A Novel Strategy-Based Hybrid Binary Artificial Bee Colony Algorithm for Unit Commitment Problem

In this paper, a hybrid approach based on a novel binary artificial bee colony (NBABC) algorithm and local search (LS) is developed to solve the unit commitment problem (UCP). Also, the ramp rate constraints are taken into account in the solution of UCP by performing conventional economic dispatch w...

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Veröffentlicht in:Arabian Journal for Science and Engineering Jg. 40; H. 5; S. 1455 - 1469
Hauptverfasser: Singhal, Prateek K., Naresh, R., Sharma, Veena
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2015
Schlagworte:
Algorithms
Convergence
Engineering
Humanities and Social Sciences
multidisciplinary
Optimization
Research Article - Electrical Engineering
Robustness
Scheduling
Science
Strings
Swarm intelligence
Unit commitment
Local search
Artificial bee colony
Dynamic economic dispatch
Unit commitment
ISSN:1319-8025, 2191-4281
Online-Zugang:Volltext
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Abstract In this paper, a hybrid approach based on a novel binary artificial bee colony (NBABC) algorithm and local search (LS) is developed to solve the unit commitment problem (UCP). Also, the ramp rate constraints are taken into account in the solution of UCP by performing conventional economic dispatch with modifying unit generating capacities over the entire scheduling time horizon. The proposed NBABC–LS method differs from its counterparts in three main aspects: (i) it utilizes a novel strategy which measures the dissimilarity between two binary strings for generating the new binary strings for UCP; (ii) it uses an intelligent scout bee phase; (iii) A LS module is hybridized with the NBABC algorithm. These modifications result in three major advantages: (i) it avoids the problem of slow and premature convergence and thus does not fall into the local optimum solutions; (ii) it can quickly find the near global optimum solution for UCP; (iii) accuracy and robustness of the solution are achieved. The proposed approach is successfully applied to the test systems up to 100 thermal units over 24-h scheduling time horizon and the real Turkish interconnected power system consisting of eight thermal units over 8-h scheduling time horizon. The obtained results confirm the quality solution in terms of total generation cost compared with the other methods reported in the literature.
AbstractList In this paper, a hybrid approach based on a novel binary artificial bee colony (NBABC) algorithm and local search (LS) is developed to solve the unit commitment problem (UCP). Also, the ramp rate constraints are taken into account in the solution of UCP by performing conventional economic dispatch with modifying unit generating capacities over the entire scheduling time horizon. The proposed NBABC-LS method differs from its counterparts in three main aspects: (i) it utilizes a novel strategy which measures the dissimilarity between two binary strings for generating the new binary strings for UCP; (ii) it uses an intelligent scout bee phase; (iii) A LS module is hybridized with the NBABC algorithm. These modifications result in three major advantages: (i) it avoids the problem of slow and premature convergence and thus does not fall into the local optimum solutions; (ii) it can quickly find the near global optimum solution for UCP; (iii) accuracy and robustness of the solution are achieved. The proposed approach is successfully applied to the test systems up to 100 thermal units over 24-h scheduling time horizon and the real Turkish interconnected power system consisting of eight thermal units over 8-h scheduling time horizon. The obtained results confirm the quality solution in terms of total generation cost compared with the other methods reported in the literature.
Author Naresh, R.
Singhal, Prateek K.
Sharma, Veena
Author_xml – sequence: 1
  givenname: Prateek K.
  surname: Singhal
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  organization: Department of Electrical Engineering, National Institute of Technology
– sequence: 2
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  surname: Naresh
  fullname: Naresh, R.
