An NSGA-III algorithm for solving multi-objective economic/environmental dispatch problem

被引:59
作者
Bhesdadiya, Rajnikant H. [1 ]
Trivedi, Indrajit N. [2 ]
Jangir, Pradeep [1 ]
Jangir, Narottam [3 ]
Kumar, Arvind [4 ]
机构
[1] Lukhdhirji Engn Coll, Dept Elect Engn, Morbi 363641, Gujarat, India
[2] Govt Engn Coll, Dept Elect Engn, Gandhinagar 389001, Gujarat, India
[3] Govt Engn Coll, Dept Elect Engn, Bikaner 334004, Rajasthan, India
[4] Univ Western Australia, Nedlands, WA, Australia
关键词
emission constrained economic dispatch; NSGA-III; valve point loading effect; meta-heuristic; multi-objective;
D O I
10.1080/23311916.2016.1269383
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The main ambition of utility is to provide continuous reliable supply to customers, satisfying power balance, transmission loss while generators are allowed to be operated within rated limits. Meanwhile, achieving this from fossil fuel fired power plant emission value and fuel cost should be as less as possible. An allowable deviation in fuel cost and feasible tolerance in fuel cost has been additively called as multi objective combined economic emission dispatch (MOCEED) problem. MOCEED problem is applied to newly proposed non dominated sorting genetic algorithm-III (NSGA-III). NSGA-III method is really powerful to handle problems with non-linear characteristics as well as having many objectives. The proposed NSGA-III is firstly applied to unconstraint/constraints multi-objective test functions then applied to solve MOCEED problem with 6-generation unit, IEEE 118 bus 14 generating unit system with a smooth quadratic fuel/emission objective functions and 10-unit with non-smooth/valve point loading effect test system. Statistical results of MOCEED problem obtained by NSGA-III is compared with other well-known techniques proposed in recent literature, validates the effectiveness of proposed approach.
引用
收藏
页数:23
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[1]   Scenario-based dynamic economic emission dispatch considering load and wind power uncertainties [J].
Aghaei, Jamshid ;
Niknam, Taher ;
Azizipanah-Abarghooee, Rasoul ;
Arroyo, Jose M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2013, 47 :351-367
[2]   Artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch problem [J].
Aydin, Dogan ;
Ozyon, Serdar ;
Yasar, Celal ;
Liao, Tianjun .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 54 :144-153
[3]   Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II [J].
Basu, M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (02) :140-149
[4]   Economic environmental dispatch using multi-objective differential evolution [J].
Basu, M. .
APPLIED SOFT COMPUTING, 2011, 11 (02) :2845-2853
[5]  
Bhoye M, 2016, 2016 IEEE STUDENTS' CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER SCIENCE (SCEECS)
[6]   SECURITY-CONSTRAINED MULTIOBJECTIVE GENERATION DISPATCH USING BICRITERION GLOBAL OPTIMIZATION [J].
CHANG, CS ;
WONG, KP ;
FAN, B .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1995, 142 (04) :406-414
[7]   Solution of combined economic and emission dispatch problems of power systems by an opposition-based harmony search algorithm [J].
Chatterjee, A. ;
Ghoshal, S. P. ;
Mukherjee, V. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 39 (01) :9-20
[8]   A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization [J].
Cheng, Ran ;
Jin, Yaochu ;
Olhofer, Markus ;
Sendhoff, Bernhard .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2016, 20 (05) :773-791
[9]   Handling multiple objectives with particle swarm optimization [J].
Coello, CAC ;
Pulido, GT ;
Lechuga, MS .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2004, 8 (03) :256-279
[10]   An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints [J].
Deb, Kalyanmoy ;
Jain, Himanshu .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2014, 18 (04) :577-601