Title
Swarm Based Mean-Variance Mapping Optimization For Solving Economic Dispatch With Cubic Fuel Cost Function
Abstract
In power generation system, the economic dispatch (ED) is used to allocate the real power output of thermal generating units to meet required load demand so as their total operating cost is minimized while satisfying all units and system constraints. This paper proposes a novel swarm based mean-variance mapping optimization (MVMOS) for solving the ED problem with the cubic fuel cost function. The special feature of the proposed algorithm is a mapping function applied for the mutation based on the mean and variance of n-best population. This method has been tested on 3, 5 and 26 units and the obtained results are compared to those from genetic algorithm (GA), particle swarm optimization (PSO) and firefly algorithm (FA). Test results have indicated that the proposed method is efficient for solving the ED problem with cubic fuel cost function.
Year
DOI
Venue
2015
10.1007/978-3-319-15705-4_1
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT II
Keywords
Field
DocType
Economic dispatch, Cubic fuel cost function, Mean-variance mapping optimization, Swarm based Mean-variance mapping optimization
Particle swarm optimization,Population,Economic dispatch,Mathematical optimization,Swarm behaviour,Computer science,Multi-swarm optimization,Firefly algorithm,Genetic algorithm,Operating cost
Conference
Volume
ISSN
Citations 
9012
0302-9743
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Khoa H. Truong100.34
P. Vasant210015.00
M. S. Balbir Sing300.34
Dieu N. Vo442.45