您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(工学版)》

山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (5): 111-122.doi: 10.6040/j.issn.1672-3961.0.2021.459

• • 上一篇    

高比例风电接入下计及时段间耦合旋转备用响应风险的动态经济调度方法

孙东磊1,杨思1,韩学山2,叶平峰2*,王宪1,刘蕊1   

  1. 1.国网山东省电力公司经济技术研究院, 山东 济南 250021;2.山东大学电气工程学院, 山东 济南 250061
  • 发布日期:2022-10-20
  • 作者简介:孙东磊(1988— ),男,山东济宁人,高级工程师,博士,主要研究方向为高比例新能源电力系统规划技术研究. E-mail:sdusdlei@sina.com. *通信作者简介:叶平峰(1988— ),男,浙江绍兴人,博士,主要研究方向为电力系统优化调度和电压稳定分析. E-mail:ypfinput@163.com
  • 基金资助:
    国网山东省电力公司科技资助项目(52062519000V)

Dynamic economic dispatching method considering time-coupling spinning reserve response risk for power system with high proportion of wind power

SUN Donglei1, YANG Si1, HAN Xueshan2, YE Pingfeng2*, WANG Xian1, LIU Rui1   

  1. 1. Economic &
    Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, Shandong, China;
    2. School of Electrical Engineering, Shandong University, Jinan 250061, Shandong, China
  • Published:2022-10-20

摘要: 针对目前动态经济调度研究中风电波动性和不确定性引发旋转备用响应风险难以有机考虑的问题,提出一种针对高风电接入比例下的动态经济调度方法。将机组强迫停运引发的旋转备用响应风险有机统一到时间耦合引起的响应风险中,将旋转备用响应风险的用户停电损失期望和弃风损失期望加入目标函数中,在寻求目标函数最小的同时,自动为系统配置适宜备用,保证各时段系统响应风险的一致性。利用改进的多宇宙并行量子遗传算法以及图形处理器(graphics processing unit, GPU)加速技术对模型进行求解。10机系统算例及其分析证明了该方法的有效性和可行性,能够在动态经济调度中准确度量风电波动性和不确定性共同引发的旋转备用响应风险。

关键词: 电力系统, 动态经济调度, 旋转备用, 响应风险, 多宇宙并行量子遗传算法

中图分类号: 

