A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch

被引:130
作者
Niknam, Taher [1 ]
Azizipanah-Abarghooee, Rasoul [1 ]
Roosta, Alireza [1 ]
Amiri, Babak [2 ]
机构
[1] Shiraz Univ Technol, Dept Elect & Elect Engn, Shiraz, Iran
[2] Univ Sydney, Fac Engn & IT, Sydney, NSW 2006, Australia
关键词
Combined heat and power unit; Dynamic economic emission dispatch; Enhanced firefly algorithm; Pareto-optimal front; Spinning reserve constraint; PARTICLE SWARM OPTIMIZATION; EVOLUTIONARY ALGORITHMS; UNIT COMMITMENT; SYSTEMS; CHP; SQP;
D O I
10.1016/j.energy.2012.02.041
中图分类号
O414.1 [热力学];
学科分类号
摘要
Combined heat and power units are playing an ever increasing role in conventional power stations due to advantages such as reduced emissions and operational cost savings. This paper investigates a more practical formulation of the complex non-convex, non-smooth and non-linear multi-objective dynamic economic emission dispatch that incorporates combined heat and power units. Integrating these types of units, and their power ramp constraints, require an efficient tool to cope with the joint characteristics of power and heat. Unlike previous approaches, the spinning reserve requirements of this system are clearly formulated in the problem. In this way, a new multi-objective optimisation based on an enhanced firefly algorithm is proposed to achieve a set of non-dominated (Pareto-optimal) solutions. A new tuning parameter based on a chaotic mechanism and novel self adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The numerical results demonstrate how the proposed framework was applied in real time studies. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:530 / 545
页数:16
相关论文
共 44 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 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
[3]  
Akbari R, 2011, THESIS U SHIRAZ IRAN
[4]  
[Anonymous], 2013, Power generation, operation, and control
[5]  
Apostolopoulos T., 2011, International Journal of Combinatorics
[6]   A hybrid EP and SQP for dynamic economic dispatch with nonsmooth fuel cost function [J].
Attaviriyanupap, P ;
Kita, H ;
Tanaka, E ;
Hasegawa, J .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) :411-416
[7]   Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method [J].
Azizipanah-Abarghooee, Rasoul ;
Niknam, Taher ;
Roosta, Alireza ;
Malekpour, Ahmad Reza ;
Zare, Mohsen .
ENERGY, 2012, 37 (01) :322-335
[8]   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
[9]   Bee colony optimization for combined heat and power economic dispatch [J].
Basu, M. .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (11) :13527-13531
[10]   Dynamic Economic Emission Dispatch Using Evolutionary Programming and Fuzzy Satisfying Method [J].
Basu, Mousumi .
INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2007, 8 (04)