Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Heloisa H. Müller"'
Autor:
Heloisa H. Müller, Adriel Naiber Willis Fuentes, Olívia Orneles Pereira, Lemuel José da Silva, Giselle Aparecida de Arruda Mello Martins, Gisele Barreto de Deus, Ana Carolina Megda Alves, Júlia Madiuto Grégio
Publikováno v:
International Journal of Health Science. 3:2-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::201f23372b1df9220f9be1a1520dc9e6
https://doi.org/10.22533/at.ed.15932723150410
https://doi.org/10.22533/at.ed.15932723150410
Publikováno v:
IET Generation, Transmission & Distribution. 14:2034-2045
The new grid operation constraints, allied to the substation automation and intelligence, require the state estimation (SE) to work even more efficiently, with reliability and accuracy. The proposed method for optimally allocating existing phasor mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f309fe2d9c05f3f8bb40ec0ad6ee7f2
https://doi.org/10.1049/iet-gtd.2019.0760
https://doi.org/10.1049/iet-gtd.2019.0760
Autor:
Carlos A. Castro, Heloisa H. Müller
Publikováno v:
IET Generation, Transmission & Distribution. 10:270-280
The phasor measurement technology has made it possible the monitoring and control of wide-area power systems. In this study, a new genetic algorithm based method for optimal placement of phasor measurement units (PMUs) considering observability and s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb45c8c92d160b0e2189936b27a1669d
https://doi.org/10.1049/iet-gtd.2015.1005
https://doi.org/10.1049/iet-gtd.2015.1005
Publikováno v:
Electric Power Systems Research. 80:1033-1041
In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the basic load flow, (b) solving the load flow considering the reactive power limits of generation (PV) buses, (c) determining a good quality load flow sta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9aabeebd61675a752bba42336b19d62b
https://doi.org/10.1016/j.epsr.2010.01.008
https://doi.org/10.1016/j.epsr.2010.01.008
Autor:
Heloisa H. Müller, Carlos A. Castro
Publikováno v:
2015 IEEE Eindhoven PowerTech.
This paper presents a robust self healing algorithm for the two-level state estimation (SE), including both the substation and control center levels. The SE is based on the presence of phasor measurement units (PMUs) at the substations. Even though t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0acf6f887ab622f3cc136ecb22ec133e
https://doi.org/10.1109/ptc.2015.7232274
https://doi.org/10.1109/ptc.2015.7232274
Autor:
Heloisa H. Müller, Carlos A. Castro
Publikováno v:
2013 3rd International Conference on Electric Power and Energy Conversion Systems.
This paper presents a new method for the optimal allocation of phasor measurement units in substations with a focus on the two-level state estimation process that was recently proposed in the specialized literature. A mixed heuristic/metaheuristic me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74554350b8ec1b5179d5741493c16dc8
https://doi.org/10.1109/epecs.2013.6713097
https://doi.org/10.1109/epecs.2013.6713097
Publikováno v:
2005 IEEE Russia Power Tech.
In this paper a model and a methodology for using artificial neural networks to solve the load flow problem are proposed. An evaluation of the input data required by the ANN as well as its architecture is also presented. The ANN model used in this pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6067ccc7bd5526c1610366ed81d0d5f1
https://doi.org/10.1109/ptc.2005.4524546
https://doi.org/10.1109/ptc.2005.4524546