  • TM732
[1] 白建华,辛颂旭,刘俊,等. 中国实现高比例可再生能源发展路径研究[J]. 中国电机工程学报,2015,35(14):3699-3705. BAI Jianhua, XIN Songxu, LIU Jun, et al. Roadmap of realizing the high penetration renewable energy in China[J]. Proceedings of the CSEE, 2015, 35(14):3699-3705.
[2] HAND M M, BALDWIN S, DEMEO E, et al. Renewable electricity futures study[R]. Colorado, USA: National Renewable Energy Laboratory, 2014.
[3] SCHELLEKENS G, BATTAGLINI A, LILLIESTAM J, et al. 100% renewable electricity:a roadmap to 2050 for Europe and North Africa[M]. London, Britain:Pricewaterhouse Coopers, 2010: 1-13.
[4] 国家能源局.国家能源局关于印发《风电发展“十三五”规划》的通知[EB/OL].(2016-11-16)[2016-11-29]. http://www.nea.gov.cn/2016-11/29/c_135867633.htm. National Energy Administration. Wind power development in the National Energy Administration on issuing the “Thirteen-Five” planning notice [EB/OL].(2016-11-16)[2016-11-29]. http://www.nea.gov.cn/2016-11/29/c_135867633.htm.
[5] 王士柏,韩学山,杨明,等.计及间歇性特征的电力系统区间经济调度[J].中国电机工程学报,2016,36(11):2966-2977. WANG Shibo, HAN Xueshan, YANG Ming, et al. Interval economic dispatch of power system considering intermittent feature[J]. Proceedings of the CSEE, 2016, 36(11):2966-2977.
[6] 柳进,于继来,柳焯.针对风电间歇性扰动的旋转备用智能优化调度策略[J].中国电机工程学报,2013,33(1):163-170. LIU Jin, YU Jilai, LIU Zhuo. An intelligent optimal dispatch strategy for spinning reserve coping with wind intermittent disturbance[J]. Proceedings of the CSEE, 2013, 33(1):163-170.
[7] 吉兴全,郝晴,张玉敏,等.分布不确定性条件下的N-k分布鲁棒优化机组组合[J].电力系统自动化,2022,46(2):56-64. JI Xingquan, HAO Qing, ZHANG Yumin, et al. Unit commitment based on N-k distributionally robust optimization under uncertain distribution[J]. Automation of Electric Power Systems, 2022, 46(2):56-64.
[8] 吉兴全,张朔,张玉敏,等.基于IELM 算法的配电网故障区段定位[J].电力系统自动化,2021,45(22):157-166. JI Xingquan, ZHANG Shuo, ZHANG Yumin, et al. Fault section location for distribution network based on improved electromagnetism-like machanism algorithm[J]. Automation of Electric Power Systems, 2021, 45(22):157-166.
[9] HAN Xueshan, GOOI H B, KIRSCHEN D S. Dynamic economic dispatch: feasible and optimal solutions[J]. IEEE Transactions on Power Systems, 2001, 16(1):22-28.
[10] 周玮,彭昱,孙辉,等.含风电场的电力系统动态经济调度[J].中国电机工程学报,2009,29(25):13-18. ZHOU Wei, PENG Yu, SUN Hui, et al. Dynamic economic dispatch in wind power integrated system[J]. Proceedings of the CSEE, 2009, 29(25):13-18.
[11] 孙元章,吴俊,李国杰,等.基于风速预测和随机规划的含风电场电力系统动态经济调度[J].中国电机工程学报,2009,29(4):41-47. SUN Yuanzhang, WU Jun, LI Guojie, et al. Dynamic economic dispatch considering wind power penetration based on wind speed forecasting and stochastic programming[J]. Proceedings of the CSEE, 2009, 29(4):41-47.
[12] LEE T Y. Optimal spinning reserve for a wind-thermal power system using EIPSO[J]. IEEE Transactions on Power Systems, 2007, 22(4):1612-1621.
[13] TROY N, DENNY E, O'MALLEY M. Base-load cycling on a system with significant wind penetration[J]. IEEE Transactions on Power Systems, 2010, 25(2):1088-1097.
[14] 刘德伟,郭剑波,黄越辉,等.基于风电功率概率预测和运行风险约束的含风电场电力系统动态经济调度[J].中国电机工程学报,2013,33(16):9-15. LIU Dewei, GUO Jianbo, HUANG Yuehui, et al. Dynamic economic dispatch of wind integrated power system based on wind power probabilistic forecasting and operation risk constraints[J]. Proceedings of the CSEE, 2013, 33(16):9-15.
[15] 韩学山.动态优化调度的积留量法[D].哈尔滨:哈尔滨工业大学,1994. HAN Xueshan. The accumulation variable method of dynamic optimal dispatch[D]. Harbin:Harbin Institute of Technology,1994.
[16] 杨明,韩学山,梁军,等. 计及用户停电损失的动态经济调度方法[J].中国电机工程学报, 2009,29(31): 103-108. YANG Ming, HAN Xueshan, LIANG Jun, et al. Novel solution to dynamic economic dispatch considering customer interruption costs[J]. Proceedings of the CSEE, 2009, 29(31):103-108.
[17] 周玮,孙辉,顾宏,等. 计及风险备用约束的含风电场电力系统动态经济调度[J]. 中国电机工程学报, 2012, 32(1):47-55. ZHOU Wei, SUN Hui, GU Hong, et al. Dynamic economic dispatch of wind integrated power systems based on risk reserve constraints[J]. Proceedings of the CSEE, 2012, 32(1):47-55.
[18] 罗超,杨军,孙元章,等. 考虑备用容量优化分配的含风电电力系统动态经济调度[J]. 中国电机工程学报, 2014,34(34):6109-6118. LUO Chao, YANG Jun, SUN Yuanzhang, et al. Dynamic economic dispatch of wind integrated power system considering optimal scheduling of reserve capacity[J]. Proceedings of the CSEE, 2014, 34(34):6109-6118.
[19] NAVID N. Market solutions for managing ramp flexibility with high penetration of renewable resource[J]. IEEE Trans on Sustainable Energy, 2012, 3(4):784-790.
