A CVaR-constrained optimal power flow model for wind integrated power systems considering Transmission-side flexibility

被引:9
|
作者
You, Lei [1 ]
Ma, Hui [1 ]
Saha, Tapan Kumar [1 ]
机构
[1] Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
关键词
Optimal power flow; Operational flexibility; Conditional value-at-risk; Dynamic line rating; FACTS; Gaussian mixture model; CORRECTIVE CONTROL; CONDITIONAL VALUE; RISK; UNCERTAINTY; SET; MICROGRIDS; FACTS;
D O I
10.1016/j.ijepes.2023.109087
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
The integration of renewable power can pose uncertainty to power system operation, causing operational risk like power imbalance or line congestion. To improve the operational security and economy of the system under uncertainties, this paper considers two potential directions. The first is to enhance the system capability for safely accommodating uncertainties using various network resources. Such capability is often termed as the operational flexibility. The second direction is to employ appropriate risk management methods. With these two directions, a conditional value-at-risk (CVaR)-constrained optimal power flow (OPF) model is developed in this paper for wind-integrated power systems. In this model, dynamic line rating (DLR) and flexible AC transmission system (FACTS) technologies are exploited to unlock transfer capacities of transmission lines and enable line reactance control. As a result, power system has capability to allow more flexible and cost-efficient power flow distribu-tions. That is, additional operational flexibility is provided by the transmission-side DLR and FACTS technolo-gies. Such flexibility is termed as the transmission-side flexibility. Meanwhile, CVaR is employed as the risk management tool to control the security level of each operational constraint. To address the non-linearity of CVaR and solve the proposed model, a novel solution method is developed by combining Gaussian mixture model for uncertainty modelling with cutting-planes for CVaR reformulation. Numerical experiments in MATLAB reveal the economic benefit of the proposed model: the inclusion of transmission-side flexibility in formula can reduce the operational cost by 6.10% on a 14-bus system. The simulation results also show that the proposed solution method overcomes the poor system security associated with the traditional Gaussian method and is more economical than the previous robust method (3.79% reduction in operational cost on a 14-bus system).
引用
下载
收藏
页数:14
相关论文
共 50 条
  • [31] Stability Constrained Optimal Power Flow in Deregulated Power Systems
    Azadani, E. Nasr
    Hosseinian, S. H.
    Divshali, P. Hasanpor
    Vahidi, B.
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2011, 39 (08) : 713 - 732
  • [32] Production of Hydrogen from Wind and Hydro Power in Constrained Transmission grids, Considering the Stochasticity of Wind Power
    Bodal, Espen Flo
    Korpas, Magnus
    EERA DEEPWIND'2018, 15TH DEEP SEA OFFSHORE WIND R&D CONFERENCE, 2018, 1104
  • [33] Optimal Power Flow in Wind Power Integrated Systems using Function Optimization by Learning Automata
    Liao, H. L.
    Wu, Q. H.
    2011 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2011,
  • [34] Chance-constrained stochastic congestion management of power systems considering uncertainty of wind power and demand side response
    Wu, Jiasi
    Zhang, Buhan
    Jiang, Yazhou
    Bie, Pei
    Li, Hang
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 107 : 703 - 714
  • [35] The Calibrated Safety Constraints Optimal Power Flow for the Operation of Wind-Integrated Power Systems
    Lu, Kai-Hung
    Qian, Wenjun
    Jiang, Yuesong
    Zhong, Yi-Shun
    Processes, 2024, 12 (10)
  • [36] Unbiased optimal power flow for power systems with wind power generation
    Plathottam, S. J.
    Ranganathan, P.
    Salehfar, H.
    ELECTRONICS LETTERS, 2014, 50 (18) : 1312 - 1313
  • [37] Robust Stochastic Dynamic Optimal Power Flow Model of Electricity-Gas Integrated Energy System considering Wind Power Uncertainty
    Qin, Zhengfeng
    Bai, Xiaoqing
    Su, Xiangyang
    COMPLEXITY, 2020, 2020
  • [38] Stochastic Optimal Power Flow for Power Systems Considering Wind Farms Based on the Stochastic Collocation Method
    Xia, Bingqing
    Chen, Yuwei
    Yang, Wenbin
    Chen, Qing
    Wang, Xiaohe
    Min, Kuan
    IEEE ACCESS, 2022, 10 : 44023 - 44032
  • [39] Optimal reactive power flow in wind generation integrated power system
    Qiao, Jiageng
    Min, Yong
    Lu, Zongxiang
    2006 INTERNATIONAL CONFERENCE ON POWER SYSTEMS TECHNOLOGY: POWERCON, VOLS 1- 6, 2006, : 928 - +
  • [40] Stochastic optimal transmission switching considering the correlated wind power
    Zhang, Heng
    Cheng, Haozhong
    Zhang, Shenxi
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2019, 13 (13) : 2664 - 2672