Araştırma Makalesi
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Yıl 2019, Cilt: 32 Sayı: 2, 524 - 542, 01.06.2019

Öz

Kaynakça

  • [2]. Hardiansyah, Junaidi, “Solving Economic Load Dispatch problem using particle swarm Optimization Technique”, I.J. Intelligent Systems and Applications, 2012, 12, 12-18.
  • [6]. K. K. MandaI, N. Chakraborty, “Differential Evolution based environmentally constrained Economic Dispatch”, 2008 IEEE.
  • [7]. D. Nelson Jayakumar, P. Venkatesh, “Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem”, Applied Soft Computing 23 (2014) 375–386.
  • [8]. Chatterjee, S.P. Ghoshal “Solution of combined economic and emission dispatch problems of power systems by an opposition-based harmony search algorithm”, Electrical Power and Energy Systems 39 (2012) 9–20.
  • [9]. M. A. Abido, “Multiobjective Evolutionary Algorithms for Electric power dispatch algorithm”, ieee transactions on evolutionary computation, vol. 10, no. 3, june 2006.
  • [10]. B.Y. Qu, J.J. Liang, “Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm”, Information Sciences (2016).
  • [11]. Mostafa Modiri-Delshad, Nasrudin Abd Rahim “Multi-objective Backtracking Search Algorithm for Economic Emission Dispatch Problem”, Applied Soft Computing 2015.
  • [12]. Abd Allah “Hybrid ant optimization system for multiobjective economic emission load dispatch problem under fuzziness”, Swarm and Evolutionary Computation 18 (2014) 11–21.
  • [13]. Celal Yas¸ “A new hybrid approach for nonconvex economic dispatch problem with valve-point effect”, Energy 36 (2011) 5838-45.
  • [14]. Tahir Nadeem Malik, Azzam ul Asar “A new hybrid approach for the solution of nonconvex ED problem with valve-point effects, Electric Power Systems Research 80 (2010) 1128–1136.
  • [15]. Serhat Duman, “A novel modified hybrid PSOGSA based on fuzzy logic for non-convex ED problem with valve-point effect”, Electrical Power and Energy Systems 64 (2015) 121–135.
  • [16]. Meisam Moradi, Ali “Non-Convex Constrained economic dispatch with valve point loading effect using a GWO algorithm”, 6th conference on Thermal Power Plants, janaury 2016, Iran.
  • [17]. Mostafa Modiri-Delshad, “Backtracking search algorithm for solving economic diapatch problems with valve-point effects and multiple fuel optins”, Energy 116 (2016) 637e649.
  • [18]. Zwe-Lee Gaing “Particle Swarm Optimization to Solving the economic dispatch considering the generator constrints”, ieee transactions on power systems, vol. 18, no. 3, august 2003.
  • [19]. Naser Ghorbani, Ebrahim Babaei “Exchange market algorithm for economic load dispatch”, Electrical Power and Energy Systems 75 (2016) 19–27.
  • [20]. Wael Taha Elsayed, Yasser G. Hegazy “Improved Random Drift Particle Swarm Optimization With Self-Adaptive Mechanism for Solving the Power Economic Dispatch Problem”, ieee transactions on industrial informatics, vol. 13, no. 3, june 2017.
  • [21]. Seyedali Mirjalili “The Ant Lion Optimizer”, Advances in Engineering Software 83 (2015) 80–98.

Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints

Yıl 2019, Cilt: 32 Sayı: 2, 524 - 542, 01.06.2019

Öz

This paper presents Ant
Lion Optimization (ALO) algorithm
ffffor solvingfffEconomic Load Dispatch
(ELD) problem
fffwith practical constraints. ALO is a newly developed
optimization algorithm, which draws inspiration from mimics, the hunting
fffmechanism of antlions in
nature. The antlions have a unique hunting mechanism and exhibit high
capability of reaching global optima, exploring the search space to find the
optimal
fffsolution within a low computational time. For
practical ELD problem needs to take care about the characteristics of
generators, and their operational constraints, such as ramp rate limits,
prohibited operating zones, generation operating limits, transmission loss,
valve-point loading and non-linear emission functions. In order to validate the potency of the proposed method, four case
studies are investigated on different 6-unit systems and correlated with
recently published ELD solution methods. The results of the present work shows
that the proposed ALO is dominant than other
methods to finding out optimal results. Stastical analysis
fffof the results among 30
trails has been
fffcarried out to validate the ALO as a highly potent
method. This algorithm
fffis considered to be a promising best alternative
algorithm for solving the ELD problem
ff in power systems.

