lviv. – P. 40-51.
  • 11. Tsmots I. H., Tesliuk V. M, Tesliuk T. V. 2017, Determining model for the investment priority of energy saving projects implementation on enterprise // Actual Problems of Economics. №1 (187). P. 398-408.
  • 12. Tsmots I. H., Tesliuk T. V., Opotiak Y.V. Tesliuk V.M. 2017, Architecture of the multilevel energy efficiency management system of the region // Visnyk NU “Lviv Polytechnic” “Computer Science and Information Technology” №864 Lviv. P.201-209.
  • 13. Tsmots I. H., Skorokhoda O. V., Roman V. I. 2016, Multilevel energy efficiency management systems data warehouses // Collection of scientific works “Modeling and Information Technology”. Institute of Modeling Problems in Power Engineering. Edition 77. P. 192–197.
  • 14. Arakelov, V. E., Kremer, A. I. 1990, Methodological issues of energy saving. M: Energoatomizdat. 188 p.
  • 15. Ganzha, V. L. 2007, Basics of effective use of energy resources. Mn.: Beloruskaya nauka. 452 p.
  • 16. Agile Best Practices for Data Warehousing [Electronic resource]. - Access mode: http://www.agiledata.org/essays/dataWarehousingBestPractices.html
  • 17. Data Warehouse Design [Electronic resource]. - Access mode: http://tdan.com/data-warehouse-design-inmon-versus-kimball/20300
  • 18. Big Data Implementation vs. Data Warehousing [Electronic resource]. - Access mode: http://www.b-eye-network.com/view/17017
  • 19. Lambda Architecture [Electronic resource] - Access mode: http://lambda-architecture.net/
  • 20. Big Data and its Impact on Data Warehousing [Electronic resource] - Access mode: http://cdn.ttgtmedia.com/BeyeNETWORK/downloads/BigDataE-Book_final.pdf
  • 21. Real-Time Stream Processing [Electronic resource] - Access mode: https://www.infoq.com/articles/stream-processing-hadoop
  • 22. Batch vs Streaming Processing [Electronic resource] - Access mode: http://blog.syncsort.com/2017/07/big-data/big-data-101-batch-stream-processing/
  • 23. Spark Streaming [Electronic resource] - Access mode: https://spark.apache.org/streaming.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3f6fb2dd-fd30-4285-89fe-f24d94f543d2
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