Discrete particle swarm optimization algorithm for unit commitment

被引:53
|
作者
Gaing, ZL [1 ]
机构
[1] Kao Yuan Inst Technol, Kaohsiung 821, Taiwan
关键词
unit commitment; particle swarm optimization; genetic algorithm;
D O I
10.1109/PES.2003.1267212
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
This paper proposes integrating a discrete binary particle swarm optimization (BPSO) method with the Lambda-iteration method for solving unit commitment (UC) problems. The UC problem is considered as two linked optimization sub-problems: the unit-scheduled problem that can be solved by the BPSO method for the minimization of the transition cost, and the economic dispatch (ED) problem that can be solved by the Lambda-iteration method for the minimization of the production cost. The feasibility of the proposed method is demonstrated for 10 and 26 unit systems, respectively, and the test results are compared with those obtained by the GA method in terms of solution quality and convergence characteristic. The simulation results show that the proposed method is indeed capable of obtaining higher quality solutions.
引用
收藏
页码:418 / 424
页数:7
相关论文
共 50 条
  • [1] An improved particle swarm optimization algorithm for unit commitment
    Zhao, B.
    Guo, C.X.
    Bai, B.R.
    Cao, Y.J.
    [J]. International Journal of Electrical Power and Energy Systems, 2006, 28 (07): : 482 - 490
  • [2] An Improved Particle Swarm Optimization Algorithm for Unit Commitment
    Xiong, Wei
    Li, Mao-jun
    Cheng, Yuan-lin
    [J]. INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL 1, PROCEEDINGS, 2008, : 21 - +
  • [3] An improved particle swarm optimization algorithm for unit commitment
    Zhao, B.
    Guo, C. X.
    Bai, B. R.
    Cao, Y. J.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2006, 28 (07) : 482 - 490
  • [4] Unit commitment optimization based on genetic algorithm and particle swarm optimization hybrid algorithm
    Zhang, Jiong
    Liu, Tian-Qi
    Su, Peng
    Zhang, Xin
    [J]. Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2009, 37 (09): : 25 - 29
  • [5] Unit commitment problem using enhanced particle swarm optimization algorithm
    Xiaohui Yuan
    Anjun Su
    Hao Nie
    Yanbin Yuan
    Liang Wang
    [J]. Soft Computing, 2011, 15 : 139 - 148
  • [6] Unit commitment problem using enhanced particle swarm optimization algorithm
    Yuan, Xiaohui
    Su, Anjun
    Nie, Hao
    Yuan, Yanbin
    Wang, Liang
    [J]. SOFT COMPUTING, 2011, 15 (01) : 139 - 148
  • [7] A solution to particle swarm optimization algorithm with adaptive inertia weight for unit commitment
    Chang, Wen-Ping
    Yu, Hai
    Hua, Da-Peng
    [J]. Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2009, 37 (15): : 15 - 18
  • [8] A Hybrid Particle Swarm Optimization Employing Genetic Algorithm for Unit Commitment Problem
    Singh, R. Lal Raja
    Rajan, C. Christober Asir
    [J]. INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE, 2011, 6 (07): : 3211 - 3217
  • [9] Thermal Unit Commitment Using hybrid Binary Particle Swarm Optimization and Genetic Algorithm
    Hosseini, S. M. Hassan
    Siahkali, H.
    Ghalandaran, Y.
    [J]. 2012 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2012,
  • [10] The Unit Commitment Problem Based on an Improved Firefly and Particle Swarm Optimization Hybrid Algorithm
    Yang, Yuanwen
    Mao, Yi
    Yang, Peng
    Jiang, Yuanmeng
    [J]. 2013 CHINESE AUTOMATION CONGRESS (CAC), 2013, : 718 - 722