  email: rnareshnith@gmail.com
  organization: Department of Electrical Engineering, National Institute of Technology
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  givenname: Veena
  surname: Sharma
  fullname: Sharma, Veena
  organization: Department of Electrical Engineering, National Institute of Technology
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Cites_doi 10.1016/j.ijepes.2013.01.007
10.1109/TPWRS.2009.2021216
10.1109/TPWRS.2014.2306933
10.1109/59.801925
10.1016/j.ijepes.2014.04.028
10.1109/59.260859
10.1109/59.119267
10.1080/15325000600561589
10.1007/s13369-014-1389-8
10.1016/j.asoc.2014.05.029
10.1016/j.asoc.2007.05.007
10.1109/TPWRS.2009.2021220
10.1109/TPWRS.2011.2158010
10.1109/TPWRS.2013.2288933
10.1109/TPWRS.2005.860922
10.1007/s13369-014-1218-0
10.1016/j.ijepes.2012.10.042
10.1016/j.asoc.2011.08.038
10.1109/60.222703
10.1007/s13369-012-0217-2
10.1007/s13369-013-0560-y
10.1016/j.ijepes.2013.08.020
10.1016/j.ijepes.2012.08.046
10.1109/ICCSCE.2012.6487175
10.1007/s13369-012-0221-6
10.1016/j.epsr.2011.09.022
10.1109/59.485989
10.1007/s10898-007-9149-x
10.1016/j.eswa.2008.06.039
10.1016/j.epsr.2013.10.012
10.1109/TPWRS.2003.811000
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Keywords Local search
Artificial bee colony
Dynamic economic dispatch
Unit commitment
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References VianaA.PedrosoJ.P.A new MILP-based approach for unit commitment in power production planningInt. J. Electr. Power Energy Syst.201344997100510.1016/j.ijepes.2012.08.046
LauT.W.ChungC.Y.WongK.P.ChungT.S.HoS.L.Quantum-inspired evolutionary algorithm approach for unit commitmentIEEE Trans. Power Syst.20092431503151210.1109/TPWRS.2009.2021220
ArifS.MohammediR.HellalA.ChouchaA.A memory simulated annealing method to the unit commitment problem with ramp constraintsArab. J. Sci. Eng.2012371021103110.1007/s13369-012-0217-21296.90140
UyarA.S.TurkayB.Evolutionary algorithms for the unit commitment problemTurk. J. Elec. Eng.2008163239255
HadjiM.M.VahidiB.A solution to the unit commitment problem using imperialistic competition algorithmIEEE Trans. Power Syst.201227111712410.1109/TPWRS.2011.2158010
KhorasaniJ.A new heuristic approach for unit commitment problem using particle swarm optimizationArab. J. Sci. Eng.2012371033104210.1007/s13369-012-0221-61296.90147
OuyangZ.ShahidehpourS.M.An intelligent dynamic programming for unit commitment applicationIEEE Trans. Power Syst.1991631203120910.1109/59.119267
ChowdhuryN.BillintonR.Interruptible load considerations in spinning reserve assessment of isolated and interconnected generating systemsProc. Inst. Elect. Eng. Part C19901372159167
LuP.ZhouJ.ZhangH.ZhangR.WangC.Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effectsInt. J. Electr. Power Energy Syst.20146213014310.1016/j.ijepes.2014.04.028
LiX.LiT.WeiJ.WangG.YehW.W.G.Hydro unit commitment via mixed integer linear programming: a case study of the three gorges projectChina. IEEE Trans. Power Syst.20142931232124110.1109/TPWRS.2013.2288933
ElaiwA.M.ShehataA.M.AlghamdiM.A.A model predictive control approach to combined heat and power dynamic economic dispatch problemArab. J. Sci. Eng.2014397117712510.1007/s13369-014-1218-0
FengX.LiaoY.A new lagrangian multiplier update approach for Lagrangian relaxation based unit commitmentElectr. Power Compon. Syst.20063485786610.1080/15325000600561589
KazarlisS.A.BakirtzisA.G.PetridisV.A genetic algorithm solution to the unit commitment problemIEEE Trans. Power Syst.1996111839210.1109/59.485989
HarisonD.S.SreerengarajaT.Swarm intelligence to the solution of profit-based unit commitment problem with emission limitationsArab. J. Sci. Eng.2013381415142510.1007/s13369-013-0560-y
WoodA.J.WollenbergB.F.Power Generation, Operation and Control2007New YorkWiley