Kaynakça

  • [2]. Hardiansyah, Junaidi, “Solving Economic Load Dispatch problem using particle swarm Optimization Technique”, I.J. Intelligent Systems and Applications, 2012, 12, 12-18.
  • [6]. K. K. MandaI, N. Chakraborty, “Differential Evolution based environmentally constrained Economic Dispatch”, 2008 IEEE.
  • [7]. D. Nelson Jayakumar, P. Venkatesh, “Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem”, Applied Soft Computing 23 (2014) 375–386.
  • [8]. Chatterjee, S.P. Ghoshal “Solution of combined economic and emission dispatch problems of power systems by an opposition-based harmony search algorithm”, Electrical Power and Energy Systems 39 (2012) 9–20.
  • [9]. M. A. Abido, “Multiobjective Evolutionary Algorithms for Electric power dispatch algorithm”, ieee transactions on evolutionary computation, vol. 10, no. 3, june 2006.
  • [10]. B.Y. Qu, J.J. Liang, “Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm”, Information Sciences (2016).
  • [11]. Mostafa Modiri-Delshad, Nasrudin Abd Rahim “Multi-objective Backtracking Search Algorithm for Economic Emission Dispatch Problem”, Applied Soft Computing 2015.
  • [12]. Abd Allah “Hybrid ant optimization system for multiobjective economic emission load dispatch problem under fuzziness”, Swarm and Evolutionary Computation 18 (2014) 11–21.
  • [13]. Celal Yas¸ “A new hybrid approach for nonconvex economic dispatch problem with valve-point effect”, Energy 36 (2011) 5838-45.
  • [14]. Tahir Nadeem Malik, Azzam ul Asar “A new hybrid approach for the solution of nonconvex ED problem with valve-point effects, Electric Power Systems Research 80 (2010) 1128–1136.
  • [15]. Serhat Duman, “A novel modified hybrid PSOGSA based on fuzzy logic for non-convex ED problem with valve-point effect”, Electrical Power and Energy Systems 64 (2015) 121–135.
  • [16]. Meisam Moradi, Ali “Non-Convex Constrained economic dispatch with valve point loading effect using a GWO algorithm”, 6th conference on Thermal Power Plants, janaury 2016, Iran.
  • [17]. Mostafa Modiri-Delshad, “Backtracking search algorithm for solving economic diapatch problems with valve-point effects and multiple fuel optins”, Energy 116 (2016) 637e649.
  • [18]. Zwe-Lee Gaing “Particle Swarm Optimization to Solving the economic dispatch considering the generator constrints”, ieee transactions on power systems, vol. 18, no. 3, august 2003.
  • [19]. Naser Ghorbani, Ebrahim Babaei “Exchange market algorithm for economic load dispatch”, Electrical Power and Energy Systems 75 (2016) 19–27.
  • [20]. Wael Taha Elsayed, Yasser G. Hegazy “Improved Random Drift Particle Swarm Optimization With Self-Adaptive Mechanism for Solving the Power Economic Dispatch Problem”, ieee transactions on industrial informatics, vol. 13, no. 3, june 2017.
  • [21]. Seyedali Mirjalili “The Ant Lion Optimizer”, Advances in Engineering Software 83 (2015) 80–98.
Toplam 17 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Electrical & Electronics Engineering
Yazarlar

Y.venkata Krishna Reddy 0000-0001-5913-3391

M.damodar Reddy Bu kişi benim

Yayımlanma Tarihi 1 Haziran 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 32 Sayı: 2

Kaynak Göster

APA Reddy, Y. K., & Reddy, M. (2019). Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints. Gazi University Journal of Science, 32(2), 524-542.
AMA Reddy YK, Reddy M. Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints. Gazi University Journal of Science. Haziran 2019;32(2):524-542.
Chicago Reddy, Y.venkata Krishna, ve M.damodar Reddy. “Economic Load Dispatch Problem With Ant Lion Optimization Using Practical Constraints”. Gazi University Journal of Science 32, sy. 2 (Haziran 2019): 524-42.
EndNote Reddy YK, Reddy M (01 Haziran 2019) Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints. Gazi University Journal of Science 32 2 524–542.
IEEE Y. K. Reddy ve M. Reddy, “Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints”, Gazi University Journal of Science, c. 32, sy. 2, ss. 524–542, 2019.
ISNAD Reddy, Y.venkata Krishna - Reddy, M.damodar. “Economic Load Dispatch Problem With Ant Lion Optimization Using Practical Constraints”. Gazi University Journal of Science 32/2 (Haziran 2019), 524-542.
JAMA Reddy YK, Reddy M. Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints. Gazi University Journal of Science. 2019;32:524–542.
MLA Reddy, Y.venkata Krishna ve M.damodar Reddy. “Economic Load Dispatch Problem With Ant Lion Optimization Using Practical Constraints”. Gazi University Journal of Science, c. 32, sy. 2, 2019, ss. 524-42.
Vancouver Reddy YK, Reddy M. Economic Load Dispatch Problem with Ant Lion Optimization Using Practical Constraints. Gazi University Journal of Science. 2019;32(2):524-42.