计及深度调峰辅助服务与多典型日的年度发电计划优化模型
作者:
作者单位:

1.重庆电力交易中心有限公司,重庆 400013;2.重庆大学 输配电装备及系统安全与新技术 国家重点实验室,重庆 400044

作者简介:

张爱枫(1967—),女,高级工程师,主要从事电力系统继电保护与控制、电力市场交易研究,(E-mail)cqsee-zh@qq.com。

通讯作者:

颜伟,男,博士,教授,博士生导师,(E-mail) cquyanwei@cqu.edu.cn。

中图分类号:

TM732


Annual power generation plan optimization model considering deep peak regulation auxiliary services and multiple typical days
Author:
Affiliation:

1.Chongqing Electric Power Trading Center Co., Ltd., Chongqing 400013, P. R. China;2.State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, P. R. China

  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [26]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    在调峰市场背景下,机组调峰成本与辅助服务费用对发电企业影响较大,据此,提出了计及深度调峰辅助服务与多典型日的年度发电计划优化模型。在场景获取方面,提出了考虑负荷与风电耦合的典型场景聚类方法,有效解决了月内多个典型日场景的模拟问题。在模型方面,考虑了深度调峰成本、辅助服务补偿费用、售电利益与碳交易成本,建立了发电企业参与深度调峰辅助服务市场的收益约束,确保市场各主体能从中获利。考虑到该模型属于非线性混合整数规划模型,结合线性化策略和CPLEX求解器实现了高效求解。最后,基于修正算例系统进行了仿真分析,验证了所提模型的有效性。

    Abstract:

    In the context of the deep peak regulation auxiliary service market, the costs of unit peak regulation and auxiliary service fees have a significant impact on power generation companies. To address this issue, this paper proposes an optimization model for annual generation plan that takes into account deep peak regulation auxiliary services and multiple typical days. To achieve effective scene acquisition, a typical scene clustering method with considering the coupling of load and wind power is proposed, thereby effectively solving the simulation problem of multiple typical daily scenes in a month. By considering the deep peak regulation cost, auxiliary services compensation, benefit from electricity sales and carbon trading cost, the model established the income constraints of generation companies participating in the auxiliary service market to ensure profitability for market entities. As the model is a nonlinear mixed integer programming problem, this paper uses linearization strategy and CPLEX solver to achieve an efficient solution. Finally, simulation analysis is conducted using a modified example system, verifying the effectiveness of the proposed model.