PatraS.GoswamiS.K.GoswamiB.Fuzzy and simulated annealing based dynamic programming for the unit commitment problemExp. Syst. Appl.2009365081508610.1016/j.eswa.2008.06.039
AbarghooeeR.A.NiknamT.BavafaF.ZareM.Short-term scheduling of thermal power systems using hybrid gradient based modified teaching–learning optimizer with black hole algorithmElectr. Power Syst. Res.2014108163410.1016/j.epsr.2013.10.012
EslamianM.HosseinianS.H.VahidiB.Bacterial foraging-based solution to the unit commitment problemIEEE Trans. Power Syst.20092431478148810.1109/TPWRS.2009.2021216
PourjamalY.RavadaneghS.N.HSA based solution to the UC problemInt. J. Electr. Power Energy Syst.20134621122010.1016/j.ijepes.2012.10.042
JusteK.A.KitaH.TanakaE.HasegawaJ.An evolutionary programming solution to the unit commitment problemIEEE Trans. Power Syst.19991441452145910.1109/59.801925
YuanX.JiB.ZhangS.TianH.HouY.A new approach for unit commitment problem via binary gravitational search algorithmAppl. Soft Comput.20142224926010.1016/j.asoc.2014.05.029
WangM.Q.GooiH.B.ChenS.X.LuS.A mixed integer quadratic programming for dynamic economic dispatch with valve point effectIEEE Trans. Power Syst.20142952097210610.1109/TPWRS.2014.2306933
Saleem, N.; Ahmad, A.; Zafar, S.: A modified differential evolution algorithm for the solution of a large-scale unit commitment problem. Arab. J. Sci. Eng. (2014). doi:10.1007/s13369-014-1389-8
ChandrasekaranK.HemamaliniS.SimonS.P.PadhyN.P.Thermal unit commitment using binary/real coded artificial bee colony algorithmElectr. Power Syst. Res.20128410911910.1016/j.epsr.2011.09.022
ChenC.L.WangS.C.Branch-and-bound scheduling for thermal generating unitsIEEE Trans. Energy Convers.19938218418910.1109/60.222703
SimopoulosD.N.KavatzaS.D.VournasC.D.Unit commitment by an enhanced simulated annealing algorithmIEEE Trans. Power Syst.2006211687610.1109/TPWRS.2005.860922
KashanM.H.NahavandiN.KashanA.H.DisABC: a new artificial bee colony algorithm for binary optimizationAppl. Soft Comput.20121234235210.1016/j.asoc.2011.08.038
KarabogaD.BasturkB.On the performance of artificial bee colony (ABC) algorithmAppl. Soft Comput.2008868769710.1016/j.asoc.2007.05.007
WangC.ShahidehpourS.M.Effects of ramp-rate limits on unit commitment and economic dispatchIEEE Trans. Power Syst.1993831341135010.1109/59.260859
KangW.Y.ChengH.C.LiangL.C.Resolution of the unit commitment problems by using the hybrid Taguchi-ant colony system algorithmInt. J. Electr. Power Energy Syst.20134918819810.1016/j.ijepes.2013.01.007
SenjyuT.ShimabukuroK.UezatoK.FunabashiT.A fast technique for unit commitment problem by extended priority listIEEE Trans. Power Syst.200318288288810.1109/TPWRS.2003.811000
KarabogaD.BasturkB.A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithmJ. Global Optim.20073945947110.1007/s10898-007-9149-x1149.901862346178
SaravananB.VasudevanE.R.KothariD.P.Unit commitment problem solution using invasive weed optimization algorithmInt. J. Electr. Power Energy Syst.201455212810.1016/j.ijepes.2013.08.020
Abro, A.G.; Saleh, J.M.: Intelligent scout-bee based artificial bee colony optimization algorithm. In: IEEE International Conference on Control System, Computing and Engineering, pp. 380–385 (2012)
SaadatH.Power System Analysis2002IndiaTata McGraw Hill
1610_CR35
B. Saravanan (1610_CR24) 2014; 55
D. Karaboga (1610_CR29) 2007; 39
T.W. Lau (1610_CR16) 2009; 24
A.M. Elaiw (1610_CR4) 2014; 39
A.J. Wood (1610_CR1) 2007
T. Senjyu (1610_CR5) 2003; 18
R.A. Abarghooee (1610_CR28) 2014; 108
A. Viana (1610_CR8) 2013; 44
A.S. Uyar (1610_CR15) 2008; 16
C.L. Chen (1610_CR9) 1993; 8
M. Eslamian (1610_CR17) 2009; 24
D.S. Harison (1610_CR20) 2013; 38
C. Wang (1610_CR25) 1993; 8
J. Khorasani (1610_CR19) 2012; 37
Y. Pourjamal (1610_CR21) 2013; 46
S. Arif (1610_CR13) 2012; 37
S.A. Kazarlis (1610_CR11) 1996; 11
P. Lu (1610_CR3) 2014; 62
M.M. Hadji (1610_CR18) 2012; 27
K. Chandrasekaran (1610_CR31) 2012; 84
