Voltage Profile Augmentation and Minimization of Real Power Loss in Transmission Lines by using Improved Hybrid Particle Swarm Optimization-Based on Harmony Search Algorithm

α
Dr.K.Lenin
Dr.K.Lenin
σ
K. Lenin
K. Lenin
ρ
Dr. B.Ravindranath Reddy
Dr. B.Ravindranath Reddy
Ѡ
Dr. M.Surya Kalavathi
Dr. M.Surya Kalavathi

Send Message

To: Author

Voltage Profile Augmentation and Minimization of Real Power Loss in Transmission Lines  by using  Improved Hybrid Particle Swarm Optimization-Based on Harmony Search Algorithm

Article Fingerprint

ReserarchID

BEW5P

Voltage Profile Augmentation and Minimization of Real Power Loss in Transmission Lines  by using  Improved Hybrid Particle Swarm Optimization-Based on Harmony Search Algorithm Banner

AI TAKEAWAY

Connecting with the Eternal Ground
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

Abstract

In this paper, a new particle swarm search algorithm is proposed to solve the optimal reactive power dispatch (ORPD) Problem. The ORPD problem is formulated as a nonlinear constrained singleobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized separately. As an optimization technique, particle swarm optimization (PSO) has obtained much attention during the past decade. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to realize. To enhance the performance of PSO, an improved hybrid particle swarm optimization (IHPSO) is proposed to solve complex optimization problems more efficiently, accurately and reliably. It provides a new way of producing new individuals through organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to generate new solutions and this makes IHPSO algorithm have more powerful exploitation capabilities. In order to evaluate the performance of the proposed algorithm, it has been tested on IEEE 30 bus system.

References

31 Cites in Article
  1. M Abido,J Bakhashwain (2003). A novel multiobjective evolutionaryalgorithm for optimal reactive power dispatch problem.
  2. W Abdullah,H Saibon,A Zain,K Lo (1998). Genetic algorithm for optimal reactive power dispatch.
  3. K Lee,Y Park,J Ortiz (1984). Fuel-cost minimisation for both realandreactive-power dispatches.
  4. S Granville (1994). Optimal reactive dispatch through interior point methods.
  5. N Deeb,S Shahidehpour (1988). An Efficient Technique for ReactivePower Dispatch Using a Revised Linear Programming Approach.
  6. N Grudinin (1998). Reactive Power Optimization Using Successive QuadraticProgramming Method.
  7. M Abido (2002). Optimal Power Flow Using Particle SwarmOptimization.
  8. A Abou El Ela,M Abido,S Spea (2011). Differential EvolutionAlgorithm for Optimal Reactive Power Dispatch.
  9. V Miranda,N Fonseca (2002). EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems.
  10. Zong Geem (2006). Improved Harmony Search from Ensemble of Music Players.
  11. Zong Geem (2007). Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm.
  12. C Canizares,A De Souza,V Quintana (1996). Comparison of performance indices for detection of proximity to voltage collapse.
  13. C Bishop (1995). Neural Networks for Pattern Recognitionm.
  14. (1997). Handbook of Evolutionary Computation.
  15. J Holland (1975). Adaptation in Natural and Artificial Systems.
  16. James Kennedy,Russell Eberhart,Yuhui Shi (2001). The Particle Swarm.
  17. A Engelbrecht (2005). Fundamentals of Computational Swarm Intelligence.
  18. R Eberhart,J Kennedy (1995). A new optimizer using particle swarm theory.
  19. J Kennedy,R Eberhart (1995). Particle swarm optimization.
  20. S Fan,Y Liang,E Zahara (2004). Hybrid simplex search and particle swarm optimization for the global optimization of multimodal functions.
  21. Bo Liu,Ling Wang,Yi-Hui Jin,Fang Tang,De-Xian Huang (2005). Improved particle swarm optimization combined with chaos.
  22. Z Geem,J Kim,G Loganathan (2001). A new heuristic optimization algorithm: harmony search.
  23. Kang Lee,Zong Geem (2004). A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice.
  24. Joong Kim,Zong Geem,Eung Kim (2001). PARAMETER ESTIMATION OF THE NONLINEAR MUSKINGUM MODEL USING HARMONY SEARCH<sup>1</sup>.
  25. Z Geem,J Kim,G Loganathan (2002). Harmony search optimization: application to pipe network design.
  26. S Kang,Z Geem (2004). A new structural optimization method based on the harmony search algorithm.
  27. Zong Geem,Chung-Li Tseng,Yongjin Park (2005). Harmony Search for Generalized Orienteering Problem: Best Touring in China.
  28. Q Wu,J Ma (1995). Power system optimal reactive power dispatch using evolutionary programming.
  29. S Durairaj,D Devaraj,P Kannan (2006). Genetic algorithm applications to optimal reactive power dispatch with voltage stability enhancement.
  30. D Devaraj (2007). Improved genetic algorithm for multi‐objective reactive power dispatch problem.
  31. P Jeyanthy,Dr Devaraj (2010). Optimal Reactive Power Dispatch for Voltage Stability Enhancement Using Real Coded Genetic Algorithm.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr.K.Lenin. 2014. \u201cVoltage Profile Augmentation and Minimization of Real Power Loss in Transmission Lines by using Improved Hybrid Particle Swarm Optimization-Based on Harmony Search Algorithm\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 14 (GJRE Volume 14 Issue F3): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Version of record

v1.2

Issue date

June 2, 2014

Language
en
Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 4651
Total Downloads: 2309
2026 Trends
Related Research

Published Article

In this paper, a new particle swarm search algorithm is proposed to solve the optimal reactive power dispatch (ORPD) Problem. The ORPD problem is formulated as a nonlinear constrained singleobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized separately. As an optimization technique, particle swarm optimization (PSO) has obtained much attention during the past decade. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to realize. To enhance the performance of PSO, an improved hybrid particle swarm optimization (IHPSO) is proposed to solve complex optimization problems more efficiently, accurately and reliably. It provides a new way of producing new individuals through organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to generate new solutions and this makes IHPSO algorithm have more powerful exploitation capabilities. In order to evaluate the performance of the proposed algorithm, it has been tested on IEEE 30 bus system.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Voltage Profile Augmentation and Minimization of Real Power Loss in Transmission Lines by using Improved Hybrid Particle Swarm Optimization-Based on Harmony Search Algorithm

K. Lenin
K. Lenin
Dr. B.Ravindranath Reddy
Dr. B.Ravindranath Reddy
Dr. M.Surya Kalavathi
Dr. M.Surya Kalavathi

Research Journals