Cuckoo Search Algorithm with Interactive learning for Economic Dispatch
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- 英文论文题名：Cuckoo Search Algorithm with Interactive learning for Economic Dispatch
- 论文作者：Jian Zhao ; Shixin Liu ; Yifan Wang
- 英文论文作者：Jian Zhao ; Shixin Liu ; Yifan Wang ; Collage of Information Science and Engineering ; Northeastern University ; School of Science ; University of Science and Technology
- 年：2017
- 作者机构：Collage of Information Science and Engineering,Northeastern University;School of Science,University of Science and Technology,Liaoning,Anshan;
- 英文论文关键词：Cuckoo search algorithm ; Economic dispatch ; Interactive learning ; Linear decreasing probability ; Prohibited operating zones ; Valve point effect ; Ramp rate limits ; Power balance
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TM73
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：346k
- 原文格式：D
- 会议级别：全国
摘要
This paper presents a proposed cuckoo search algorithm with interactive learning and linear decreasing probability strategy(CSIL) to solve the economic dispatch problem with power balance,prohibited operating zones,valve point effect,and ramp rate.In the new approach,interactive learning strategy helps the nest to exchange good information from each other.Meanwhile,the linear decreasing probability is used to balance exploration and exploitation of the algorithm.The effectiveness of the CSIL algorithm has been verified on different test systems.Simulation results indicate that the CSIL algorithm performs better than,or at least comparable to state-of-the-art methods from literature.
This paper presents a proposed cuckoo search algorithm with interactive learning and linear decreasing probability strategy(CSIL) to solve the economic dispatch problem with power balance,prohibited operating zones,valve point effect,and ramp rate.In the new approach,interactive learning strategy helps the nest to exchange good information from each other.Meanwhile,the linear decreasing probability is used to balance exploration and exploitation of the algorithm.The effectiveness of the CSIL algorithm has been verified on different test systems.Simulation results indicate that the CSIL algorithm performs better than,or at least comparable to state-of-the-art methods from literature.
This paper presents a proposed cuckoo search algorithm with interactive learning and linear decreasing probability strategy(CSIL) to solve the economic dispatch problem with power balance,prohibited operating zones,valve point effect,and ramp rate.In the new approach,interactive learning strategy helps the nest to exchange good information from each other.Meanwhile,the linear decreasing probability is used to balance exploration and exploitation of the algorithm.The effectiveness of the CSIL algorithm has been verified on different test systems.Simulation results indicate that the CSIL algorithm performs better than,or at least comparable to state-of-the-art methods from literature.
引文
1.Wood Aj,W.B.,Powert generation,operation and control.3rd ed.2013,New York:John Wiley&Sons Press.
2.Dodu,J.C.,et al.,An optimal formulation and solution of short-range operating problems for a power system with flow constraints.Proceedings of the IEEE,1972.60(1):p.54-63.
3.Ding,T.,et al.,A Bi-Level Branch and Bound Method for Economic Dispatch With Disjoint Prohibited Zones Considering Network Losses.IEEE Transactions on Power Systems,2015.30(6):p.2841-2855.
4.Po-Hung,C.and C.Hong-Chan,Large-scale economic dispatch by genetic algorithm.IEEE Transactions on Power Systems,1995.10(4):p.1919-1926.
5.Chaturvedi,K.T.,M.Pandit,and L.Srivastava,Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch.IEEE Transactions on Power Systems,2008.23(3):p.1079-1087.
6.Niknam,T.,H.D.Mojarrad,and H.Z.Meymand,Non-smooth economic dispatch computation by fuzzy and self adaptive particle swarm optimization.Applied Soft Computing,2011.11(2):p.2805-2817.
7.Hosseinnezhad,V.,et al.,Species-based Quantum Particle Swarm Optimization for economic load dispatch.International Journal of Electrical Power&Energy Systems,2014.63:p.311-322.