    参考文献
    [1] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11.Kang C Q, Yao L Z. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 2-11.(in Chinese)
    [2] Yaramasu V, Wu B, Sen P C, et al. High-power wind energy conversion systems: State-of-the-art and emerging technologies[J]. Proceedings of the IEEE. 2015, 103(5): 740-788.
    [3] Burke M J, Stephens J C. Political power and renewable energy futures: a critical review[J]. Energy Research & Social Science, 2018, 35:78-93.
    [4] 林俐, 邹兰青, 周鹏, 等. 规模风电并网条件下火电机组深度调峰的多角度经济性分析[J]. 电力系统自动化, 2017, 41(7): 21-27.Lin L, Zou L Q, Zhou P, et al. Multi-angle economic analysis on deep peak regulation of thermal power units with large-scale wind power integration[J]. Automation of Electric Power Systems, 2017, 41(7): 21-27.(in Chinese)
    [5] Lee Y Y, Baldick R. A frequency-constrained stochastic economic dispatch model[J]. IEEE Transactions on Power Systems, 2013, 28(3): 2301-2312.
    [6] Hetzer J, Yu D C, Bhattarai K. An economic dispatch model incorporating wind power[J]. IEEE Transactions on Energy Conversion, 2008, 23(2): 603-611.
    [7] 林俐, 田欣雨. 基于火电机组分级深度调峰的电力系统经济调度及效益分析[J]. 电网技术, 2017, 41(7): 2255-2263.Lin L, Tian X Y. Analysis of deep peak regulation and its benefit of thermal units in power system with large scale wind power integrated[J]. Power System Technology, 2017, 41(7): 2255-2263.(in Chinese)
    [8] 祁乐, 陈标, 江平, 等. 燃煤火电机组提供调峰辅助服务的成本和效益分析[J]. 电力大数据, 2019, 22(10): 23-29.Qi L, Chen B, Jiang P, et al. Cost and benefit analysis of peak regulation auxiliary services for coal-fired thermal power units[J]. Power Systems and Big Data, 2019, 22(10): 23-29.(in Chinese)
    [9] 李嘉龙, 陈雨果, 刘思捷, 等. 考虑深度调峰的电力日前市场机制设计[J]. 电力系统自动化, 2019, 43(4): 9-15,78.Li J L, Chen Y G, Liu S J, et al. Mechanism design of day-ahead market considering deep peak regulation[J]. Automation of Electric Power Systems, 2019, 43(4): 9-15,78.(in Chinese)
    [10] 田亮, 谢云磊, 周桂平, 等. 基于两阶段随机规划的热电机组深调峰辅助服务竞价策略[J]. 电网技术, 2019, 43(8): 2789-2798.Tian L, Xie Y L, Zhou G P, et al. Deep peak regulation ancillary service bidding strategy for CHP units based on two-stage stochastic programming[J]. Power System Technology, 2019, 43(8): 2789-2798.(in Chinese)
    [11] 董超, 张彦涛, 刘嘉宁, 等. 考虑火电机组深度调峰的实时发电计划模型及应用[J]. 电力自动化设备, 2019, 39(3): 108-113.Dong C, Zhang Y T, Liu J N, et al. Real-time generation scheduling model and its application considering deep peak regulation of thermal power units[J]. Electric Power Automation Equipment, 2019, 39(3): 108-113.(in Chinese)
    [12] 邓婷婷, 娄素华, 田旭, 等. 计及需求响应与火电深度调峰的含风电系统优化调度[J]. 电力系统自动化, 2019, 43(15): 34-41.Deng T T, Lou S H, Tian X, et al. Optimal dispatch of power system integrated with wind power considering demand response and deep peak regulation of thermal power units[J]. Automation of Electric Power Systems, 2019, 43(15): 34-41.(in Chinese)
    [13] 邓婷婷. 考虑源荷双端灵活性的电力系统优化调度研究[D]. 武汉: 华中科技大学, 2019.Deng T T. Optimal dispatch of power system considering the flexibility of demand side and power generation side[D]. Wuhan: Huazhong University of Science and Technology, 2019. (in Chinese)
    [14] 王淑云, 娄素华, 刘文霞, 等. 考虑火电深度调峰的电力系统低碳发电优化研究[J]. 全球能源互联网, 2019, 2(3): 226-231.Wang S Y, Lou S H, Liu W X, et al. Study on optimization of low-carbon power generation in power system considering the depth peak regulation of thermal power units[J]. Journal of Global Energy Interconnection, 2019, 2(3): 226-231.(in Chinese)
    [15] 李军徽, 张嘉辉, 穆钢, 等. 储能辅助火电机组深度调峰的分层优化调度[J]. 电网技术, 2019, 43(11): 3961-3970.Li J H, Zhang J H, Mu G, et al. Hierarchical optimization scheduling of deep peak shaving for energy-storage auxiliary thermal power generating units[J]. Power System Technology, 2019, 43(11): 3961-3970.(in Chinese)
