A hybrid algorithm for the unit commitment problem with wind uncertainty

被引:0
|
作者
Layon M. de Oliveira
Ivo C. Silva Junior
Ramon Abritta
Ezequiel da S. Oliveira
Pedro Henrique M. Nascimento
Leonardo de M. Honório
机构
[1] Federal University of Juiz de Fora,Laboratory of Power Systems, Department of Electrical Energy
[2] Federal Center of Technological Education Celso Suckow da Fonseca,undefined
来源
Electrical Engineering | 2022年 / 104卷
关键词
Heuristic; Wind generation; Sine cosine algorithm; Unit commitment; Daily planning;
D O I
暂无
中图分类号
学科分类号
摘要
This paper applies the sine cosine algorithm to the operation planning of wind-penetrated thermoelectric systems considering wind-related uncertainties, which is a mixed-integer nonlinear programming problem often referred to as thermal unit commitment with power integration. The proposed method, denominated hybrid sine cosine algorithm (HSCA), is based on heuristic information derived from sensitivity indexes obtained from priority lists and power dispatch evaluations regarding the thermoelectric system operation. Wind uncertainty was managed by two methodologies, which are extensions of the HSCA, through a set of predicted generation scenarios. One is based on the median wind power generation (M-HSCA), whereas the other is based on the probability distribution matrix (PDM-HSCA). Results have shown that the proposed method is reliable since it guarantees the attendance of all constraints. Furthermore, concerning the operational cost values obtained, it proved itself competitive when compared to other methods found in the literature.
引用
收藏
页码:1093 / 1110
页数:17
相关论文
共 50 条
  • [31] Unit commitment considering flexibility and uncertainty of wind power generation
    Liu, Bin
    Liu, Feng
    Wang, Cheng
    Mei, Shengwei
    Wei, Wei
    Dianwang Jishu/Power System Technology, 2015, 39 (03): : 730 - 736
  • [32] Hybrid immune genetic algorithm approach for short-term unit commitment problem
    Liao, GC
    Tsao, TP
    2004 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1 AND 2, 2004, : 1075 - 1081
  • [33] The Unit Commitment Problem Based on an Improved Firefly and Particle Swarm Optimization Hybrid Algorithm
    Yang, Yuanwen
    Mao, Yi
    Yang, Peng
    Jiang, Yuanmeng
    2013 CHINESE AUTOMATION CONGRESS (CAC), 2013, : 718 - 722
  • [34] Coping with Wind Power Uncertainty in Unit Commitment: a Robust Approach using the New Hybrid Metaheuristic DEEPSO
    Pinto, Rui
    Carvalho, Leonel M.
    Sumaili, Jean
    Pinto, Mauro S. S.
    Miranda, Vladimiro
    2015 IEEE EINDHOVEN POWERTECH, 2015,
  • [35] An unit commitment model and algorithm with randomness of wind power
    Zhang, N., 2013, China Machine Press (28):
  • [36] Solving wind-integrated unit commitment problem by a modified African vultures optimization algorithm
    Abuelrub, Ahmad
    Awwad, Boshra
    Al-Masri, Hussein M. K.
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2023, 17 (16) : 3678 - 3691
  • [37] Modified Genetic Algorithm Solution to Unit Commitment Problem
    Madraswala, Hatim S.
    2017 INTERNATIONAL CONFERENCE ON NASCENT TECHNOLOGIES IN ENGINEERING (ICNTE-2017), 2017,
  • [38] An implementation of harmony search algorithm to unit commitment problem
    Afkousi-Paqaleh, M.
    Rashidinejad, M.
    Pourakbari-Kasmaei, M.
    ELECTRICAL ENGINEERING, 2010, 92 (06) : 215 - 225
  • [39] Optimization of Unit Commitment Problem Using Genetic Algorithm
    Agarwal, Aniket
    Pal, Kirti
    INTERNATIONAL JOURNAL OF SYSTEM DYNAMICS APPLICATIONS, 2021, 10 (03) : 21 - 37
  • [40] Risk Constrained Unit Commitment Considering Uncertainty of Wind Power and Load
    Li, Zhi
    Han, Xueshan
    2009 INTERNATIONAL CONFERENCE ON SUSTAINABLE POWER GENERATION AND SUPPLY, VOLS 1-4, 2009, : 1276 - 1280