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多时间尺度的电池储能系统建模及分析应用_陆秋瑜.pdf

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    • » 33  » 16 ù Ï S È  ý ñ Ð  Vol.33 No.16 Jun. 5, 2013 86 2013 M 6 5 ° Proceedings of the CSEE ©2013 Chin.Soc.for Elec.Eng. ÓcI| 0258-8013 (2013) 16-0086-08 Ïms Ë| TM 74 ÓDS½’ A Ð Ss Ë| 47040 HW¥Èý% ?"dy #s‹¨ d l:1±¿1¢ Á1‰§1Ï¿2ë»=2¦¤&2†=32(1È ï"d#?È!! eÅ„_‡SE×ÄLi ( b¿vÐÈ" )Øg ZÎ u 100084 2 a8È ïµK³ a8 +g 110006) Modeling and Analysis of Battery Energy Storage Systems in Multi-time Scales Application LU Qiuyu1, HU Wei1, ZHENG Le1, MIN Yong1, LUO Weihua2, GE Weichun2, WANG Zhiming2, YAN Chunsheng2(1. State Key Lab of Power Systems, Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China; 2. Liaoning Electrical Power Co. Ltd., Shenyang 110006, Liaoning Province, China) ABSTRACT: The rapid development of battery energy storage technology has provided a new solution for integrating large scale wind power; however, the accurate simulation model for battery energy storage system (BESS) in power system application has not been developed yet. In this paper, a BESS model based on Thevenin circuit was developed. In this model, the model parameters fitting method based on experimental data was proposed, and the influences of state of charge (SOC) and charged/discharged current on model parameters were taken into account. Further, the critical factors in various application scenarios were analyzed to facilitate the proposed model to be feasible in multiple time scales. The effectiveness of the presented model was verified by the measured voltage and current data. Finally, the model was applied to alleviate low frequency wind power volatility to test the control effect of BESS, and the advantages and disadvantages of different models and their impacts on BESS capacity allocation was further discussed. KEY WORDS: battery energy storage; multi-time scales battery model; parameter fitting method; wind power volatility alleviation; battery capacity allocation K1 v ¸Èý% ?/Œ¥ yÎ?Z#‹¨¹v? „È¥¤ ÆÐh ,4¥³ %±^ÐZE ŒÈý% ?Èï"d‹¨Ï¥y Ù5B°À ?¤ž z¥³ %b y ë¿z» 2©rÈ^¥Èý% ?"d_‡ ˜i ˜Á[ " SEÚ/Œùî?Z9à (863 9à )(2011AA05A112) SE S/¦ê9à (2011BAA01B02) SE1 – SÐÁ×v[ "(51190101) SEÈ©³ S/[ "  a8È ïµK³ S/[ "b The National High Technology Research and Development of China 863 Program (2011AA05A112); Key Project of the National Eleventh-Five Year Research Program of China (2011BAA01B02); Project Supported by National Natural Science Foundation of China (51190101). Ï9#Èý€Èÿ„ bÈÈ@ ˜•”¥•Y ]H4¿L” E† ˜•”¥ZEbN$s)‚¾ ˜È ï"d‚]‹¨ÆßÏ¥öyÍ y ëa¨¿HW¥Èý% ?_‡ ˜ iYVL©ÈâÈ@wL£ ˜¥µrŸb Kª[ Ü]„ÈÏÉ ùoèYV9Ø_‡¨z» 2©rÈ^eÄ ˜¥Èý%? Ü]„È{oî¥rT i1 Ð¨È?šÿq ˜H¥ªÄ#% ? ¸?Ã¥•Yb1oM Èý% ? HWÈý ˜ •” E† „Èoî Ü] ¸?à 0 „ý Û" ?÷²¥F #ÌâÙ5¥Ú×j[„ȹ}V¥ V3 ?÷W¸òS¤žáÎ?ZbáS 2012 M„ÈF9 ¸Xrž 7532 £ kW[1]]H?Þ 2020 M¸yî 7 ñ $£ kW)v˜„ȹ½H„È ¸|rž 1.5 a kWb –7„È µ  0 Ub(t)>Ubmax(t) & Pb(t)<0? Pb(t)0ô Pb(t)Ub(SSOC, Ib)Ib9ؤž eÅ·7 Ib 9Ø SSOC(t1)SSOC(t)bIb(t)Ta/SAh ^ Žm 9 „% ó†"d eÅ@ñm Fig. 9 Control flow of wind-BESS integrate system » 16 ù d l:©HW¥Èý% ?"dy #s‹¨ 91 ÿq/W_‡HW /h 020 10 „ÿq % ?ÿq „% ó†"dÿq 1 500 500 1 000 500 0 1 000 m 10 „a% ?„ ó†"d ï wL Fig. 10 Power output of wind turbine, battery and the integrate system0 10 20 _‡HW /s (a) Èâ Ub/V 8 7 6 5 0 10 20 _‡HW /s (b) È@ Ib/V 2 0 2 0 10 20 _‡HW /h (c) SOC wL SSOC/% 100 50 0 m 11 †8Èý¥ÈâaÈ@„ SOC wL Fig. 11 Voltage, current and SOC curves of battery cellHsY^®¿Èý¥ûà /bÈP¤Èâ6Ú /ًÀ©¸ÈâÁ ¹îT M% ?"db VnNH% ?¥ ¸ ¯‚ ?¡@ eÅ1 pb 2.2 ‚]% ? ˜ Ü]rT#% ? ¸ªÄ¥•Y '«1 î¨¥z» 2©rÈ^eÄ ˜„È?šÿq ˜ Ü]rT#% ? ¸ªÄ¥•YbÕ ˜¨M]¥ eŦ{®¿šÿq˜iÀµ% ? =†MÉ›y yN¨SOCT¹©¸ ‘Hq Ï SSOC90% SSOC10%5 M% ?"db |„-çÿq¥ 20%T¹ÿqo9Ø‚]% ? ¸ (Èý†8ñ” )/ ó†"dÿqo =¥Àq²T Âm 12îUb sm 12¥ wL t] V© 1Û"% ? ¸¥9Fÿqoî‚hlb ÿqoîÀqÈý†8ñ” eÄ ˜ šÿq ˜ 1.00.80.90.60.720 60 80 40 m 12 ‚] ¸/ÿqoî¡@´1 p¥Àq Fig. 12 Power volatility probability within threshold with different battery capacities 7®¿ 。

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