AN OPTIMIZATION-BASED METHOD FOR UNIT COMMITMENT

被引:166
|
作者
GUAN, X
LUH, PB
YAN, H
AMALFI, JA
机构
[1] Department of Electrical and Systems Engineering, University of Connecticut, Storrs
[2] Northeast Utilities Service Company, Berlin
基金
美国国家科学基金会;
关键词
UNIT COMMITMENT; POWER SYSTEM SCHEDULING; MATHEMATICAL PROGRAMMING; LAGRANGIAN RELAXATION;
D O I
10.1016/0142-0615(92)90003-R
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An optimization-based method for unit commitment using the Lagrangian relaxation technique is presented. The salient features of this method includes nondiscretization of generation levels, a systematic method to handle ramp rate constraints, and a good initialization procedure. By using Lagrange multipliers to relax system-wide demand and reserve requirements and ramp rate constraints, the problem is decomposed into the scheduling of individual units. The optimal generation level of a unit at each hour can be easily calculated since there are no system dynamics, and the cost function is stage-wise additive and piecewise linear with only a few corner points. A relaxed subproblem can therefore be efficiently solved by using the dynamic programming technique without discretizing generation levels. A subgradient algorithm with adaptive step sizing is used to update Lagrange multipliers. An effective method based on priority-list commitment and dispatch is adopted to initialize these multipliers, and a heuristic approach is developed to generate a good feasible schedule based on the dual solution. Numerical results based on data sets from Northeast Utilities show that this algorithm is efficient, and near-optimal solutions are obtained.
引用
收藏
页码:9 / 17
页数:9
相关论文
共 50 条
  • [41] Sequential optimization and uncertainty propagation method for efficient optimization-based model calibration
    Lee, Guesuk
    Son, Hyejeong
    Youn, Byeng D.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 60 (04) : 1355 - 1372
  • [42] Sequential optimization and uncertainty propagation method for efficient optimization-based model calibration
    Guesuk Lee
    Hyejeong Son
    Byeng D. Youn
    Structural and Multidisciplinary Optimization, 2019, 60 : 1355 - 1372
  • [43] Development of an Optimization-Based Atomistic-to-Continuum Coupling Method
    Olson, Derek
    Bochev, Pavel
    Luskin, Mitchell
    Shapeev, Alexander V.
    LARGE-SCALE SCIENTIFIC COMPUTING, LSSC 2013, 2014, 8353 : 33 - 44
  • [44] OPTIMIZATION-BASED SHRINKING DIMER METHOD FOR FINDING TRANSITION STATES
    Zhang, Lei
    Du, Qiang
    Zheng, Zhenzhen
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2016, 38 (01): : A528 - A544
  • [45] Ordinal Optimization-Based Performance Model Estimation Method for HDFS
    Ma, Tian
    Tian, Feng
    Dong, Bo
    IEEE ACCESS, 2020, 8 : 889 - 899
  • [46] Optimization-Based Tracking Method for Active Navigation in Orthopedic Surgeries
    Meng, Yiyang
    Luo, Mengde
    Han, Jianda
    Qin, Yanding
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 3850 - 3855
  • [47] A new optimization-based method for motion planning in dynamic environments
    Ren, J
    McIsaac, KA
    Huang, XS
    IEEE ROBIO 2004: PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, 2004, : 157 - 162
  • [48] Optimization-based automated unsupervised classification method: A novel approach
    Matci, Dilek Kucuk
    Avdan, Ugur
    EXPERT SYSTEMS WITH APPLICATIONS, 2020, 160
  • [49] Parameter estimation of copula functions using an optimization-based method
    Abdi, Amin
    Hassanzadeh, Yousef
    Talatahari, Siamak
    Fakheri-Fard, Ahmad
    Mirabbasi, Rasoul
    THEORETICAL AND APPLIED CLIMATOLOGY, 2017, 129 (1-2) : 21 - 32
  • [50] An optimization-based method for dynamic multiple fault diagnosis problem
    Singh, Satnam
    Ruan, Sui
    Choi, Kihoon
    Pattipati, Krishna
    Willett, Peter
    Namburu, Setu Madhavi
    Chigusa, Shunsuke
    Prokhorov, Danil V.
    Qiao, Liu
    2007 IEEE AEROSPACE CONFERENCE, VOLS 1-9, 2007, : 3824 - +