Monitoring and control of electrical power systems using machine learning techniques:
Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-tim...
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Elsevier
[2023]
|
| Zusammenfassung: | Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms |
| Beschreibung: | 1. Introduction to Monitoring and control of electrical power systems using machine learning techniques ; 2. Power quality disturbances in electrical power systems; 3. Monitoring and control in electrical power systems; 4. Benchmark Test Systems for the Validation of Power Quality Disturbance Studies; 5. Advanced signal processing methods for monitoring and control of Electrical Power Systems; 6. Monitoring of Electrical Power Systems based on Automatic Learning methods; 7. Spatio-Temporal Data-Driving Methods for Monitoring of Electrical Power Systems; 8. Data Analytic Applications for Monitoring of Electrical Power Systems; 9. Trends in Monitoring and Control of Power Quality in Electrical Power Systems ; 10. Didactic examples of algorithm implementation |
| Beschreibung: | xiv, 339 Seiten Illustrationen, Diagramme 450 grams |
| ISBN: | 9780323999045 |
Internformat
MARC
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| 245 | 1 | 0 | |a Monitoring and control of electrical power systems using machine learning techniques |c Emilio Barocio Espejo, Felix Rafael Segundo Sevilla, Petr Korba |
| 264 | 1 | |a Amsterdam |b Elsevier |c [2023] | |
| 300 | |a xiv, 339 Seiten |b Illustrationen, Diagramme |c 450 grams | ||
| 336 | |b txt |2 rdacontent | ||
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| 338 | |b nc |2 rdacarrier | ||
| 500 | |a 1. Introduction to Monitoring and control of electrical power systems using machine learning techniques ; 2. Power quality disturbances in electrical power systems; 3. Monitoring and control in electrical power systems; 4. Benchmark Test Systems for the Validation of Power Quality Disturbance Studies; 5. Advanced signal processing methods for monitoring and control of Electrical Power Systems; 6. Monitoring of Electrical Power Systems based on Automatic Learning methods; 7. Spatio-Temporal Data-Driving Methods for Monitoring of Electrical Power Systems; 8. Data Analytic Applications for Monitoring of Electrical Power Systems; 9. Trends in Monitoring and Control of Power Quality in Electrical Power Systems ; 10. Didactic examples of algorithm implementation | ||
| 520 | |a Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms | ||
| 700 | 1 | |a Barocio Espejo, Emilio |0 (DE-588)1177731711 |4 edt | |
| 700 | 1 | |a Segundo Sevilla, Felix Rafael |4 edt | |
| 700 | 1 | |a Korba, Petr |4 edt | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034064858 | ||
Datensatz im Suchindex
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| author2 | Barocio Espejo, Emilio Segundo Sevilla, Felix Rafael Korba, Petr |
| author2_role | edt edt edt |
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| author_GND | (DE-588)1177731711 |
| author_facet | Barocio Espejo, Emilio Segundo Sevilla, Felix Rafael Korba, Petr |
| building | Verbundindex |
| bvnumber | BV048690647 |
| classification_rvk | ZN 8520 |
| ctrlnum | (OCoLC)1372479405 (DE-599)BVBBV048690647 |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| discipline_str_mv | Elektrotechnik / Elektronik / Nachrichtentechnik |
| format | Book |
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| id | DE-604.BV048690647 |
| illustrated | Illustrated |
| index_date | 2024-07-03T21:27:22Z |
| indexdate | 2024-07-10T09:46:14Z |
| institution | BVB |
| isbn | 9780323999045 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034064858 |
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| owner_facet | DE-29T DE-898 DE-BY-UBR |
| physical | xiv, 339 Seiten Illustrationen, Diagramme 450 grams |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Elsevier |
| record_format | marc |
| spelling | Monitoring and control of electrical power systems using machine learning techniques Emilio Barocio Espejo, Felix Rafael Segundo Sevilla, Petr Korba Amsterdam Elsevier [2023] xiv, 339 Seiten Illustrationen, Diagramme 450 grams txt rdacontent n rdamedia nc rdacarrier 1. Introduction to Monitoring and control of electrical power systems using machine learning techniques ; 2. Power quality disturbances in electrical power systems; 3. Monitoring and control in electrical power systems; 4. Benchmark Test Systems for the Validation of Power Quality Disturbance Studies; 5. Advanced signal processing methods for monitoring and control of Electrical Power Systems; 6. Monitoring of Electrical Power Systems based on Automatic Learning methods; 7. Spatio-Temporal Data-Driving Methods for Monitoring of Electrical Power Systems; 8. Data Analytic Applications for Monitoring of Electrical Power Systems; 9. Trends in Monitoring and Control of Power Quality in Electrical Power Systems ; 10. Didactic examples of algorithm implementation Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms Barocio Espejo, Emilio (DE-588)1177731711 edt Segundo Sevilla, Felix Rafael edt Korba, Petr edt |
| spellingShingle | Monitoring and control of electrical power systems using machine learning techniques |
| title | Monitoring and control of electrical power systems using machine learning techniques |
| title_auth | Monitoring and control of electrical power systems using machine learning techniques |
| title_exact_search | Monitoring and control of electrical power systems using machine learning techniques |
| title_exact_search_txtP | Monitoring and control of electrical power systems using machine learning techniques |
| title_full | Monitoring and control of electrical power systems using machine learning techniques Emilio Barocio Espejo, Felix Rafael Segundo Sevilla, Petr Korba |
| title_fullStr | Monitoring and control of electrical power systems using machine learning techniques Emilio Barocio Espejo, Felix Rafael Segundo Sevilla, Petr Korba |
| title_full_unstemmed | Monitoring and control of electrical power systems using machine learning techniques Emilio Barocio Espejo, Felix Rafael Segundo Sevilla, Petr Korba |
| title_short | Monitoring and control of electrical power systems using machine learning techniques |
| title_sort | monitoring and control of electrical power systems using machine learning techniques |
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