The Model of Unit Commitment on Wind Power Accommodation Based on the Fuzzy Preferences Evolutionary Algorithm

被引:0
作者
Sun Hongbin [1 ]
Wang Dexin [2 ]
机构
[1] Changchun Inst Technol, Sch Elect Engn & Informat, Changchun 130012, Jilin, Peoples R China
[2] Jilin Univ, Sch Elect Engn & Informat, Changchun 130012, Jilin, Peoples R China
来源
PROCEEDINGS 2015 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND ENGINEERING APPLICATIONS ISDEA 2015 | 2015年
关键词
Unit Commitment; Operational Cost; Wind Power Accommodation; Fuzzy Preferences; GENETIC ALGORITHM;
D O I
10.1109/ISDEA.2015.218
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Unit Commitment problem is a nonlinear mixed integer optimization problem used in the scheduling operation of power system generating units subjected to demand and reserve requirement constraints for achieving minimum operating cost. In this paper, multiple objectives are considered for capacity of wind power, the risk of lacking peak regulation capacity and lower operational cost. We propose a fuzzy preferences evolutionary which solves the unit commitment problem subjected to necessary constraints and gives the optimal commitment of the units. Based on the objectives evaluated by membership functions respectively, These objectives are modeled with fuzzy sets to evaluate their imprecise nature and one can provide the anticipated value of each objective. The model and algorithms are applied to calculate a case of 10 units. The results show that the proposed modeling method can provide a useful guidance for Unit Commitment problems.
引用
收藏
页码:863 / 866
页数:4
相关论文
共 17 条
  • [1] Bansal M, 2011, IEEE IC COMP COM NET
  • [2] Barth R., 2006, Probabilistic Methods Applied to Power Systems, P1
  • [3] Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II
    Basu, M.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (02) : 140 - 149
  • [4] A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem
    Carrion, Miguel
    Arroyo, Jose M.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (03) : 1371 - 1378
  • [5] A solution to the unit-commitment problem using integer-coded genetic algorithm
    Damousis, IG
    Bakirtzis, AG
    Dokopoulos, PS
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (02) : 1165 - 1172
  • [6] A fast and elitist multiobjective genetic algorithm: NSGA-II
    Deb, K
    Pratap, A
    Agarwal, S
    Meyarivan, T
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) : 182 - 197
  • [7] Eppe S, 2011, IEEE C EVOL COMPUTAT, P2751
  • [8] Lakshmi R., 2012, INDONESIAN J ELECT E, V10, P409
  • [9] Unit commitment - A bibliographical survey
    Padhy, NP
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (02) : 1196 - 1205
  • [10] A Stochastic Model for the Optimal Operation of a Wind-Thermal Power System
    Pappala, Venkata Swaroop
    Erlich, Istvan
    Rohrig, Kurt
    Dobschinski, Jan
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (02) : 940 - 950