[20] 鲁宗相,李海波,乔颖. 高比例可再生能源并网的电力系统灵活性评价与平衡机理[J]. 中国电机工程学报,2017,37(1):9-19. LU Zongxiang, LI Haibo, QIAO Ying. Flexibility evaluation and supply/demand balance principle of power system with high-penetration renewable electricity [J]. Proceedings of the CSEE, 2017, 37(1):9-19.
[21] WU C, HUG G, KAR S. Risk-limiting economic dispatch for electricity markets with flexible ramping products[J]. IEEE Trans on Power Systems, 2016, 31(3):1990-2003.
[22] BILLINTON R, ALLAN R N. Reliability evaluation of power systems [M]. New York, America:Plenum Press, 1996:215-224.
[23] ORTEGA-VAZQUEZ M A, KIRSCHEN D S. Estimating the spinning reserve requirements in systems with significant wind power generation penetration[J]. IEEE Transactions on Power Systems, 2009, 24(1):114-124.
[24] FABBRI A, GOMEZSANROMAN T, RIVIERABBAD J, et al. Assessment of the cost associated with wind generation prediction errors in a liberalized electricity market[J]. IEEE Transactions on Power Systems, 2005, 20(3):1440-1446.
[25] MILLER I. Probability, random variables, and stochastic processes[J]. Technometrics, 2012, 8(2): 378-380.
[26] SODER L. Reserve margin planning in a wind-hydro-thermal power system[J]. IEEE Transactions on Power Systems, 1993, 8(2): 564-571.
[27] DOHERTY R, O MALLEY M. A new approach to quantify reserve demand in systems with significant installed wind capacity[J]. IEEE Transactions on Power Systems, 2005, 20(2): 587-595.
[28] BOUFFARD F, GALIANA F D. Stochastic security for operations planning with significant wind power generation[J]. IEEE Transactions on Power Systems, 2008, 23(2): 306-316.
[29] 韩学山,柳焯. 考虑机组爬坡速度和网络安全约束的经济调度解耦算法[J].电力系统自动化,2002,26(13):32-37. HAN Xueshan, LIU Zhuo. Decoupled economic dispatch including unit ramp rate and network security constraints[J]. Automation of Electric Power Systems, 2002, 26(13):32-37.
[30] 孙东磊. 电力系统源、网协同调度的理论研究[D]. 济南:山东大学, 2016. SUN Donglei. Thepretical studies on synergistic dispatch of power source and electric network in power system[D]. Jinan: Shandong University, 2016.
[31] BOUFFARD F, GALIANA F D. An electricity market with a probabilistic spinning reserve criterion[J]. IEEE Transactions on Power Systems, 2004, 19(1):300-307.
[32] HAN K, KIM J H. Genetic quantum algorithm and its application to combinatorial optimization problem[C] //Proceedings of the 2000 Congress on Evolutionary Computation. CEC00(Cat. No.00TH8512). La Jolla, USA: IEEE, 2002.
[33] 杨俊安,庄镇泉,史亮. 多宇宙并行量子遗传算法[J]. 电子学报, 2004, 32(6):923-928. YANG Junan, ZHUANG Zhenquan, SHI Liang. Multi-universe parallel quantum genetic algorithm[J]. Acta Electronica Sinica, 2004, 32(6):923-928.
[34] MILLIGAN M, KIRBY B. Calculating wind integration costs:separating wind energy value from integration cost impacts[R]. Golden,Colorado: National Renewable Energy Laboratory, 2009.
[35] 李卫东,吴海波,武亚光,等.电力市场下AGC 机组调配的遗传算法[J].电力系统自动化,2003,27(15):20-24. LI Weidong, WU Haibo, WU Yaguang, et al. Application of genetic algorithm to agc service dispatch in a deregulated power system [J].Automation of Electric Power Systems, 2003, 27(15):20-24.
[1] 韩学山,李克强. 适应新型电力系统发展的协同调度理论研究[J]. 山东大学学报 (工学版), 2022, 52(5): 14-23.
[2] 孙润稼,朱海南,刘玉田. 基于偏好多目标优化和遗传算法的输电网架重构[J]. 山东大学学报 (工学版), 2019, 49(5): 17-23.
[3] 梁志祥,刘晓明,牟颖,刘玉田. 基于深度学习的新能源爬坡事件预测方法[J]. 山东大学学报 (工学版), 2019, 49(5): 24-28.
[4] 刘玉田, 孙润稼, 王洪涛, 顾雪平. 人工智能在电力系统恢复中的应用综述[J]. 山东大学学报 (工学版), 2019, 49(5): 1-8.
[5] 刘萌,徐陶阳,李常刚,吴越,王智,史方芳,苏建军,张国辉,李宽. 基于粒子群算法的受端电网紧急切负荷优化[J]. 山东大学学报 (工学版), 2019, 49(1): 120-128.
[6] 钱淑渠,武慧虹,徐国峰,金晶亮. 计及排放的动态经济调度免疫克隆演化算法[J]. 山东大学学报(工学版), 2018, 48(4): 1-9.
[7] 王辉,陈立征,周刚,刘泊辰,于洋,刘刚,冯忠奎,靳宗帅. 基于WAMS Light的配电网电压安全在线评估[J]. 山东大学学报(工学版), 2017, 47(6): 39-45.
[8] 侯广松,高军,吴衍达,张欣,邓影,李常刚,张亚萍. 输电线路参数与运行方式的相关性分析[J]. 山东大学学报(工学版), 2017, 47(4): 89-95.
[9] 孙一冰,付敏跃,王炳昌,张焕水. 大规模动态系统的分布式状态估计算法[J]. 山东大学学报(工学版), 2016, 46(6): 62-68.
[10] 刘向杰,韩耀振. 基于连续高阶模滑的多机电力系统励磁控制[J]. 山东大学学报(工学版), 2016, 46(2): 64-71.
[11] 潘志远1, 韩学山1*, 刘超男2. 交流潮流约束下的机组组合求解[J]. 山东大学学报(工学版), 2012, 42(2): 130-137.
[12] 杨朋朋,王葵,李磊,赵兰明. 机组组合问题的两层优化研究[J]. 山东大学学报(工学版), 2011, 41(3): 167-172.
[13] 曹刚 董朝阳 黄洁宝 薛禹胜. 应用FACTS装置实现电力系统区间震荡阻尼控制[J]. 山东大学学报(工学版), 2009, 39(3): 31-36.
[14] 刘允刚. 一类一阶控制系数未知非线性系统有限时间镇定[J]. 山东大学学报(工学版), 2009, 39(3): 37-46.
[15] 孙炜伟,王玉振. 考虑饱和的发电机单机无穷大系统有限增益镇定[J]. 山东大学学报(工学版), 2009, 39(1): 69-76.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!