Energy Cloud: Real-Time Cloud-Native Energy Management System to Monitor and Analyze Energy Consumption in Multiple Industrial Sites
Industrial organizations use Energy Management Systems (EMS) to monitor, control, and optimize their energy consumption. Industrial EMS are complex and expensive systems due to the unique requirements of performance, reliability, and interoperability. Moreover, industry is facing challenges with cur...
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| Vydáno v: | Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing s. 529 - 534 |
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| Jazyk: | angličtina |
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IEEE
01.12.2014
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| Abstract | Industrial organizations use Energy Management Systems (EMS) to monitor, control, and optimize their energy consumption. Industrial EMS are complex and expensive systems due to the unique requirements of performance, reliability, and interoperability. Moreover, industry is facing challenges with current EMS implementations such as cross-site monitoring of energy consumption and CO2 emissions, integration between energy and production data, and meaningful energy efficiency benchmarking. Additionally, big data has emerged because of recent advances in field instrumentation that led to the generation of large quantities of machine data, with much more detail and higher sampling rates. This created a challenge for real-time analytics. In order to address all these needs and challenges, we propose a cloud-native industrial EMS solution with cloud computing capabilities. Through this innovative approach we expect to generate useful knowledge in a shorter time period, enabling organizations to react quicker to changes of events and detect hidden patterns that compromise efficiency. |
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| AbstractList | Industrial organizations use Energy Management Systems (EMS) to monitor, control, and optimize their energy consumption. Industrial EMS are complex and expensive systems due to the unique requirements of performance, reliability, and interoperability. Moreover, industry is facing challenges with current EMS implementations such as cross-site monitoring of energy consumption and CO2 emissions, integration between energy and production data, and meaningful energy efficiency benchmarking. Additionally, big data has emerged because of recent advances in field instrumentation that led to the generation of large quantities of machine data, with much more detail and higher sampling rates. This created a challenge for real-time analytics. In order to address all these needs and challenges, we propose a cloud-native industrial EMS solution with cloud computing capabilities. Through this innovative approach we expect to generate useful knowledge in a shorter time period, enabling organizations to react quicker to changes of events and detect hidden patterns that compromise efficiency. |
| Author | Carreira, Paulo Sequeira, Hugo Goldschmidt, Thomas Vorst, Philipp |
| Author_xml | – sequence: 1 givenname: Hugo surname: Sequeira fullname: Sequeira, Hugo email: hugo.sequeira@tecnico.ulisboa.pt organization: INESC-ID Lisboa, Lisbon, Portugal – sequence: 2 givenname: Paulo surname: Carreira fullname: Carreira, Paulo email: paulo.carreira@tecnico.ulisboa.pt organization: INESC-ID Lisboa, Lisbon, Portugal – sequence: 3 givenname: Thomas surname: Goldschmidt fullname: Goldschmidt, Thomas email: thomas.goldschmidt@de.abb.com organization: ABB Corp. Res., Ladenburg, Germany – sequence: 4 givenname: Philipp surname: Vorst fullname: Vorst, Philipp email: philipp.vorst@de.abb.com organization: ABB Corp. Res., Ladenburg, Germany |
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| Snippet | Industrial organizations use Energy Management Systems (EMS) to monitor, control, and optimize their energy consumption. Industrial EMS are complex and... |
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| StartPage | 529 |
| SubjectTerms | big data Cloud computing Energy consumption Energy efficiency Energy management energy management systems Industries Monitoring Production Real-time systems |
| Title | Energy Cloud: Real-Time Cloud-Native Energy Management System to Monitor and Analyze Energy Consumption in Multiple Industrial Sites |
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