Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/14625
Title: Self-adaptive differential evolution algorithm for economic dispatch with transmission losses consideration
Authors: Sum-Im T.
Keywords: Ant colony search algorithms
Comparative studies
Computational time
Differential evolution algorithm
Economic Dispatch
Economic dispatch problems
Fuel cost
Power system optimization
Self-adaptive differential evolution algorithms
Software development
Stable convergence
Technical operations
Test case
Thermal power plants
Transmission loss
Adaptive algorithms
Artificial intelligence
Biology
Heuristic algorithms
Mathematical programming
Software design
Tabu search
Thermoelectric power plants
Wave transmission
Evolutionary algorithms
Issue Date: 2010
Abstract: In this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical programming environment of MATLAB in this work. The efficiency of the proposed methodology is initially demonstrated via the analysis of IEEE 30-bus test case. A detailed comparative study among Lambda iteration, conventional genetic algorithm (CGA), tabu search/simulated annealing (TS/SA), ant colony search algorithm (ACSA) and the proposed method is presented. From the experimental results, the proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computational time. ©2010 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/14625
https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951615901&doi=10.1109%2fTENCON.2010.5685839&partnerID=40&md5=ea131bf89661ae7df25eca0493b1dbb8
Appears in Collections:Scopus 1983-2021

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