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Title: :  Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms
PaperId: :  3954
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 3 Issue 2 2017
DUI:    16.0415/IJARIIE-3954
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Pawanpreet SinghGNIEM, Naushehra, Hoshiarpur, Punjab ,India
Rohit BainsGNIEM, Naushehra, Hoshiarpur, Punjab ,India
Gurjit SinghFormerly Dr. B. R. Ambedkar N.I.T , Jalandhar, Presently GNIEM, Naushehra, Hoshiarpur, Punjab, India
Neha BhagatGNIEM, Naushehra, Hoshiarpur, Punjab, India
Vikram Kumar KambojDAV University, Jalandhar, Punjab ,India
Ashutosh BhadoriaDAV University, Jalandhar, Punjab ,India

Abstract

Electrical Engineering
Economic Load Dispatch Problem Optimization (ELDPO), Power Management System (PMS), Moth Flame Optimization (MFO), Sine Cosine Algorithm (SCA)
This paper proposes a heuristic approach for Economic Load Dispatch Problem Optimization (ELDPO) in Power Management System (PMS) using Sine Cosine Algorithm (SCA) and Moth Flame Optimizer Algorithm (MFO), erstwhile performing a combinatorial analysis among them. ELDPO is a remedy to real time onsite problem incurred in PMS of Electrical Power Generation Systems (EPGS) (Both Conventional & Non-Conventional) which paves way to transmission and operation constraints. SCA is used for constrained optimization problems and based on the concept of a correlation mathematical model of sine and cosine functions. Also, MFO is a heuristic algorithm which utilizes the concept that the moth eventually converges towards the light. Both SCA algorithm and MFO algorithm are utilized for ELDPO of Three IEEE benchmarks of small scale power systems and are verified by a comparative study with Lambda Iteration. Combinatorial results show that the performance of MFO is better than SCA algorithm in view of various parameters viz. Exploration, local optima avoidance, exploitation and convergence.

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IJARIIE Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. "Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms" International Journal Of Advance Research And Innovative Ideas In Education Volume 3 Issue 2 2017 Page 65-75
MLA Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. "Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms." International Journal Of Advance Research And Innovative Ideas In Education 3.2(2017) : 65-75.
APA Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, & Ashutosh Bhadoria. (2017). Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms. International Journal Of Advance Research And Innovative Ideas In Education, 3(2), 65-75.
Chicago Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. "Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms." International Journal Of Advance Research And Innovative Ideas In Education 3, no. 2 (2017) : 65-75.
Oxford Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. 'Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms', International Journal Of Advance Research And Innovative Ideas In Education, vol. 3, no. 2, 2017, p. 65-75. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Comparative_Analysis_on_Economic_Load_Dispatch_Problem_Optimization_using_Moth_Flame_Optimization_and_Sine_Cosine_Algorithms_ijariie3954.pdf (Accessed : 06 October 2018).
Harvard Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. (2017) 'Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms', International Journal Of Advance Research And Innovative Ideas In Education, 3(2), pp. 65-75IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Comparative_Analysis_on_Economic_Load_Dispatch_Problem_Optimization_using_Moth_Flame_Optimization_and_Sine_Cosine_Algorithms_ijariie3954.pdf (Accessed : 06 October 2018)
IEEE Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria, "Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms," International Journal Of Advance Research And Innovative Ideas In Education, vol. 3, no. 2, pp. 65-75, Mar-App 2017. [Online]. Available: http://ijariie.com/AdminUploadPdf/Comparative_Analysis_on_Economic_Load_Dispatch_Problem_Optimization_using_Moth_Flame_Optimization_and_Sine_Cosine_Algorithms_ijariie3954.pdf [Accessed : 06 October 2018].
Turabian Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. "Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 3 number 2 (06 October 2018).
Vancouver Pawanpreet Singh, Rohit Bains, Gurjit Singh, Neha Bhagat, Vikram Kumar Kamboj, and Ashutosh Bhadoria. Comparative Analysis on Economic Load Dispatch Problem Optimization using Moth Flame Optimization and Sine Cosine Algorithms. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2017 [Cited : 06 October 2018]; 3(2) : 65-75. Available from: http://ijariie.com/AdminUploadPdf/Comparative_Analysis_on_Economic_Load_Dispatch_Problem_Optimization_using_Moth_Flame_Optimization_and_Sine_Cosine_Algorithms_ijariie3954.pdf
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