Optimal power flow solution using improved harmony search method

Sinsuphan, Nampetch; Leeton, Uthen; Kulworawanichpong, Thanatchai

doi:10.1016/j.asoc.2013.01.024

Cited by 89 publications

(33 citation statements)

References 23 publications

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“…On the other hand, these parameters are taken as constant in conventional HSA. Literature survey reveals that IHSA has been, successfully, applied in solving complex engineering optimization problems and the numerical results reveals that the IHSA can find a better solution vector in comparison to traditional HSA and other metaheuristic optimization technique [35,36].…”

Section: Variants Of Hsamentioning

confidence: 97%

Quasi oppositional harmony search algorithm based controller tuning for load frequency control of multi-source multi-area power system

Shankar

Mukherjee

2016

International Journal of Electrical Power & Energy Systems

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Section: Variants Of Hsamentioning

confidence: 97%

Quasi oppositional harmony search algorithm based controller tuning for load frequency control of multi-source multi-area power system

Shankar

Mukherjee

2016

International Journal of Electrical Power & Energy Systems

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“…The economic load dispatch and combined economic and emission load dispatch problems can be converted into the minimization of the cost function [18]. Sinsuphan et al [19] combine the HS with sequential quadratic programming and GA to solve the optimal power flow problems. The objective function to be optimized is the total generator fuel costs in the entire system.…”

Section: Power Systemsmentioning

confidence: 99%

The Overview of Harmony Search

Wang

Gao

Zenger

2014

An Introduction to Harmony Search Optimization Method

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When musicians compose the harmony, they usually try various possible combinations of the music pitches stored in their memory, which can be considered as a optimization process of adjusting the input (pitches) to obtain the optimal output (perfect harmony). Harmony search draws the inspiration from harmony improvisation, and has gained considerable results in the field of optimization, although it is a relatively NIC algorithm. With mimicking the rules of various combining pitches, harmony search has two distinguishing operators different from other NIC algorithms: harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) that are used to generate and further mutate a solution, respectively. This candidate generation mechanism and single search memory involved decide its excellence in structure simplicity and small initial population. This chapter presents the discussions of the inspiration of harmony search, the basic harmony search optimization algorithm, and an overview of different application areas of the harmony search.

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“…Recent attempts to overcome the limitations of mathematical programming approaches include the application of meta-heuristic algorithm i.e. modified teaching-learning based optimization (MTLBO) [8], gravitational search algorithm (GSA) [9], improved harmony search method [10], discrete PSO [11], League Championship Algorithm (LCA) [12], etc. However, none of the above-mentioned frameworks has considered all the practical constraints on TUs such as POZs, multi-fuel options and valve-point effects.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although, there is a vast body of literature on proposing a solution methodology for DOPF including [6][7][8][9][10][11][12], and on modeling the uncertainties and correlations between IRVs of the POPF problem which comprise [13][14][15][16][17][18][19][20][21][22][23], little attention has been paid to accomplish the goal of contributing all these essential issues in a well-organized POPF considering both the technical and economical restrictions.…”

Section: Literature Reviewmentioning

confidence: 99%