Open AccessA novel sizing inherits allocation strategy of renewable distributed generations using crow search combined with particle swarm optimization algorithm
Author(s) -
Farh Hassan M. H.,
Eltamaly Ali M.,
AlShaalan Abdullah M.,
AlShamma'a Abdullrahman A.
Publication year - 2021
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12107
Subject(s) - sizing , particle swarm optimization , mathematical optimization , benchmark (surveying) , computer science , photovoltaic system , renewable energy , distributed generation , reduction (mathematics) , wind power , algorithm , engineering , mathematics , electrical engineering , art , geometry , geodesy , visual arts , geography
In this study, a new distributed generation sizing that inherits the allocation strategy for the IEEE 30‐bus benchmark system is proposed. The hybrid crow search‐particle swarm optimization technique would select the optimal buses through the automatic cancelation of the unfeasible load buses. Additionally, it performs sizing that inherits allocation for minimum costs and transmission losses. Also, it selects the best distributed generation technology among wind turbines and photovoltaic energy systems based on the minimum total capital cost. The proposed strategy outperformed others in terms of total cost alleviation, power losses reduction, voltage profile improvement, and lines loading mitigation.