8.Sun,J.,et al.,Solving the Power Economic Dispatch Problem With Generator Constraints by Random Drift Particle Swarm Optimization.IEEE Transactions on Industrial Informatics,2014.10(1):p.222-232.
9.Noman,N.and H.Iba,Differential evolution for economic load dispatch problems.Electric Power Systems Research,2008.78(8):p.1322-1331.
10.Yang,X.S.and S.Deb.Cuckoo Search via Levy Flights,in Nature&Biologically Inspired Computing,2009.NaBIC 2009.World Congress on.2010.
11.Yang,X.S.and S.Deb,Engineering Optimisation by Cuckoo Search.International Journal of Mathematical Modelling&Numerical Optimisation,2010.1(4):p.330-343.
12.Yang,X.S.,Nature-Inspired Metaheuristic Algorithms.2010:Luniver Press.
13.Walton,S.,et al.,Modified cuckoo search:A new gradient free optimisation algorithm.Chaos,Solitons&Fractals,2011.44(9):p.710-718.
14.Valian,E.,S.Mohanna,and S.Tavakoli,Improved Cuckoo Search Algorithm for Feed forward Neural Network Training.International Journal of Artificial Intelligence&Applications,2011.2(3):p.36-43.
15.Victoire,T.A.A.and A.E.Jeyakumar,Hybrid PSO-SQP for economic dispatch with valve-point effect.Electric Power Systems Research,2004.71(1):p.51-59.
16.Mantegna,R.N.,Fast,accurate algorithm for numerical simulation of Levy stable stochastic processes.Physical Review E,1994.49(5):p.4677-4683.
17.Vo,D.N.,P.Schegner,and W.Ongsakul,Cuckoo search algorithm for non-convex economic dispatch.IET Generation,Transmission&Distribution,2013.7(6):p.645-654.
18.Basu,M.and A.Chowdhury,Cuckoo search algorithm for economic dispatch.Energy,2013.60:p.99-108.
19.Adarsh,B.R.,et al.,Economic dispatch using chaotic bat algorithm.Energy,2016.96:p.666-675.
20.Secui,D.C.,A new modified artificial bee colony algorithm for the economic dispatch problem.Energy Conversion and Management,2015.89:p.43-62.
21.Selvakumar,A.I.and K.Thanushkodi,A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems.IEEE Transactions on Power Systems,2007.22(1):p.42-51.
22.Pothiya,S.,I.Ngamroo,and W.Kongprawechnon,Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints.Energy Conversion and Management,2008.49(4):p.506-516.
23.Wang,L.and L.-p.Li,An effective differential harmony search algorithm for the solving non-convex economic load dispatch problems.International Journal of Electrical Power&Energy Systems,2013.44(1):p.832-843.
24.Panigrahi,B.K.,et al.,A clonal algorithm to solve economic load dispatch.Electric Power Systems Research,2007.77(10):p.1381-1389.
25.Zhan,J.,et al.,Economic Dispatch With Non-Smooth Objectives-Part II:Dimensional Steepest Decline Method.IEEE Transactions on Power Systems,2015.30(2):p.722-733.
26.Chaturvedi,K.T.,M.Pandit,and L.Srivastava,Particle swarm optimization with time varying acceleration coefficients for non-convex economic power dispatch.International Journal of Electrical Power&Energy Systems,2009.31(6):p.249-257.
27.Wang,Y.,B.Li,and B.Yuan,Hybrid of comprehensive learning particle swarm optimization and SQP algorithm for large scale economic load dispatch optimization of power system.Science China Information Sciences,2010.53(8):p.1566-1573.
28.Subbaraj,P.,R.Rengaraj,and S.Salivahanan,Enhancement of Self-adaptive real-coded genetic algorithm using Taguchi method for Economic dispatch problem.Applied Soft Computing,2011.11(1):p.83-92.
