Transmission Expansion Planning for Renewable-Energy-Dominated Power Grids Considering Climate Impact

被引:3
作者
Lu, Jin [1 ]
Li, Xingpeng [1 ]
机构
[1] Univ Houston, Dept Elect & Comp Engn, Houston, TX 77204 USA
关键词
Renewable energy sources; Meteorology; Generators; Planning; Production; Power systems; Costs; Generation investment; power grid; renewable energy; reliability; climate; transmission expansion planning; GENERATION; MANAGEMENT; SYSTEMS; DEMAND;
D O I
10.35833/MPCE.2023.000990
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
As renewable energy is becoming the major resource in future power grids, the weather and climate can have a higher impact on grid reliability. Transmission expansion planning (TEP) has the potential to reinforce the power transfer capability of a transmission network for climate-impacted power grids. In this paper, we propose a systematic TEP procedure for renewable-energy-dominated power grids considering climate impact (CI). Particularly, this paper develops an improved model for TEP considering climate impact (TEP-CI) and evaluates the reliability of power grid with the obtained transmission investment plan. Firstly, we create climate-impacted spatio-temporal future power grid data to facilitate the study of TEP-CI, which include the future climate-dependent renewable power generation as well as the dynamic line rating profiles of the Texas 123-bus backbone transmission (TX-123BT) system. Secondly, the TEP-CI model is proposed, which considers the variation in renewable power generation and dynamic line rating, and the investment plan for future TX-123BT system is obtained. Thirdly, a customized security-constrained unit commitment (SCUC) is presented specifically for climate-impacted power grids. The reliability of future power grid in various investment scenarios is analyzed based on the daily operation conditions from SCUC simulations. The whole procedure presented in this paper enables numerical studies on power grid planning considering climate impact. It can also serve as a benchmark for other studies of the TEP-CI model and its performance evaluation.
引用
收藏
页码:1737 / 1748
页数:12
相关论文
共 41 条
[31]  
Pyomo, 2024, Pyomo package
[32]   Distributionally Robust Congestion Management With Dynamic Line Ratings [J].
Qiu, Feng ;
Wang, Jianhui .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (04) :2198-2199
[33]   Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment [J].
Ramesh, Arun Venkatesh ;
Li, Xingpeng .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2024, 39 (02) :4735-4746
[34]   RCP 8.5-A scenario of comparatively high greenhouse gas emissions [J].
Riahi, Keywan ;
Rao, Shilpa ;
Krey, Volker ;
Cho, Cheolhung ;
Chirkov, Vadim ;
Fischer, Guenther ;
Kindermann, Georg ;
Nakicenovic, Nebojsa ;
Rafaj, Peter .
CLIMATIC CHANGE, 2011, 109 (1-2) :33-57
[35]   Forecasting the inevitable: A review on the impacts of climate change on renewable energy resources [J].
Russo, M. A. ;
Carvalho, D. ;
Martins, N. ;
Monteiro, A. .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 52
[36]   Price-based unit commitment with decision-dependent uncertainty in hourly demand [J].
Su, Jinshun ;
Dehghanian, Payman ;
Lejeune, Miguel A. .
IET SMART GRID, 2022, 5 (01) :12-24
[37]  
U.S. Department of Energy, 2023, Operation and planning tools for inverter-based resource management and availability for future power systems (optima)
[38]  
University of Washington, 2023, 118 bus power flow test case
[39]   Stochastic Transmission Expansion Planning Considering Uncertain Dynamic Thermal Rating of Overhead Lines [J].
Zhan, Junpeng ;
Liu, Weijia ;
Chung, C. Y. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (01) :432-443
[40]  
Zhao C., 2022, P 2022 N AM POWER S, P1