    [16] Zhang N, Kang C Q, Kirschen D S, et al. Planning pumped storage capacity for wind power integration[J]. IEEE Transactions on Sustainable Energy, 2013, 4(2): 393-401.
    [17] 李铁, 李正文, 杨俊友, 等. 计及调峰主动性的风光水火储多能系统互补协调优化调度[J]. 电网技术, 2020, 44(10): 3622-3630.Li T, Li Z W, Yang J Y, et al. Coordination and optimal scheduling of multi-energy complementary system considering peak regulation initiative[J]. Power System Technology, 2020, 44(10): 3622-3630.(in Chinese)
    [18] Kazempour S J, Conejo A J, Ruiz C. Strategic generation investment using a complementarity approach[J]. IEEE Transactions on Power Systems, 2011, 26(2): 940-948.
    [19] Kim M, Ramakrishna R S. New indices for cluster validity assessment[J]. Pattern Recognition Letters, 2005, 26(15): 2353-2363.
    [20] 国家能源局华中监管局, 重庆市经济和信息化委员会. 重庆电力辅助服务(调峰)交易规则[EB/OL]. (2019-04-29) [2021-04-15]. https://shoudian.bjx.com.cn/html/20190429/977900.shtml.Central China Energy Regulatory Bureau of National Energy Administration of the People’s Republic of China, Chongqing Economic and Information Commission. Chongqing auxiliary service (peak regulation) trading rules[EB/OL]. (2019-04-29) [2021-04-15]. https://shoudian.bjx.com.cn/html/20190429/977900.shtml.(in Chinese)
    [21] 生态环境部. 2019-2020年全国碳排放权交易配额总量设定与分配实施方案(发电行业)[EB/OL]. (2020-12-30.) [2021-04-15]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/202012/t20201230_815546.html.Ministry of Ecology and Environment of the People’s Republic of China. 2019-2020 national carbon emission trading quota setting and allocation implementation plan (power generation industry) [EB/OL]. (2020-12-30) [2021-04-15]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/202012/t20201230_815546.html.(in Chinese)
    [22] 周一凡, 胡伟, 闵勇, 等. 考虑热电联产调峰主动性的电热协调调度[J]. 电力系统自动化, 2019, 43(19): 42-51.Zhou Y F, Hu W, Min Y, et al. Coordinated power and heat dispatch considering peak regulation initiative of combined heat and power unit[J]. Automation of Electric Power Systems, 2019, 43(19): 42-51.(in Chinese)
    [23] Carrion M, Arroyo J M. A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem[J]. IEEE Transactions on Power Systems, 2006, 21(3): 1371-1378.
    [24] 葛晓琳. 水火风发电系统多周期联合优化调度模型及方法[D]. 北京: 华北电力大学, 2013.Ge X L. Multi-period optimal scheduling models and methods for hydro-thermal-wind power system[D]. Beijing: North China Electric Power University, 2013. (in Chinese)
    [25] 王淑云, 娄素华, 吴耀武, 等. 计及火电机组深度调峰成本的大规模风电并网鲁棒优化调度[J]. 电力系统自动化, 2020, 44(1): 118-125.Wang S Y, Lou S H, Wu Y W, et al. Robust optimal dispatch of large-scale wind power integration considering deep peak regulation cost of thermal power units[J]. Automation of Electric Power Systems, 2020, 44(1): 118-125.(in Chinese)
    [26] 国家能源局华中监管局. 华中区域并网发电厂辅助服务管理实施细则[EB/OL]. (2020-09-07)[2021-03-01]. http://hzj.nea.gov.cn/adminContent/initViewContent.do?pk=AEB05CC013329FBDE050A8C0C1C8659B.Central China Energy Regulatory Bureau of National Energy Administration of the People’s Republic of China. Implementation rules for auxiliary service management of grid connected power plants in Central China [EB/OL]. (2020-09-07)[2021-03-01]. http://hzj.nea.gov.cn/adminContent/initViewContent.do?pk=AEB05CC013329FBDE050A8C0C1C8659B.(in Chinese)
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

张爱枫,刘或让,王勇,艾林,周颖,蒋振涌,桑福敏,林祖贵,颜伟.计及深度调峰辅助服务与多典型日的年度发电计划优化模型[J].重庆大学学报,2023,46(8):20-31.

复制
分享
文章指标
  • 点击次数:283
  • 下载次数: 829
  • HTML阅读次数: 86
  • 引用次数: 0
历史
  • 收稿日期:2021-10-28
  • 在线发布日期: 2023-08-25
文章二维码