29.dosSantosCoelho,L.and V.C.Mariani,Combining of Chaotic Differential Evolution and Quadratic Programming for Economic Dispatch Optimization With Valve-Point Effect.IEEE Transactions on Power Systems,2006.21(2):p.989-996.
30.Yang,X.-S.,S.S.Sadat Hosseini,and A.H.Gandomi,Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect.Applied Soft Computing,2012.12(3):p.1180-1186.
31.Srinivasa Reddy,A.and K.Vaisakh,Shuffled differential evolution for large scale economic dispatch.Electric Power Systems Research,2013.96:p.237-245.
32.Kumar,R.,D.Sharma,and A.Sadu,A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch.International Journal of Electrical Power&Energy Systems,2011.33(1):p.115-123.
33.Gaing,Z.L.,Particle swarm optimization to solving the economic dispatch considering the generator constraints.IEEE Transactions on Power Systems,2003.18(3):p.1187-1195.
34.Gaing,Z.L.,Closure to"Discussion of"Particle Swarm Optimization to Solving the Economic Dispatch Considering the Generator Constraints'".IEEE Transactions on Power Systems,2004.19(4):p.2122-2123.
35.Sinha,N.,R.Chakrabarti,and P.K.Chattopadhyay,Evolutionary programming techniques for economic load dispatch.IEEE Transactions on Evolutionary Computation,2003.7(1):p.83-94.
2.Dodu,J.C.,et al.,An optimal formulation and solution of short-range operating problems for a power system with flow constraints.Proceedings of the IEEE,1972.60(1):p.54-63.
3.Ding,T.,et al.,A Bi-Level Branch and Bound Method for Economic Dispatch With Disjoint Prohibited Zones Considering Network Losses.IEEE Transactions on Power Systems,2015.30(6):p.2841-2855.
4.Po-Hung,C.and C.Hong-Chan,Large-scale economic dispatch by genetic algorithm.IEEE Transactions on Power Systems,1995.10(4):p.1919-1926.
5.Chaturvedi,K.T.,M.Pandit,and L.Srivastava,Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch.IEEE Transactions on Power Systems,2008.23(3):p.1079-1087.
6.Niknam,T.,H.D.Mojarrad,and H.Z.Meymand,Non-smooth economic dispatch computation by fuzzy and self adaptive particle swarm optimization.Applied Soft Computing,2011.11(2):p.2805-2817.
7.Hosseinnezhad,V.,et al.,Species-based Quantum Particle Swarm Optimization for economic load dispatch.International Journal of Electrical Power&Energy Systems,2014.63:p.311-322.
8.Sun,J.,et al.,Solving the Power Economic Dispatch Problem With Generator Constraints by Random Drift Particle Swarm Optimization.IEEE Transactions on Industrial Informatics,2014.10(1):p.222-232.
9.Noman,N.and H.Iba,Differential evolution for economic load dispatch problems.Electric Power Systems Research,2008.78(8):p.1322-1331.
10.Yang,X.S.and S.Deb.Cuckoo Search via Levy Flights,in Nature&Biologically Inspired Computing,2009.NaBIC 2009.World Congress on.2010.
11.Yang,X.S.and S.Deb,Engineering Optimisation by Cuckoo Search.International Journal of Mathematical Modelling&Numerical Optimisation,2010.1(4):p.330-343.
12.Yang,X.S.,Nature-Inspired Metaheuristic Algorithms.2010:Luniver Press.
13.Walton,S.,et al.,Modified cuckoo search:A new gradient free optimisation algorithm.Chaos,Solitons&Fractals,2011.44(9):p.710-718.
14.Valian,E.,S.Mohanna,and S.Tavakoli,Improved Cuckoo Search Algorithm for Feed forward Neural Network Training.International Journal of Artificial Intelligence&Applications,2011.2(3):p.36-43.
15.Victoire,T.A.A.and A.E.Jeyakumar,Hybrid PSO-SQP for economic dispatch with valve-point effect.Electric Power Systems Research,2004.71(1):p.51-59.
