Open AccessTransmission expansion planning using AC‐based differential evolution algorithm
Author(s) -
Alhamrouni Ibrahim,
Khairuddin Azhar,
Ferdavani Ali Khorasani,
Salem Mohamed
Publication year - 2014
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2014.0001
Subject(s) - mathematical optimization , heuristic , ac power , electric power system , power flow , transmission system , computer science , differential evolution , transmission (telecommunications) , electrical network , slack bus , voltage , nonlinear system , electric power transmission , algorithm , integer programming , flow (mathematics) , nonlinear programming , power flow study , power (physics) , mathematics , engineering , electrical engineering , telecommunications , physics , quantum mechanics , geometry
The rapid growth of the transmission networks has brought more uncertainties and new requirements in the transmission expansion planning (TEP) to the planners. The existing methods of solving TEP problem have a drawback since the DC load flow and the relaxed load flow models have been utilized to solve TEP problem. In this work, the TEP problem is solved based on mixed integer nonlinear non‐convex programming model. A meta‐heuristic algorithm by the means of differential evolution algorithm (DEA) is employed as an optimisation tool. An AC load flow model is used in solving the TEP problem, where accurate and realistic results can be obtained. Furthermore, the work considers the constraints checking and system violation such as real and power generation limits, possible number of lines added and bus voltage limits. The proposed technique is tested on Garver's 6 bus system and IEEE 24 bus system and has shown high capability in considering the active and reactive power in the same manner and solving the TEP problem. The method produced improved results for the test systems. In terms of minimising the cost and the solution quality, the proposed method obtained good and challenging results comparing to the previous works.