Cooperation of Storage Operation in a Power Network With Renewable Generation

被引:40
作者
Lakshminarayana, Subhash [1 ,2 ]
Xu, Yunjian [1 ]
Poor, H. Vincent [3 ]
Quek, Tony Q. S. [1 ,4 ]
机构
[1] Singapore Univ Technol & Design, Singapore 591401, Singapore
[2] Illinois Singapore, Adv Digital Sci Ctr, Singapore, Singapore
[3] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
[4] Inst Infocomm Res, Singapore, Singapore
基金
美国国家科学基金会;
关键词
Energy storage; dc power network; Lyapunov optimization; look-ahead policy; ENERGY;
D O I
10.1109/TSG.2016.2542367
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
In this paper, proper scheduling of the operation of multiple storage devices is sought so as to minimize the expected total cost (of conventional generation) in a power network with intermittent renewable generation. Since the power network constraints make it intractable to compute optimal storage operation policies through dynamic programming-based approaches, a Lyapunov optimization-based online algorithm (LOPN) is proposed, which makes decisions based only on the current state of the system (i.e., the current demand and renewable generation). The proposed algorithm is computationally simple and achieves asymptotic optimality (as the capacity of energy storage grows large). To improve the performance of the LOPN algorithm for the case with limited storage capacity, a threshold-based energy storage management (TESM) algorithm is proposed that utilizes the forecast information (on demand and renewable generation) over the next few time slots to make storage operation decisions. Numerical experiments are conducted on IEEE 6- and 9-bus test systems to validate the asymptotic optimality of LOPN, and compare the performance of LOPN and TESM. Numerical results show that TESM significantly outperforms LOPN when the storage capacity is relatively small.
引用
收藏
页码:2108 / 2122
页数:15
相关论文
共 27 条
[1]  
[Anonymous], 2012, P IEEE POW EN SOC GE
[2]  
[Anonymous], 2009, ACC HIGH LEV VAR GEN
[3]  
[Anonymous], 2010, MAX WEIGHT ACHIEVES
[4]  
[Anonymous], 2008, 20 WIND EN 2030 INCR
[5]  
[Anonymous], 2011, P ACM SIGMETRICS JOI
[6]   The economic benefit of short-term forecasting for wind energy in the UK electricity market [J].
Barthelmie, R. J. ;
Murray, F. ;
Pryor, S. C. .
ENERGY POLICY, 2008, 36 (05) :1687-1696
[7]  
Bitar E, 2011, P AMER CONTR CONF, P3886
[8]  
CPUC, 2013, DEC AD EN STOR PROC
[9]   Stochastic joint optimization of wind generation and pumped-storage units in an electricity market [J].
Garcia-Gonzalez, Javier ;
Ruiz de la Muela, Rocio Moraga ;
Matres Santos, Luz ;
Mateo Gonzalez, Alicia .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (02) :460-468
[10]  
Georgiadis Leonidas, 2006, Foundations and Trends in Networking, V1, P1, DOI 10.1561/1300000001