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D. Karaboga (1610_CR30) 2008; 8
H. Saadat (1610_CR33) 2002
M.Q. Wang (1610_CR2) 2014; 29
S. Patra (1610_CR26) 2009; 36
W.Y. Kang (1610_CR27) 2013; 49
Z. Ouyang (1610_CR6) 1991; 6
X. Feng (1610_CR10) 2006; 34
X. Yuan (1610_CR22) 2014; 22
D.N. Simopoulos (1610_CR14) 2006; 21
N. Chowdhury (1610_CR32) 1990; 137
M.H. Kashan (1610_CR34) 2012; 12
K.A. Juste (1610_CR12) 1999; 14
X. Li (1610_CR7) 2014; 29
References_xml – reference: KarabogaD.BasturkB.On the performance of artificial bee colony (ABC) algorithmAppl. Soft Comput.2008868769710.1016/j.asoc.2007.05.007
– reference: KazarlisS.A.BakirtzisA.G.PetridisV.A genetic algorithm solution to the unit commitment problemIEEE Trans. Power Syst.1996111839210.1109/59.485989
– reference: VianaA.PedrosoJ.P.A new MILP-based approach for unit commitment in power production planningInt. J. Electr. Power Energy Syst.201344997100510.1016/j.ijepes.2012.08.046
– reference: LuP.ZhouJ.ZhangH.ZhangR.WangC.Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effectsInt. J. Electr. Power Energy Syst.20146213014310.1016/j.ijepes.2014.04.028
– reference: HarisonD.S.SreerengarajaT.Swarm intelligence to the solution of profit-based unit commitment problem with emission limitationsArab. J. Sci. Eng.2013381415142510.1007/s13369-013-0560-y
– reference: SaadatH.Power System Analysis2002IndiaTata McGraw Hill
– reference: LauT.W.ChungC.Y.WongK.P.ChungT.S.HoS.L.Quantum-inspired evolutionary algorithm approach for unit commitmentIEEE Trans. Power Syst.20092431503151210.1109/TPWRS.2009.2021220
– reference: FengX.LiaoY.A new lagrangian multiplier update approach for Lagrangian relaxation based unit commitmentElectr. Power Compon. Syst.20063485786610.1080/15325000600561589
– reference: JusteK.A.KitaH.TanakaE.HasegawaJ.An evolutionary programming solution to the unit commitment problemIEEE Trans. Power Syst.19991441452145910.1109/59.801925
– reference: AbarghooeeR.A.NiknamT.BavafaF.ZareM.Short-term scheduling of thermal power systems using hybrid gradient based modified teaching–learning optimizer with black hole algorithmElectr. Power Syst. Res.2014108163410.1016/j.epsr.2013.10.012
– reference: YuanX.JiB.ZhangS.TianH.HouY.A new approach for unit commitment problem via binary gravitational search algorithmAppl. Soft Comput.20142224926010.1016/j.asoc.2014.05.029
– reference: EslamianM.HosseinianS.H.VahidiB.Bacterial foraging-based solution to the unit commitment problemIEEE Trans. Power Syst.20092431478148810.1109/TPWRS.2009.2021216
– reference: ElaiwA.M.ShehataA.M.AlghamdiM.A.A model predictive control approach to combined heat and power dynamic economic dispatch problemArab. J. Sci. Eng.2014397117712510.1007/s13369-014-1218-0
– reference: KarabogaD.BasturkB.A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithmJ. Global Optim.20073945947110.1007/s10898-007-9149-x1149.901862346178
– reference: Saleem, N.; Ahmad, A.; Zafar, S.: A modified differential evolution algorithm for the solution of a large-scale unit commitment problem. Arab. J. Sci. Eng. (2014). doi:10.1007/s13369-014-1389-8
– reference: WangM.Q.GooiH.B.ChenS.X.LuS.A mixed integer quadratic programming for dynamic economic dispatch with valve point effectIEEE Trans. Power Syst.20142952097210610.1109/TPWRS.2014.2306933
– reference: PourjamalY.RavadaneghS.N.HSA based solution to the UC problemInt. J. Electr. Power Energy Syst.20134621122010.1016/j.ijepes.2012.10.042
– reference: ChowdhuryN.BillintonR.Interruptible load considerations in spinning reserve assessment of isolated and interconnected generating systemsProc. Inst. Elect. Eng. Part C19901372159167
– reference: LiX.LiT.WeiJ.WangG.YehW.W.G.Hydro unit commitment via mixed integer linear programming: a case study of the three gorges projectChina. IEEE Trans. Power Syst.20142931232124110.1109/TPWRS.2013.2288933
