Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective

被引:34
|
作者
Qiu, Haifeng [1 ]
Gu, Wei [1 ]
Liu, Pengxiang [1 ]
Sun, Qirun [1 ]
Wu, Zhi [1 ]
Lu, Xi [1 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing 210096, Peoples R China
关键词
Power systems; Optimal operation; Uncertainty scheduling; Robust optimization; Two-stage; CONSTRAINED UNIT COMMITMENT; AC/DC HYBRID MICROGRIDS; RENEWABLE DISTRIBUTED GENERATION; ACTIVE DISTRIBUTION NETWORKS; SMART DISTRIBUTION NETWORKS; ENERGY-STORAGE; WIND POWER; DEMAND RESPONSE; CO-OPTIMIZATION; INTEGRATED ELECTRICITY;
D O I
10.1016/j.energy.2022.123942
中图分类号
O414.1 [热力学];
学科分类号
摘要
Multi-uncertainties impose enormous challenges to the optimal scheduling of power systems, and two stage robust optimization (TSRO) theory has been widely investigated and employed in this field as a valid processing approach. This paper primarily reviews the research on TSRO scheduling of power systems. Firstly, the general formulations and solution algorithms for multi-type TSRO models are summarized and categorized. Subsequently, various modeling methods for continuous and discrete uncertainties in power systems are generalized, along with their characteristics and advantages clarified by expounding application scopes and implementation values. Next, research work and achievements of TSRO in power system scheduling are reviewed from four aspects, i.e., unit commitment, economic dispatch, active/reactive power coordination and resilient dispatch, and the development and practicality of TSRO in the four directions are detailedly combed combining latest literature. Finally, according to the aforementioned analysis, existing research gaps are discussed from the aspects of formulation morphology, solution algorithm, uncertainty modeling and extended application, and the outlook of future work is provided accordingly. (c) 2022 Published by Elsevier Ltd.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Disjoint Bilinear Optimization: A Two-Stage Robust Optimization Perspective
    Zhen, Jianzhe
    Marandi, Ahmadreza
    de Moor, Danique
    den Hertog, Dick
    Vandenberghe, Lieven
    [J]. INFORMS JOURNAL ON COMPUTING, 2022, 34 (05) : 2410 - 2427
  • [2] A Lagrangian dual method for two-stage robust optimization with binary uncertainties
    Subramanyam, Anirudh
    [J]. OPTIMIZATION AND ENGINEERING, 2022, 23 (04) : 1831 - 1871
  • [3] A Lagrangian dual method for two-stage robust optimization with binary uncertainties
    Anirudh Subramanyam
    [J]. Optimization and Engineering, 2022, 23 : 1831 - 1871
  • [4] A two-stage robust configuration optimization framework for integrated energy system considering multiple uncertainties
    Yang, Meng
    Liu, Yisheng
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2024, 101
  • [5] An interval two-stage robust stochastic programming approach for steam power systems design and operation optimization under complex uncertainties
    Niu, Teng
    Yin, Hongchao
    Feng, Enmin
    [J]. CHEMICAL ENGINEERING SCIENCE, 2022, 253
  • [6] Active and Reactive Power Coordinated Two-Stage MG Scheduling for Resilient Distribution Systems Under Uncertainties
    Cai, Sheng
    Xie, Yunyun
    Wu, Qiuwei
    Zhang, Menglin
    Jin, Xiaolong
    Xiang, Zhengrong
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (04) : 2986 - 2998
  • [7] Two-stage robust optimization of thermal-ESS units scheduling under wind uncertainty
    Wang, Jun
    Xu, Xiao
    Li, Hongyan
    Chen, Hongmei
    [J]. ENERGY REPORTS, 2022, 8 : 1147 - 1155
  • [8] Power system state scheduling with the two-stage problem
    Palamarchuk, SI
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1999, 14 (02) : 439 - 445
  • [9] Robust two-stage combinatorial optimization problems under discrete demand uncertainties and consistent selection constraints
    Buesing, Christina
    Schmitz, Sabrina
    [J]. DISCRETE APPLIED MATHEMATICS, 2024, 347 : 187 - 213
  • [10] Optimal Design of Distributed Energy Resource Systems under Uncertainties Based on Two-Stage Robust Optimization
    Da Li
    Shijie Zhang
    [J]. Journal of Thermal Science, 2021, 30 : 51 - 63