NSMOOGSA for Solving Combined Economic and Emission Dispatch Problem

被引:0
作者
Bhowmik, Arup Ratan [1 ]
Chakraborty, Ajoy Kumar [1 ]
机构
[1] Natl Inst Technol, Dept Elect Engn, Agartala 799046, Tripura, India
来源
2016 IEEE/PES TRANSMISSION AND DISTRIBUTION CONFERENCE AND EXPOSITION (T&D) | 2016年
关键词
CEED; interactive fuzzy membership approach; multi objective optimization; NSMOOGSA; non dominating sorting; opposition based learning; MULTIOBJECTIVE ENVIRONMENTAL/ECONOMIC DISPATCH; LOAD DISPATCH; POWER DISPATCH; SEARCH ALGORITHM; OPTIMIZATION;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Combined economic and emission dispatch (CEED) is a key challenge for the system operator in the open access regime and is used to operate generators that produce energy in a power plant with least costs as well as least emission simultaneously. Stability issues must, therefore, be considered during CEED. This paper presents a multi-objective formulation of CEED in a power system, with the competing objective functions of minimizing fuel cost and emission. Non-dominated Sorting Multi Objective Opposition based Gravitational Search Algorithm (NSMOOGSA) is used as an optimization tool. Fuzzy decision maker is used to extract the best compromise non-dominated solution. The proposed method has been tested on the IEEE 30-bus system and results are compared with those of the other reported in the recent literature. The quality of the results establishes the efficacy of the proposed approach in solving different CEED problem.
引用
收藏
页数:5
相关论文
共 17 条
[1]   Multiobjective evolutionary algorithms for electric power dispatch problem [J].
Abido, M. A. .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2006, 10 (03) :315-329
[2]   Multiobjective particle swarm optimization for environmental/economic dispatch problem [J].
Abido, M. A. .
ELECTRIC POWER SYSTEMS RESEARCH, 2009, 79 (07) :1105-1113
[3]   A novel multiobjective evolutionary algorithm or environmental/economic power dispatch [J].
Abido, MA .
ELECTRIC POWER SYSTEMS RESEARCH, 2003, 65 (01) :71-81
[4]   A niched Pareto genetic algorithm for multiobjective environmental/economic dispatch [J].
Abido, MA .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2003, 25 (02) :97-105
[5]   Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch [J].
Agrawal, Shubham ;
Panigrahi, B. K. ;
Tiwari, Manoj Kumar .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2008, 12 (05) :529-541
[6]  
Bhowmik A.R., 2014, IEEE INT C GREEN COM, P44
[7]   Solution of optimal power flow using non dominated sorting multi objective opposition based gravitational search algorithm [J].
Bhowmik, Arup Ratan ;
Chakraborty, Ajoy Kumar .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 64 :1237-1250
[8]   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
[9]   New multi-objective stochastic search technique for economic load dispatch [J].
Das, DB ;
Patvardhan, C .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1998, 145 (06) :747-752
[10]   ECONOMIC LOAD DISPATCH MULTIOBJECTIVE OPTIMIZATION PROCEDURES USING LINEAR-PROGRAMMING TECHNIQUES [J].
FARAG, A ;
ALBAIYAT, S ;
CHENG, TC .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1995, 10 (02) :731-738