Study on Operation Technology of Wind-PV-Energy Storage Combined Power Generation

doi:10.12096/j.2096-4528.pgt.2018.046

Abstract

Abstract:

With the increasing demand for energy and the rapid development of new energy, the technology of generating electricity by wind and solar energy has gradually matured, and the penetration rate in the power grid is also increasing. In order to remedy problems of unstable power and low power quality caused by wind and solar power generation, it is necessary to study the combined power generation of wind power, solar energy and energy storage. In this paper, the strategy of energy storage inhibition control is summarized according to the simple suppression method, the suppression method considering certain constraints, the suppression method considering power prediction and artificial intelligence. In the study of energy storage to tame scenery fluctuation filtering algorithm is the most common method, adding certain constraints can make smooth effect better, and energy storage to tame with accurate prediction can make the system smoother. Multi-energy storage technology can give full play to the advantages of energy storage technology. The wind energy storage complementary system with the energy storage device can effectively reduce the adverse effect of the original wind energy complementary system on the power grid. It can smooth the output characteristics of the wind power generation system to a higher degree, increase the acceptance of renewable energy to the power grid, and achieve good economic and social benefits.

Key words: scenery storage combined power generation, energy storage optimization, control strategy, stabilizing control

Yani ZHUANG,Xiuyuan YANG,Xincheng JIN. Study on Operation Technology of Wind-PV-Energy Storage Combined Power Generation[J]. Power Generation Technology, 2018, 39(4): 296-303.

