JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (6): 89-94.doi: 10.6040/j.issn.1672-3961.0.2017.208

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Rolling optimal dispatch method of wind power based on distributed energy storage system

WANG Fei1, XU Jian2, LI Wei3, WANG Xinhao4*, SHI Xiaohan4   

  1. 1. State Grid Shandong Electric Power Company, Jinan 250001, Shandong, China;
    2. Maintenance Company, State Grid Shandong Electric Power Company, Jinan 250118, Shandong, China;
    3. Economic Research Institute, State Grid Shandong Electric Power Company, Jinan 250000, Shandong, China;
    4. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University), Jinan 250061, Shandong, China
  • Received:2017-04-25 Online:2017-12-20 Published:2017-04-25

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Abstract: According to the inherent characteristics of wind power that forecased accuracy increasing with the time-scale decreasing, a multi-time scale and multi-objective coordinated rolling optimal dispatch model was established. Based on the wind power grid-connected standards and combined with distributed battery energy storage system(DBESS), the low-frequency fluctuation of wind power could be damped in time. An optimized model was established with objectives of minimizing the economy of the system and the curtailed wind power. The IEEE 39-bus system with four wind farms and two battery energy storage systems(BESSs)was added for utilizing to verify the optimization dispatch model proposed, and it was solved by genetic algorithm(GA)iteratively. The results showed that the proposed wind-storage rolling optimal dispatch model based on DBESS could reduce the cost of the system operation and increase the amount of wind power griding effectively.

Key words: genetic algorithm(GA), wind power, rolling optimal, multi-objective optimal, wind-storage combined power system, coordinative dispatch

CLC Number: 

