Zobrazeno 1 - 10
of 86
pro vyhledávání: '"V-I trajectory"'
Publikováno v:
Heliyon, Vol 10, Iss 14, Pp e34457- (2024)
Non-intrusive load monitoring (NILM) can obtain fine-grained power consumption information for individual appliances within the user without installing additional hardware sensors. With the rapid development of the deep learning model, many methods h
Externí odkaz:
https://doaj.org/article/052a8be2c4a74d608ad3e5f46a05521c
Publikováno v:
Heliyon, Vol 10, Iss 9, Pp e30666- (2024)
Non-intrusive load monitoring (NILM) offers precise insights into equipment-level energy consumption by analyzing current and voltage data from residential smart meters, thus emerging as a potential strategy for demand-side management in power system
Externí odkaz:
https://doaj.org/article/b70bf37c39b54051aeda5c81af69b04d
Publikováno v:
Sensors, Vol 24, Iss 8, p 2562 (2024)
Non-intrusive load monitoring (NILM) can identify each electrical load and its operating state in a household by using the voltage and current data measured at a single point on the bus, thereby behaving as a key technology for smart grid constructio
Externí odkaz:
https://doaj.org/article/5c53ec840ead4aadb56d41325b0feb82
Hierarchical load identification method based on K-means clustering and PSO feature optimization KNN
Publikováno v:
Journal of Hebei University of Science and Technology, Vol 43, Iss 3, Pp 249-258 (2022)
In order to solve the problem that a single V-I track feature can not effectively identify similar track features and the extracted features are prone to redundacy or even noise features in non-invasive load identification,a hierarchical non-invasive
Externí odkaz:
https://doaj.org/article/48ff12f50af84b18ab6435b9e9259e6f
Publikováno v:
IEEE Access, Vol 10, Pp 11564-11573 (2022)
The traditional non-intrusive load monitoring (NILM) algorithms are mostly based on classification models, which have several deficiencies. Firstly, a large amount of labeled data is required to train the classification model. Secondly, these algorit
Externí odkaz:
https://doaj.org/article/7d4700aca5be4f569ec77773f442f914
Akademický článek
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Nonintrusive Load Monitoring Method Based on Color Encoding and Improved Twin Support Vector Machine
Publikováno v:
Frontiers in Energy Research, Vol 10 (2022)
In the process of traditional power load identification, the load information of V-I track is missing, the image similarity of V-I track of some power loads is high and the recognition effect is not good, and the training time of recognition model is
Externí odkaz:
https://doaj.org/article/3d1f0dcc8ee14ad6bcd3ae37dbe09c84
Autor:
Qifeng Huang, Kaijie Fang, Zecheng Ding, Hanmiao Cheng, Yixuan Huang, Lulu Geng, Puyu Wang, Haibo Xu
Publikováno v:
Frontiers in Energy Research, Vol 10 (2022)
Taking into account energy management and fire safety, electric bicycles are one of the most significant household loads that require real-time sensing for nonintrusive load monitoring. V–I trajectories, power quantities, and harmonic characteristi
Externí odkaz:
https://doaj.org/article/a8630b97507b43afa5e0eef18c827c89
Publikováno v:
AIMS Electronics and Electrical Engineering, Vol 4, Iss 3, Pp 326-344 (2020)
Nonintrusive Appliance Load Monitoring (NIALM) is used to analyze individual’s house energy consumption by distinguishing variations in voltage and current of appliances in a household. The method identifies load consumption of each appliance from
Externí odkaz:
https://doaj.org/article/3894bdb26fea4723815f2dd870209bc6
Akademický článek
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