References

1	周博文, 陈麒宇, 杨东升. 巴西大停电的思考[J]. 发电技术, 2018, 39 (2): 97- 105.
2	李星, 杨秀媛, 王丽婕. 灰狼算法在风电水电协同运行中的应用[J]. 发电技术, 2018, 39 (1): 43- 48.
3	陈麒宇, 张芳, 章锐. 风水协同运行控制信息的传输[J]. 发电技术, 2018, 39 (1): 53- 57.
4	王玺, 杨秀媛, 范新桥, 等. 潮流分析和鸟群优化在风水协同运行中的应用[J]. 发电技术, 2018, 39 (2): 171- 176.
5	樊新东, 杨秀媛, 金鑫城. 风电场有功功率控制综述[J]. 发电技术, 2018, 39 (3): 268- 276.
6	刘烨, 魏高升, 由文江, 等. 空气压缩系统深度节能技术[J]. 发电技术, 2018, 39 (1): 70- 76.
7	韩晓娟, 艾瑶瑶, 李相俊. 储能在电网中的应用价值及其商业模式[J]. 发电技术, 2018, 39 (1): 77- 83.
8	张学庆, 刘波, 叶军, 等. 储能装置在风光储联合发电系统中的应用[J]. 华东电力, 2010, 38 (12): 1894- 1896.
9	朱兰, 严正, 杨秀, 等. 风光储微网系统蓄电池容量优化配置方法研究[J]. 电网技术, 2012, 36 (12): 26- 31.
10	黄秀琼, 鲁籍元, 牛焕娜, 等. 用于主网削峰填谷调度的风/光/储微电网控制策略[J]. 中国电力, 2013, 46 (2): 87- 92.
11	刘波, 郭家宝, 袁智强, 等. 风光储联合发电系统调度策略研究[J]. 华东电力, 2010, 38 (12): 1897- 1899.
12	任洛卿, 白泽洋, 于昌海, 等. 风光储联合发电系统有功控制策略研究及工程应用[J]. 电力系统自动化, 2014, 38 (7): 105- 111.
13	张明霞, 闫涛, 来小康, 陈继忠, 牛萌, 徐少华. 电网新功能形态下储能技术的发展愿景和技术路径[J]. 电网技术, 2018, 42 (05): 1370- 1377.
14	Li X , Hui D , Lai X . Battery energy storage station (BESS)-based smoothing control of photovoltaic (PV) and wind power generation fluctuations[J]. IEEE Transactions on Sustainable Energy, 2013, 4 (2): 464- 473.
15	李国杰, 唐志伟, 聂宏展, 等. 钒液流储能电池建模及其平抑风电波动研究[J]. 电力系统保护与控制, 2010, 38 (22): 115- 119.
16	Liu C, Hu C, Li X, et al. Applying SMES to smooth short-term power fluctuations in wind farms[C]//Industrial Electronics, IECON 2008: IEEE, 2008: 3352-3357.
17	李文斌.储能系统平抑风电场功率波动研究[D].重庆:重庆大学, 2012.
18	李爽.提高风电功率可调度性的储能配置研究[D].北京:北京交通大学, 2016.
19	Li W, Joos G. Comparison of energy storage system technologies and configurations in a wind farm[C]//Power Electronics Specialists Conference, PESC: IEEE, 2007: 1280-1285.
20	李国杰, 唐志伟, 聂宏展, 等. 钒液流储能电池建模及其平抑风电波动研究[J]. 电力系统保护与控制, 2010, 38 (22): 115- 119.
21	李勇.基于混合储能技术的风电场功率平滑控制策略研究[D].北京:华北电力大学, 2012.
22	陈刚, 袁越, 傅质馨, 等. 储能电池平抑光伏发电波动的应用[J]. 电力系统及其自动化学报, 2014, 26 (2): 27- 31.
23	薛迎成, 邰能灵, 宋凯, 等. 基于功率滤波的风力场功率平滑控制[J]. 华东电力, 2011, 39 (3): 454- 458.
24	刘霞, 江全元. 风光储混合系统的协调优化控制[J]. 电力系统自动化, 2012, 36 (14): 95- 100.
25	张国驹, 唐西胜, 齐智平. 平抑间歇式电源功率波动的混合储能系统设计[J]. 电力系统自动化, 2011, 35 (20): 24- 28.
26	洪海生.应用于平抑风电功率波动的多类型储能系统容量配置与协调控制研究[D].杭州:浙江大学, 2013.
27	李霄, 胡长生, 刘昌金, 等. 基于超级电容储能的风电场功率调节系统建模与控制[J]. 电力系统自动化, 2009, 33 (9): 86- 90.
28	李碧辉, 申洪, 汤涌, 等. 风光储联合发电系统储能容量对有功功率的影响及评价指标[J]. 电网技术, 2011, 35 (4): 123- 128.
29	洪海生, 江全元, 严玉婷. 实时平抑风电场功率波动的电池储能系统优化控制方法[J]. 电力系统自动化, 2013, 37 (1): 103- 109.
30	Teleke S , Baran M E , Bhattacharya S , et al. Optimal control of battery energy storage for wind farm dispatching[J]. IEEE Transactions on Energy Conversion, 2010, 25 (3): 787- 794.
31	Yoshimoto K, Nanahara T, Koshimizu G. New Control Method for Regulating State-of-Charge of a Battery in Hybrid Wind Power/Battery Energy Storage System[C]//Power Systems Conference and Exposition, 2006. PSCE'06, 2006 IEEE PES: IEEE, 2006: 1244-1251.
32	Ni B, Sourkounis C. Control strategies for energy storage to smooth power fluctuations of wind parks[C]//Melecon 2010-2010, IEEE Mediterranean Electrotechnical Conference: IEEE, 2010: 973-978.
33	王伟, 薛金花, 叶季蕾, 王晓华, 吴福保, 杨波. 基于SOC调控的用于抑制光伏波动的电池储能优化控制方法[J]. 电力系统保护与控制, 2014, 42 (2): 75- 80.
34	陈跃燕, 李相俊, 韩晓娟, 等. 基于移动平均法和风电波动率约束的电池储能系统平滑风电出力控制策略[J]. 电力建设, 2013, 34 (7): 1- 5.
35	Abbey C , Kai S , Joos G . A knowledge-based approach for control of two-level energy storage for wind energy systems[J]. IEEE Transactions on Energy Conversion, 2009, 24 (2): 539- 547.
36	王文宾, 陈岩, 史智洁. 微网下风光储预测滚动协调优化策略[J]. 电力系统及其自动化学报, 2015, (s1): 27- 32.
37	Li X , Li Y , Han X , et al. Application of Fuzzy Wavelet Transform to Smooth Wind/PV Hybrid Power System Output with Battery Energy Storage System[J]. Energy Procedia, 2011, 12 (39): 994- 1001.
38	Ni B, Sourkounis C. Control strategies for energy storage to smooth power fluctuations of wind parks[C]//Melecon 2010-2010, IEEE Mediterranean Electrotechnical Conference: IEEE, 2010: 973-978.
39	丁明, 徐宁舟, 毕锐. 用于平抑可再生能源功率波动的储能电站建模及评价[J]. 电力系统自动化, 2011, 35 (2): 66- 72.
40	谢石骁, 杨莉, 李丽娜. 基于机会约束规划的混合储能优化配置方法[J]. 电网技术, 2012, 36 (5): 79- 84.
41	谭兴国, 王辉, 张黎, 等. 微电网复合储能多目标优化配置方法及评价指标[J]. 电力系统自动化, 2014, 38 (8): 7- 14.
42	李建林, 郭斌琪, 牛萌, 等. 风光储系统储能容量优化配置研究[J]. 电工技术学报, 2018, 33 (6): 1189- 1196.
43	张晴, 李欣然, 杨明, 等. 净效益最大的平抑风电功率波动的混合储能容量配置方法[J]. 电工技术学报, 2016, 31 (14): 40- 48.

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