– reference: KashanM.H.NahavandiN.KashanA.H.DisABC: a new artificial bee colony algorithm for binary optimizationAppl. Soft Comput.20121234235210.1016/j.asoc.2011.08.038
– reference: SenjyuT.ShimabukuroK.UezatoK.FunabashiT.A fast technique for unit commitment problem by extended priority listIEEE Trans. Power Syst.200318288288810.1109/TPWRS.2003.811000
– reference: PatraS.GoswamiS.K.GoswamiB.Fuzzy and simulated annealing based dynamic programming for the unit commitment problemExp. Syst. Appl.2009365081508610.1016/j.eswa.2008.06.039
– reference: ArifS.MohammediR.HellalA.ChouchaA.A memory simulated annealing method to the unit commitment problem with ramp constraintsArab. J. Sci. Eng.2012371021103110.1007/s13369-012-0217-21296.90140
– reference: KangW.Y.ChengH.C.LiangL.C.Resolution of the unit commitment problems by using the hybrid Taguchi-ant colony system algorithmInt. J. Electr. Power Energy Syst.20134918819810.1016/j.ijepes.2013.01.007
– reference: ChenC.L.WangS.C.Branch-and-bound scheduling for thermal generating unitsIEEE Trans. Energy Convers.19938218418910.1109/60.222703
– reference: KhorasaniJ.A new heuristic approach for unit commitment problem using particle swarm optimizationArab. J. Sci. Eng.2012371033104210.1007/s13369-012-0221-61296.90147
– reference: ChandrasekaranK.HemamaliniS.SimonS.P.PadhyN.P.Thermal unit commitment using binary/real coded artificial bee colony algorithmElectr. Power Syst. Res.20128410911910.1016/j.epsr.2011.09.022
– reference: Abro, A.G.; Saleh, J.M.: Intelligent scout-bee based artificial bee colony optimization algorithm. In: IEEE International Conference on Control System, Computing and Engineering, pp. 380–385 (2012)
– reference: HadjiM.M.VahidiB.A solution to the unit commitment problem using imperialistic competition algorithmIEEE Trans. Power Syst.201227111712410.1109/TPWRS.2011.2158010
– reference: WoodA.J.WollenbergB.F.Power Generation, Operation and Control2007New YorkWiley
– reference: OuyangZ.ShahidehpourS.M.An intelligent dynamic programming for unit commitment applicationIEEE Trans. Power Syst.1991631203120910.1109/59.119267
– reference: UyarA.S.TurkayB.Evolutionary algorithms for the unit commitment problemTurk. J. Elec. Eng.2008163239255
– reference: SimopoulosD.N.KavatzaS.D.VournasC.D.Unit commitment by an enhanced simulated annealing algorithmIEEE Trans. Power Syst.2006211687610.1109/TPWRS.2005.860922
– reference: SaravananB.VasudevanE.R.KothariD.P.Unit commitment problem solution using invasive weed optimization algorithmInt. J. Electr. Power Energy Syst.201455212810.1016/j.ijepes.2013.08.020
– reference: WangC.ShahidehpourS.M.Effects of ramp-rate limits on unit commitment and economic dispatchIEEE Trans. Power Syst.1993831341135010.1109/59.260859
– volume: 49
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– volume: 24
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  ident: 1610_CR17
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  doi: 10.1109/TPWRS.2009.2021216
– volume-title: Power Generation, Operation and Control
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– volume: 29
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  year: 2014
  ident: 1610_CR2
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2014.2306933
– volume: 14
  start-page: 1452
  issue: 4
  year: 1999
  ident: 1610_CR12
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.801925
– volume: 62
  start-page: 130
  year: 2014
  ident: 1610_CR3
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2014.04.028
– volume: 8
  start-page: 1341
  issue: 3
  year: 1993
  ident: 1610_CR25
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.260859
– volume: 6
  start-page: 1203
  issue: 3
  year: 1991
  ident: 1610_CR6
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.119267
– volume: 34
  start-page: 857
  year: 2006
  ident: 1610_CR10
  publication-title: Electr. Power Compon. Syst.
