LI Shou-dong1, DONG Hai-ying1, ZHANG Rui-ping1, MA Xi-ping2
(1. School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;2. State Grid Gansu Electric Power Research Institute, Lanzhou 730050, China)
Abstract: To solve the severe problem of wind power curtailment in the winter heating period caused by “power determined by heat” operation constraint of cogeneration units, this paper analyzes thermoelectric load, wind power output distribution and fluctuation characteristics at different time scales, and finally proposes a two-level coordinated control strategy based on electric heat storage and pumped storage. The optimization target of the first-level coordinated control is the lowest operation cost and the largest wind power utilization rate. Based on prediction of thermoelectric load and wind power, the operation economy of the system and wind power accommodation level are improved with the cooperation of electric heat storage and pumped storage in regulation capacity. The second-level coordinated control stabilizes wind power real-time fluctuations by cooperating electric heat storage and pumped storage in control speed. The example results of actual wind farms in Jiuquan, Gansu verifies the feasibility and effectiveness of the proposed coordinated control strategy.
Key words: wind power accommodation; electric heat storage; pumped storage; wind power fluctuation; coordinated control
CLD number: TP273Document code: A
Article ID: 1674-8042(2018)03-0269-10doi: 10.3969/j.issn.1674-8042.2018.03.009
References
[1]Wang Z B. Wind power abandoned rationing report of China. Energy, 2014: 42-48.
[2]Mu G, Cui Y, Liu J, et al. Source-grid coordinated dispatch method for transmission constrained grid with surplus wind generators. Automation of Electric Power Systems, 2013, 37(6): 24-29
[3]Wang X H, Qiao Y, Lu Z X, et al. A novel method to assess wind energy usage in the heat-supplied season. Proceedings of the CSEE, 2015, 35(9): 2112-2119.
[4]Gu Z P, Kang C Q, Chen X Y, et al. Operation optimization of integrated power and heat energy systems and the benefit on wind power accommodation considering heating network constraints. Proceedings of the CSEE, 2015, 35(14): 3596-3604.
[5]Yuan X M, Cheng S J, Wen J Y. Prospects analysis of energy storage application in grid integration of large-scale wind power. Automation of Electric Power Systems, 2013, 37(1): 14-18.
[6]Liu D Y, Tan Z Z, Wang F. Study on combined system with wind power and pumped storage power. Water Resources and Power, 2006, 24(6): 39-42.
[7]Yan G G, Liu J, Cui Y, et al. Economic evaluation on improving wind power scheduling scale by using energy storage systems. Proceedings of the CSEE, 2013, 33(22): 45-52.
[8]Hu Z C, Ding H J, Kong T. A joint daily operational optimization model for wind power and pumped-storage plant. Automation of Electric Power Systems, 2012, 36(2): 36-41.
[9]Li F, Zhang L Z, Shu J, et al. A study on peak load regulation and economic leaning of wind power and energy storage system. East China Electric Power, 2012, 40(10): 1696-1700.
[10]Lyu Q, Chen T Y, Wang H X, et al. Combined heat and power dispatch model for power system with heat accumulator. Electric Power Automation Equipment, 2014, 34(5): 79-85.
[11]Lyu Q, Jiang H, Chen T Y, et al. Wind power accommodation by combined heat and power plant with electric boiler and its national economic evaluation. Automation of Electric Power Systems, 2014, 38(1): 6-12.
[12]Jiang Q Y, Hong H S. Wavelet-based capacity Configuration and coordinated control of hybrid energy storage system for smoothing out wind power fluctuations. IEEE Transactions on Power Systems, 2013, 28(2): 1363-1372.
[13]Ai X, Liu X. Chance constrained model for wind power usage based on demand response. Journal of North China Electric Power University (Natural Science Edition), 2011, 38(3): 17-35.
[14]Guo J J, Wu H B. Hybrid energy storage coordinated optimal control method for stabilizing wind power fluctuation. Acta Energiae Solaris Sinica, 2016, 37(10): 2695-2702.
[15]Chen N, Yu J L. Active power dispatch and regulation of wind power system based on electrical dissecting information of electric power network. Proceedings of the CSEE, 2008, 28(16): 51-58.
[16]Geem Z W, Kim J H, Loganathan G V. A new heuristic optimization algorithm: harmony search. Simulation, 2011, 76(2): 60-68.
[17]Zou D X, Gao L Q, Wu J H, et al. A novel global harmony search algorithm for reliability problems. Computers & Industrial Engineering, 2010, 58(2): 307-316.
基于电蓄热与抽水蓄能的风电消纳协调控制策略
李守东1, 董海鹰1, 张蕊萍1, 马喜平2
(1. 兰州交通大学 自动化与电气工程学院, 甘肃 兰州 730070; 2. 国网甘肃省电力公司 电力科学研究院, 甘肃 兰州 730050)
摘要:为解决“三北”地区冬季供热期由于热电机组“以热定电”运行约束而导致的严重弃风问题, 该文在研究电热负荷与风电出力分布特性以及不同时间尺度风功率波动特性的基础上, 提出了基于电蓄热与抽水蓄能的两级协调控制策略。 第一级协调控制以系统运行成本最小和风电利用率最大为目标, 根据电热负荷和风电预测出力, 通过电蓄热与抽水蓄能在调节容量上的优化配置, 提高系统运行经济性和风电消纳率; 第二级协调控制针对风电出力的实时波动, 根据风电计划上网偏差, 通过电蓄热与抽水蓄能的协调控制, 平抑风电实时波动, 提高风电消纳水平。 结合甘肃酒泉实际运行的风电场站, 所提出的协调控制策略的有效性得到验证。
关键词:风电消纳; 电蓄热; 抽水蓄能; 风电波动; 协调控制
引用格式: LI Shou-dong, DONG Hai-ying, ZHANG Rui-ping, et al. Coordinated control strategy for wind power accommodation based on electric heat storage and pumped storage. Journal of Measurement Science and Instrumentation, 2018, 9(3): 269-278. [doi:10.3969/j.issn.1674-8042.2018.03.009]
[full text full]