  • TM734
[1] 李琼慧, 王彩霞. 从电力发展“十三五”规划看新能源发展[J]. 中国电力, 2017, 50(1):30-36. LI Qionghui, WANG Caixia. Analysis on new energy development based on the 13th five-year electric power planning[J]. Electric Power, 2017, 50(1):30-36.
[2] 张运洲, 程路. 中国电力“十三五”及中长期发展的重大问题研究[J].中国电力, 2015, 48(1):1-5. ZHANG Yunzhou, CHENG Lu. Research on major issues of the 13th Five-Year Plan development of power industry[J]. Electric Power, 2015, 48(1):1-5.
[3] 张恒旭, 施啸寒, 刘玉田, 等. 我国西北地区可再生能源基地对全球能源互联网构建的支撑作用[J]. 山东大学学报(工学版), 2016, 46(6): 96-101. ZHANG Hengxu, SHI Xiaohan, LIU Yutian, et al. Support of the renewable energy base in northwest of China on the construction of global energy interconnection[J]. Journal of Shandong University(Engineering Science), 2016, 46(6): 96-101.
[4] 佘慎思,李征,蔡旭. 风储联合发电系统电池荷电状态和功率偏差控制策略[J].电力系统自动化, 2014, 38(20):9-17. SHE Shensi, LI Zheng, CAI Xu. SOC and power deviation control strategy for hybrid generation systems of wind power and storage[J]. Automation of Electric Power Systems, 2014, 38(20):9-17.
[5] 谢俊文,陆继明,毛承雄,等.基于变平滑时间常数的电池储能系统优化控制方法[J].电力系统自动化,2013, 37(1):96-102. XIE Junwen, LU Jiming, MAO Chengxiong, et al. Optimal control of battery energy system based on variable smoothing time constant[J]. Automation of Electric Power Systems, 2013, 37(1):96-102.
[6] 张文亮, 邱明, 来小康. 储能技术在电力系统中的应用[J]. 电网技术, 2008, 32(7): 1-9. ZHANG Wenliang, QIU Ming, LAI Xiaokang. Application of energy storage technologies in power grids[J]. Power System Technology, 2008, 32(7):1-9.
[7] 程世杰, 余文辉, 文劲宇, 等. 储能技术及其在电力系统稳定控制中的应用[J]. 电网技术, 2007, 31(20): 97-108. CHENG Shijie, YU Wenhui, WEN Jingyu, et al. Energy storage technology and its application in power system stability enhancement[J]. Power System Technology, 2007, 31(20): 97-108.
[8] 宋豪,宋曙光,王超, 等. 抽水蓄能电站对山东电网风电接纳能力的影响[J]. 山东大学学报(工学版), 2011,41(5): 138-142. SONG Hao, SONG Shuguang, WANG Chao, et al. Impacts of the pumped storage power station on the wind generation integration capability of the Shandong Power Grid[J]. Journal of Shandong University(Engineering Science), 2011, 41(5): 138-142.
[9] 李金鑫, 张建成. 风光储发电系统预测功率波动性优 化方法[J]. 电源技术, 2013,137(1): 62-64, 140. LI Jinxin, ZHANG Jiancheng. Optimization method to fluctuations of predictive power of HPWS[J]. Power Technology, 2013, 137(1): 62-64,140.
[10] 黄杨, 胡伟,闵勇,等. 计及风险备用的大规模风储联合系统广域协调调度[J].电力系统自动化, 2014, 38(9): 41-47. HUANG Yang, HU Wei, MIN Yong, et al. Risk-constrained coordinative dispatching for large-scale wind-storage systems[J]. Automation of Electric Power Systems, 2014, 38(9): 41-47.
[11] 赵艳雷, 李海东, 张磊, 等. 基于快速储能的风电潮流优化控制系统[J]. 中国电机工程学报, 2012, 35(12): 21-28. ZHAO Yanlei, LI Haidong, ZHANG Lei, et al. Wind power flow optimization and control system based on rapid energy storage[J]. Proceedings of the CSEE, 2012, 35(12): 21-28.
[12] 孙春顺,王耀南,李欣然. 飞轮辅助的风力发电系统功率和频率综合控制[J]. 中国电机工程学报,2008,28(29): 111-116. SUN Chunshun, WANG Yaonan, LI Xinran. Synthesized power and frequency control of wind power generation system assisted through flywheels[J]. Proceedings of the CSEE, 2008, 28(29):111-116.
[13] 张伯明,吴文传,郑太一,等. 消纳大规模风电的多时间尺度协调的有功调度系统设计[J]. 电力系统自动化, 2011,35(1): 1-6. ZHANG Boming, WU Wenchuan, ZHENG Taiyi, et al. Design of a multi-time scale coordinated active power dispatching system for accommodating large scale wind power penetration[J]. Automation of Electric Power Systems, 2011, 35(1):1-6.
[14] 戚永志,刘玉田. 风光储联合系统输出功率滚动优化与 实时控制[J]. 电工技术学报, 2014, 29(8): 265-273. QI Yongzhi, LIU Yutian. Output power rolling optimization and real-time control of wind-solar storage combined system[J]. Techniques in Electrotechnics, 2014, 29(8): 265-273.
[15] MIAO Z X, XU L, DISFANI V R, et al. An SOC-based battery management system for microgrids[J]. IEEE Transactions on Smart Grid, 2014, 5(2): 966-973.
[16] URTASUN A, BARRIOS E L, SANCHIS P, et al. Frequency-based energy-management strategy for stand-alone systems with distributed battery storage[J]. IEEE Transactions on Power Electronics, 2015, 30(9): 4794-4807.
[17] ZHANG X S, YUAN Y, HUA L, et al. On generation schedule tracking of wind farms with battery energy storage systems[J]. IEEE Transactions on Sustainable Energy, 2017, 8(1): 341-353.
[18] 中华人民共和国国家质量监督检查检疫总局. 风电场接入电力系统技术规定:GB/T 19963-2011[S]. 北京:中国质检出版社,2011.
[19] 乔颖,鲁宗相. 考虑电网约束的风电场自动有功控制[J].电力系统自动化,2009,33(22):88-93. QIAO Ying, LU Zongxiang. Wind farms active power control considering constraints of power grids[J]. Automation of Electric Power Systems, 2009, 33(22): 88-93.
[20] YAN N, XING Z X, LI W, et al. Economic dispatch application of power system with energy storage systems[J]. IEEE Transactions on Applied Superconductivity, 2016, 26(7): 1-5.
[21] 蔡国伟,孔令杰,潘超,等. 风光储联合系统的建模及并网控制策略[J]. 电工技术学报, 2013, 28(9): 196-204. CAI Guowei, KONG Lingjie, PAN Chao, et al. Modeling and grid-connected control strategy of wind-solar storage combined system[J]. Techniques in Electrotechnology, 2013, 28(9): 196-204.
[22] RAGLEND I J, PADHY N P. Solutions to practical unit commitment problems with operational, power flow and environmental constraints[C] //Proceedings of IEEE on Power Engineering Society General Meeting, 2006. Montreal, Canada: IEEE, 2006: 1-8.
[23] 于大洋,韩学山,梁军,等.基于 NASA 地球观测数据库的区域风电功率波动特性分析[J].电力系统自动化,2011,35(5): 77-81. YU Dayang, HAN Xueshan, LIANG Jun, et al.Study on the profiling of China's regional wind power fluctuation using GEOS-5 data assimilation system of national aeronautics and space administration of America[J].Automation of Electric Power Systems, 2011, 35(5):77-81.
[24] 肖白,蒲睿,穆钢. 基于多尺度空间分辨率的空间负荷预测误差评价方法[J]. 中国电机工程学报,2015, 35(22):5731-5739. XIAO Bai, PU Rui, MU Gang. Method of spatial load forecasting error evaluation based on the multi-scale spatial resolution[J]. Proceedings of the CSEE, 2015, 35(22): 5731-5739.
[25] 杨薛明,苑津莎,王剑锋,等.基于云理论的配电网空间负荷预测方法研究[J].中国电机工程学报, 2006,26(6): 30-36. YANG Xueming, YUAN Jinsha, WANG Jianfeng, et al. A new spatial forecasting method for distribution network based on cloud theory[J]. Proceedings of the CSEE, 2006, 26(6): 30-36.
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