  doi: 10.1080/15325000600561589
– ident: 1610_CR23
  doi: 10.1007/s13369-014-1389-8
– volume: 22
  start-page: 249
  year: 2014
  ident: 1610_CR22
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2014.05.029
– volume: 8
  start-page: 687
  year: 2008
  ident: 1610_CR30
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2007.05.007
– volume: 24
  start-page: 1503
  issue: 3
  year: 2009
  ident: 1610_CR16
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2009.2021220
– volume: 27
  start-page: 117
  issue: 1
  year: 2012
  ident: 1610_CR18
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2011.2158010
– volume: 29
  start-page: 1232
  issue: 3
  year: 2014
  ident: 1610_CR7
  publication-title: China. IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2013.2288933
– volume-title: Power System Analysis
  year: 2002
  ident: 1610_CR33
– volume: 21
  start-page: 68
  issue: 1
  year: 2006
  ident: 1610_CR14
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2005.860922
– volume: 39
  start-page: 7117
  year: 2014
  ident: 1610_CR4
  publication-title: Arab. J. Sci. Eng.
  doi: 10.1007/s13369-014-1218-0
– volume: 46
  start-page: 211
  year: 2013
  ident: 1610_CR21
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2012.10.042
– volume: 12
  start-page: 342
  year: 2012
  ident: 1610_CR34
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2011.08.038
– volume: 8
  start-page: 184
  issue: 2
  year: 1993
  ident: 1610_CR9
  publication-title: IEEE Trans. Energy Convers.
  doi: 10.1109/60.222703
– volume: 37
  start-page: 1021
  year: 2012
  ident: 1610_CR13
  publication-title: Arab. J. Sci. Eng.
  doi: 10.1007/s13369-012-0217-2
– volume: 38
  start-page: 1415
  year: 2013
  ident: 1610_CR20
  publication-title: Arab. J. Sci. Eng.
  doi: 10.1007/s13369-013-0560-y
– volume: 55
  start-page: 21
  year: 2014
  ident: 1610_CR24
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2013.08.020
– volume: 44
  start-page: 997
  year: 2013
  ident: 1610_CR8
  publication-title: Int. J. Electr. Power Energy Syst.
  doi: 10.1016/j.ijepes.2012.08.046
– ident: 1610_CR35
  doi: 10.1109/ICCSCE.2012.6487175
– volume: 37
  start-page: 1033
  year: 2012
  ident: 1610_CR19
  publication-title: Arab. J. Sci. Eng.
  doi: 10.1007/s13369-012-0221-6
– volume: 84
  start-page: 109
  year: 2012
  ident: 1610_CR31
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2011.09.022
– volume: 11
  start-page: 83
  issue: 1
  year: 1996
  ident: 1610_CR11
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/59.485989
– volume: 39
  start-page: 459
  year: 2007
  ident: 1610_CR29
  publication-title: J. Global Optim.
  doi: 10.1007/s10898-007-9149-x
– volume: 137
  start-page: 159
  issue: 2
  year: 1990
  ident: 1610_CR32
  publication-title: Proc. Inst. Elect. Eng. Part C
– volume: 36
  start-page: 5081
  year: 2009
  ident: 1610_CR26
  publication-title: Exp. Syst. Appl.
  doi: 10.1016/j.eswa.2008.06.039
– volume: 16
  start-page: 239
  issue: 3
  year: 2008
  ident: 1610_CR15
  publication-title: Turk. J. Elec. Eng.
– volume: 108
  start-page: 16
  year: 2014
  ident: 1610_CR28
  publication-title: Electr. Power Syst. Res.
  doi: 10.1016/j.epsr.2013.10.012
– volume: 18
  start-page: 882
  issue: 2
  year: 2003
  ident: 1610_CR5
  publication-title: IEEE Trans. Power Syst.
  doi: 10.1109/TPWRS.2003.811000
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Snippet In this paper, a hybrid approach based on a novel binary artificial bee colony (NBABC) algorithm and local search (LS) is developed to solve the unit...
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SubjectTerms Algorithms
Convergence
Engineering
Humanities and Social Sciences
multidisciplinary
Optimization
Research Article - Electrical Engineering
Robustness
Scheduling
Science
Strings
Swarm intelligence
Unit commitment
Title A Novel Strategy-Based Hybrid Binary Artificial Bee Colony Algorithm for Unit Commitment Problem
URI https://link.springer.com/article/10.1007/s13369-015-1610-4
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Volume 40
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