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Optimal probabilistic reliable hybrid allocation for system reconfiguration applying WT/PV and reclosures
Author(s) -
R.A. Swief,
Noha H. El-Amary
Publication year - 2019
Publication title -
ain shams engineering journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 46
eISSN - 2090-4495
pISSN - 2090-4479
DOI - 10.1016/j.asej.2019.09.010
Subject(s) - probabilistic logic , mathematical optimization , computer science , renewable energy , distributed generation , control reconfiguration , reliability engineering , optimal allocation , electric power system , wind power , reliability (semiconductor) , distributed computing , power (physics) , engineering , mathematics , embedded system , physics , quantum mechanics , electrical engineering , artificial intelligence
This paper introduces an optimal probabilistic study based on multi objective problem integrating the stochastic behavior of the renewable resources to improve system performance properties which are represented in reducing Energy Not Served index and reducing the system power loss. The reliability indices in power system have been effected applying reconfigurations, inserting reclosures and integrating distributed generators and setting the optimal location with the appropriate size of the allocated distributed generators. The aim of the study is hugely altered according to the appropriate allocation of the reclousers and DGs with the optimal choice for the DG sizes. The achievement of the proposed methodology is to solve the technical problems while keeping distribution network with minimum pollution, so distributed generators are preferable to be renewable sources such as wind and PV energies. The volatility nature of the renewable sources, wind & PV units, makes the study crucial to embrace the probabilistic behavior of those sources. Due to the complexity of the problem which is vastly increased with the increase of the factors affecting the study, two Meta heuristic techniques are competing each other to reach the optimal solution with the optimal technique. The approached algorithm under study is examined utilizing IEEE 69 modified system.

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