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Ant Lion Optimizer based Approach for Optimal Scheduling of Thermal Units for Small Scale Electrical Economic Power Dispatch Problem

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJGDC) 바로가기
  • 간행물
    International Journal of Grid and Distributed Computing SCOPUS 바로가기
  • 통권
    Vol.9 No.7 (2016.07)바로가기
  • 페이지
    pp.211-224
  • 저자
    Navpreet Singh Tung, Sandeep Chakravorty
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A281636

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원문정보

초록

영어
A novel nature inspired algorithm ant lion optimizer (ALO) is recently developed which is motivated from the hunting mechanism of ant lions .Inherit steps of hunting prey such as the random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building are simulated to find the optimal solution of real life problems . Intelligent and Optimization techniques based on evolutionary computing, metaheuristic,biological base,nature inspired, search method establish their applications in the area of electrical economic power dispatch planning(EEPDP) to reach global optimal solution for this multi scale, multi-decision, multi-objective combinatorial problem subjected to different constraints.An application of ALO to solve non linear elec-tric economic power dispatch problem(EEPDP) is proposed in this paper. Efficient and optimal planning of economic electrical power dispatch problem is an integral part of economic electrical energy generation planning and it is the need of time for the electrical engineers to browse this area in multi-scale planning scenarios.. The performance of s ant lion optimizer (ALO) to solve electrical economic power dispatch problem is tested on three and six unit system.Test results are compared with other techniques grey wolf optimization(GWO),cuckoo search(CS),artificial bee colony(ABC),firefly algorithm(FA),particle swarm optimization(PSO),shuffled frog leap (SFL) ,bacteria foraging algorithm(BFO),harmony search(HS) applied in literature. Simulation results proved that the ALO technique is better as compared to other nature inspired,heuristic,metaheuristic techniques to find global minima and maintain the solution quality in terms of low fuel cost.

목차

Abstract
 1. Introduction
 2. Problem Formulation
 3. Ant Lion Optimizer
 4. Optimal Economic Power Dispatch Formulation using ALO
 5. Test System
 6. Simulation Results
 7. Conclusion
 Acknowledgements
 References

키워드

Ant Lion Optimizer (ALO) Electrical Economic Power Dispatch Problem (EEPDP) artificial bee colony(ABC) firefly algorithm(FA) particle swarm optimization(PSO) shuffled frog leap (SFL)

저자

  • Navpreet Singh Tung [ Assistant Professor, Department of Electrical Engineering, Bhutta Group of Institutions, Ludhiana, India ]
  • Sandeep Chakravorty [ Dean and Professor, Department of Electrical Engineering, Baddi University, Baddi, India ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Grid and Distributed Computing
  • 간기
    격월간
  • pISSN
    2005-4262
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.9 No.7

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