16.Mantegna,R.N.,Fast,accurate algorithm for numerical simulation of Levy stable stochastic processes.Physical Review E,1994.49(5):p.4677-4683.
17.Vo,D.N.,P.Schegner,and W.Ongsakul,Cuckoo search algorithm for non-convex economic dispatch.IET Generation,Transmission&Distribution,2013.7(6):p.645-654.
18.Basu,M.and A.Chowdhury,Cuckoo search algorithm for economic dispatch.Energy,2013.60:p.99-108.
19.Adarsh,B.R.,et al.,Economic dispatch using chaotic bat algorithm.Energy,2016.96:p.666-675.
20.Secui,D.C.,A new modified artificial bee colony algorithm for the economic dispatch problem.Energy Conversion and Management,2015.89:p.43-62.
21.Selvakumar,A.I.and K.Thanushkodi,A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems.IEEE Transactions on Power Systems,2007.22(1):p.42-51.
22.Pothiya,S.,I.Ngamroo,and W.Kongprawechnon,Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints.Energy Conversion and Management,2008.49(4):p.506-516.
23.Wang,L.and L.-p.Li,An effective differential harmony search algorithm for the solving non-convex economic load dispatch problems.International Journal of Electrical Power&Energy Systems,2013.44(1):p.832-843.
24.Panigrahi,B.K.,et al.,A clonal algorithm to solve economic load dispatch.Electric Power Systems Research,2007.77(10):p.1381-1389.
25.Zhan,J.,et al.,Economic Dispatch With Non-Smooth Objectives-Part II:Dimensional Steepest Decline Method.IEEE Transactions on Power Systems,2015.30(2):p.722-733.
26.Chaturvedi,K.T.,M.Pandit,and L.Srivastava,Particle swarm optimization with time varying acceleration coefficients for non-convex economic power dispatch.International Journal of Electrical Power&Energy Systems,2009.31(6):p.249-257.
27.Wang,Y.,B.Li,and B.Yuan,Hybrid of comprehensive learning particle swarm optimization and SQP algorithm for large scale economic load dispatch optimization of power system.Science China Information Sciences,2010.53(8):p.1566-1573.
28.Subbaraj,P.,R.Rengaraj,and S.Salivahanan,Enhancement of Self-adaptive real-coded genetic algorithm using Taguchi method for Economic dispatch problem.Applied Soft Computing,2011.11(1):p.83-92.
29.dosSantosCoelho,L.and V.C.Mariani,Combining of Chaotic Differential Evolution and Quadratic Programming for Economic Dispatch Optimization With Valve-Point Effect.IEEE Transactions on Power Systems,2006.21(2):p.989-996.
30.Yang,X.-S.,S.S.Sadat Hosseini,and A.H.Gandomi,Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect.Applied Soft Computing,2012.12(3):p.1180-1186.
31.Srinivasa Reddy,A.and K.Vaisakh,Shuffled differential evolution for large scale economic dispatch.Electric Power Systems Research,2013.96:p.237-245.
32.Kumar,R.,D.Sharma,and A.Sadu,A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch.International Journal of Electrical Power&Energy Systems,2011.33(1):p.115-123.
33.Gaing,Z.L.,Particle swarm optimization to solving the economic dispatch considering the generator constraints.IEEE Transactions on Power Systems,2003.18(3):p.1187-1195.
34.Gaing,Z.L.,Closure to"Discussion of"Particle Swarm Optimization to Solving the Economic Dispatch Considering the Generator Constraints'".IEEE Transactions on Power Systems,2004.19(4):p.2122-2123.
35.Sinha,N.,R.Chakrabarti,and P.K.Chattopadhyay,Evolutionary programming techniques for economic load dispatch.IEEE Transactions on Evolutionary Computation,2003.7(1):p.83-94.