Co-Optimization of Reservoir and Power Systems (COREGS) for seasonal planning and operation

被引:3
作者
Ford, Lucas [1 ]
de Queiroz, Anderson [1 ,2 ]
DeCarolis, Joseph [1 ]
Sankarasubramanian, A. [1 ]
机构
[1] North Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA
[2] North Carolina Cent Univ, Dept Decis Sci Econ & Finance, Durham, NC USA
基金
美国国家科学基金会;
关键词
Multireservoir optimization; Energy system optimization; Hydropower; Seasonal planning; STOCHASTIC OPTIMIZATION; CLIMATE-CHANGE; FLOOD RISK; ENERGY; CASCADE; MODEL; DECOMPOSITION; GENERATION; IMPACTS; STORAGE;
D O I
10.1016/j.egyr.2022.06.017
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Climate variability accounts for distinct seasonal differences in electricity demand and streamflow potential, which power systems rely on to assess available hydropower and to cool thermal power plants. Understanding the interactions between reservoir and power networks under varying climate conditions requires an integrated analysis of both systems. In this study, we develop Co-Optimization of Reservoir and Electricity Generation Systems (COREGS), a generalized, open-source, modeling framework that optimizes both systems with respect to reducing power generation costs using a multireservoir model (GRAPS) and an electricity system model (TEMOA). Three optimization schemes of varying degrees of model integration are applied to Tennessee Valley Authority's reservoir and electricity systems for the summer and winters from 2003 to 2015. We find that co-optimization of the systems results in more efficient water allocation decisions than separate optimization. Cooptimization solutions reduce reservoir spill and allocate water for hydropower only when and where it is beneficial to the power system as compared to stand-alone water system optimization. As the penetration of solar and wind power continues to increase, power systems will be more reliant on flexible reliable generating services such as reservoir systems and co-optimization of both systems will become more essential for efficient seasonal planning and operation. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页码:8061 / 8078
页数:18
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