Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Patrick S. Pouabe Eboule"'
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 235-244 (2022)
The increase in the deployment of photovoltaic systems has brought a change to the national grid and directly influences the energy charges applied by the utilities. Different types of tariffs are applied to consumers for electrical energy. These tar
Externí odkaz:
https://doaj.org/article/aa8eb63be303485ab52c980b65eab58c
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 801-810 (2022)
Nowadays, the applications of machine learning techniques have widely been implemented in various domains of the power system and especially to predict three-phase transmission line faults. This paper compares the results obtained from two powerful m
Externí odkaz:
https://doaj.org/article/fe4ace8d9ad549a4bb2529d9eeaecb22
Publikováno v:
Energy Reports, Vol 8, Iss, Pp 801-810 (2022)
Nowadays, the applications of machine learning techniques have widely been implemented in various domains of the power system and especially to predict three-phase transmission line faults. This paper compares the results obtained from two powerful m
Publikováno v:
2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE).
Publikováno v:
2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).
Study of a nine-phase system’s implementation has been motivated by two questions, “what to do to supply more load connected to the power transmission line (line) without changing the fundamental parameters of the existing lines such as increase
Publikováno v:
2018 Australasian Universities Power Engineering Conference (AUPEC).
The study carried out here in this paper presents the application of artificial intelligence techniques to detect, classify and locate faults on power transmission line very high voltage. This paper compares the results of the techniques call Multi-
Publikováno v:
2018 IEEE Electrical Power and Energy Conference (EPEC).
In power systems, power transmission lines are an important part of an electrical grid. Thus, it is important to anticipate upcoming faults and their location by predicting them using a powerful artificial intelligence technique to improve power tran