Compensating for wind variability using co-located natural gas generation and energy storage

被引:40
作者
Hittinger, Eric [1 ]
Whitacre, J. F. [1 ,2 ]
Apt, Jay [1 ,3 ]
机构
[1] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Dept Mat Sci & Engn, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, Tepper Sch Business, Pittsburgh, PA 15213 USA
来源
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS | 2010年 / 1卷 / 04期
基金
美国国家科学基金会; 美国安德鲁·梅隆基金会;
关键词
Wind integration; Energy storage; Wind variability; Sodium sulfur batteries; Renewable portfolio standards;
D O I
10.1007/s12667-010-0017-2
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
Wind generation presents variability on every time scale, which must be accommodated by the electric grid. Limited quantities of wind power can be successfully integrated by the current generation and demand-side response mix but, as deployment of variable resources increases, the resulting variability becomes increasingly difficult and costly to mitigate. We model a co-located power generation/energy storage block which contains wind generation, a gas turbine, and fast-ramping energy storage. Conceptually, the system is designed with the goal of producing near-constant "baseload" power at a reasonable cost while still delivering a significant and environmentally meaningful fraction of that power from wind. The model is executed in 10 second time increments in order to correctly reflect the operational limitations of the natural gas turbine. A scenario analysis identifies system configurations that can generate power with 30% of energy from wind, a variability of less than 0.5% of the desired power level, and an average cost around $70/MWh. The systems described have the most utility for isolated grids, such as Hawaii or Ireland, but the study has implications for all electrical systems seeking to integrate wind energy and informs potential incentive policies.
引用
收藏
页码:417 / 439
页数:23
相关论文
共 23 条
[1]  
[Anonymous], 2007, COST PERF BAS FOSS E
[2]  
[Anonymous], 2008, LEVELIZED COST ENERG
[3]   The spectrum of power from wind turbines [J].
Apt, Jay .
JOURNAL OF POWER SOURCES, 2007, 169 (02) :369-374
[4]   Value of bulk energy storage for managing wind power fluctuations [J].
Black, Mary ;
Strbac, Goran .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2007, 22 (01) :197-205
[5]   On the optimization of the daily operation of a wind-hydro power plant [J].
Castronuovo, ED ;
Lopes, JAP .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (03) :1599-1606
[6]  
DeCesaro J., 2009, ELECT J, V22, P34, DOI [DOI 10.1016/J.TEJ.2009.10.010, DOI 10.1016/j.tej.2009.10.010]
[7]  
Department of Communications, 2004, REN EL
[8]  
*EIA, EIA NAT GAS NAV
[9]  
EPRI-DOE, 2002, HDB EN STOR TRANSM D
[10]  
ERCOT, ERCOT PROT