Journal
NEUROCOMPUTING
Volume 78, Issue 1, Pages 55-63Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2011.05.030
Keywords
Distributed generations; Optimal location and capacity; Swarm intelligence; Improved group search optimizer
Categories
Funding
- National Science Foundation of China [61005090, 61034004, 91024023, 61075064]
- Ph.D. Programs Foundation of Ministry of Education of China [20100072110038]
- Ministry of Education of China
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This paper presents a novel efficient population-based heuristic approach for optimal location and capacity of distributed generations (DGs) in distribution networks, with the objectives of minimization of fuel cost, power loss reduction, and voltage profile improvement. The approach employs an improved group search optimizer (iGSO) proposed in this paper by incorporating particle swarm optimization (PSO) into group search optimizer (GSO) for optimal setting of DGs. The proposed approach is executed on a networked distribution system the IEEE 14-bus test system for different objectives. The results are also compared to those that executed by basic GSO algorithm and PSO algorithm on the same test system. The results show the effectiveness and promising applications of the proposed approach in optimal location and capacity of DGs. (C) 2011 Elsevier B.V. All rights reserved.
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