Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mahmoud G. Hemeida"'
Autor:
Mahmoud G. Hemeida, Abdalla Ahmed Ibrahim, Al-Attar A. Mohamed, Salem Alkhalaf, Ayman M. Bahaa El-Dine
Publikováno v:
Ain Shams Engineering Journal, Vol 12, Iss 1, Pp 609-619 (2021)
The endless problem of energy supplies are always floating on the surface. As a result, there are a daily improvement to optimize power generators, networks and system configuration. Renewable distributed generators (RDG) are in the heart of these de
Externí odkaz:
https://doaj.org/article/955c431436fb46e1a3bf222fb9c09e90
Publikováno v:
Energies, Vol 15, Iss 24, p 9417 (2022)
Moving towards RER has become imperative to achieve sustainable development goals (SDG). Renewable energy resources (RER) are characterized by uncertainty whereas, most of them are unpredictable and variable according to climatic conditions. This pap
Externí odkaz:
https://doaj.org/article/c9df0b2898f545aea53d941dc997f0e4
Autor:
Asmaa Fawzy, Youssef Mobarak, Dina S. Osheba, Mahmoud G. Hemeida, Tomonobu Senjyu, Mohamed Roshdy
Publikováno v:
Energies, Vol 15, Iss 23, p 8884 (2022)
Single widespread employment of renewable energy sources (RESs) contributes to the shortage in the inertia of the microgrid (MG). After this, frequency stability may regress as a result of power imbalance or minor load fluctuations. This paper propos
Externí odkaz:
https://doaj.org/article/aab439e1d6884488b730f9d99fca674f
Autor:
Mahmoud G. Hemeida, Salem Alkhalaf, Al-Attar A. Mohamed, Abdalla Ahmed Ibrahim, Tomonobu Senjyu
Publikováno v:
Energies, Vol 13, Iss 15, p 3847 (2020)
Manta Ray Foraging Optimization Algorithm (MRFO) is a new bio-inspired, meta-heuristic algorithm. MRFO algorithm has been used for the first time to optimize a multi-objective problem. The best size and location of distributed generations (DG) units
Externí odkaz:
https://doaj.org/article/3825a1565dba4878a412b66324e4b81f
Autor:
Abdalla Ahmed Ibrahim, Mahrous Ahmed, Salem Alkhalaf, Ayman M. Bahaa-Eldin, Tomonobu Senjyu, Mahmoud G. Hemeida
Publikováno v:
Ain Shams Engineering Journal, Vol 12, Iss 3, Pp 2735-2762 (2021)
Stochastic nature of load demand has a great impact on the performance of electrical power system. As a result, planning of electrical power system considering load uncertainties became inevitable. This paper presents Monte Carlo simulation based dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad363a82cee73566fbd8ca018b5085dc
http://www.sciencedirect.com/science/article/pii/S2090447921000940
http://www.sciencedirect.com/science/article/pii/S2090447921000940
Autor:
Al-Attar Ali Mohamed, Salem Alkhalaf, Ayman M. Bahaa El-Dine, Abdalla Ahmed Ibrahim, Mahmoud G. Hemeida
Publikováno v:
Ain Shams Engineering Journal, Vol 12, Iss 1, Pp 609-619 (2021)
The endless problem of energy supplies are always floating on the surface. As a result, there are a daily improvement to optimize power generators, networks and system configuration. Renewable distributed generators (RDG) are in the heart of these de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9d06b60474aa6f4058ce6a8e900ad50
https://doi.org/10.1016/j.asej.2020.07.009
https://doi.org/10.1016/j.asej.2020.07.009
Autor:
Salem Alkhalaf, Abdalla Ahmed Ibrahim, Tomonobu Senjyu, Mahmoud G. Hemeida, Al-Attar Ali Mohamed
Publikováno v:
Energies, Vol 13, Iss 3847, p 3847 (2020)
Energies; Volume 13; Issue 15; Pages: 3847
Energies; Volume 13; Issue 15; Pages: 3847
Manta Ray Foraging Optimization Algorithm (MRFO) is a new bio-inspired, meta-heuristic algorithm. MRFO algorithm has been used for the first time to optimize a multi-objective problem. The best size and location of distributed generations (DG) units
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d9863fc687ac8255657e468c1924e71
https://www.mdpi.com/1996-1073/13/15/3847
https://www.mdpi.com/1996-1073/13/15/3847
Autor:
Mahmoud G Hemeida, Salem Alkhalaf, Tomonobu Senjyu, Abdalla Ibrahim, Mahrous Ahmed, Ayman M. Bahaa-Eldin
Publikováno v:
Ain Shams Engineering Journal, Vol 12, Iss 3, Pp 2735-2762 (2021)
Stochastic nature of load demand has a great impact on the performance of electrical power system. As a result, planning of electrical power system considering load uncertainties became inevitable. This paper presents Monte Carlo simulation based dif
Externí odkaz:
https://doaj.org/article/a318514a377d4791bfb788ccee77249a