基于“虚拟水库”的梯级水电现货报价单元组建方法

doi:10.19595/j.cnki.1000-6753.tces.210079

Abstract
Figure/Table
References
Related Citation (3)

Download: PDF (2209 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract There is a highly coupled space-time hydraulic connection between cascade hydropower plants, and due to the different locations in the basin and adjustment capabilities, the market competitiveness and quotation flexibility of various hydropower plants vary greatly, which increases the difficulty and risk of bidding in the spot market. Participating in the market with quotation units is beneficial to resist risks, but how to choose partners is very important. Based on runoff connections in the basin, this paper introduced the concept of "virtual reservoir" and put forward a new spot quotation unit construction method of cascade hydropower, then designed a complete bidding process in the spot market for the quotation unit. A two-layer simulation model was established based on the interests of both power purchase and sales. Finally, a case study was carried out with a cascade hydropower quotation unit in a river basin in Sichuan Province. The results show that participating in the market with a “virtual reservoir” quotation unit can increase the market share of each member, expand the quotation space, reduce market risks, increase net income, and at the same time reduce the purchase cost of electricity, which verifies the scientificity and correctness of the quotation unit based on the “virtual reservoir”.

Key words： Cascade hydropower electricity spot market quotation unit virtual reservoir

Received: 16 January 2021

PACS:

TM612

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhang Hongtu
	Xiong Zhijie
	Zhu Yanmei
	Huang Weibin
	Chen Shijun

Cite this article:

Zhang Hongtu,Xiong Zhijie,Zhu Yanmei等. Spot Quotation Unit Construction Method of Cascade Hydropower Based on “Virtual Reservoir”[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 719-728.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210079 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I3/719

[1] 路轶, 胡晓静, 孙毅, 等. 适应四川高水电占比特色的电力现货市场机制设计与实践[J/OL]. 电力系统自动化:1-9[2021-03-17]. http://kns.cnki.net/kcms/ detail/32.1180.TP. 20201218.1421.004. html.
Lu Yi, Hu Xiaojing, Sun Yi, et al. Design and practice of electricity spot market mechanism adapting to characteristics of high proportional hydropower in Sichuan province[J/OL]. Automation of Electric Power Systems:1-9[2021-03-17]. http://kns.cnki.net/ kcms/detail/32.1180.TP.20201218.1421.004.html.
[2] 张粒子, 刘方, 许通, 等. 多运营主体梯级水电站参与的日前市场出清模型[J]. 电力系统自动化, 2018, 42(16): 104-110.
Zhang Lizi, Liu Fang, Xu Tong, et al.A market clearing model with multi-operator cascade hydropower stations[J]. Automation of Electric Power Systems, 2018, 42(16): 104-110.
[3] 莫东, 凌武能, 毛文照, 等. 电力现货市场年度基数电量分解方法研究[J]. 电力学报, 2019, 34(6): 598-603.
Mo Dong, Ling Wuneng, Mao Wenzhao, et al.Study on the decomposition of annual base electricity in spot power market[J]. Journal of Electric Power, 2019, 34(6): 598-603.
[4] 杨智宇, 刘俊勇, 刘友波, 等. 四川建设现货市场面临的问题与解决方案[C]//中国电机工程学会电力市场专业委员会2018年学术年会暨全国电力交易机构联盟论坛论文集, 上海, 2018.
[5] 柴雁欣, 刘俊勇, 刘继春, 等. 基于国外电力现货市场分析的四川省电力现货市场交易模式初探[C]// 中国电机工程学会电力市场专业委员会2018年学术年会暨全国电力交易机构联盟论坛论文集, 上海, 2018.
[6] 袁贵川, 李荣, 李金龙, 等. 日内现货交易环境中智能发电调度系统的设计与实现[J]. 四川电力技术, 2019, 42(3): 85-89.
Yuan Guichuan, Li Rong, Li Jinlong, et al.Design and implementation of intelligent power generation and distribution system in intraday spot market[J]. Sichuan Electric Power Technology, 2019, 42(3): 85-89.
[7] 张粒子, 刘方, 许通, 等. 多主体梯级水电参与日前市场下游电站自调度投标策略[J]. 电力系统自动化, 2018, 42(19): 27-33.
Zhang Lizi, Liu Fang, Xu Tong, et al.Self-scheduling bidding strategy for downstream station in day-ahead market with participation of multi-operator cascade hydropower stations[J]. Automation of Electric Power Systems, 2018, 42(19): 27-33.
[8] 邢玉辉, 王帮灿, 丁文娇, 等. 计及梯级水量匹配约束的中长期电量合约分解方法[J]. 云南电力技术, 2020, 48(3): 21-26.
Xing Yuhui, Wang Bangcan, Ding Wenjiao, et al.Mid-and long-term contract decomposition method considering cascade water quantity matching constraint[J] Yunnan Electric Power, 2020, 48(3): 21-26.
[9] 李翔宇, 赵冬梅. 基于模糊-概率策略实时反馈的虚拟电厂多时间尺度优化调度[J]. 电工技术学报, 2021, 36(7): 1446-1455.
Li Xiangyu, Zhao Dongmei.Research on multi-time scale optimal scheduling of virtual power plant based on real-time feedback of fuzzy-probability strategy[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1446-1455.
[10] 段翩, 朱建全, 刘明波. 基于双层模糊机会约束规划的虚拟电厂优化调度[J]. 电工技术学报, 2016, 31(9): 58-67.
Duan Pian, Zhu Jianquan, Liu Mingbo.Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J]. Transactions of China Electrotechnical Society, 2016, 31(9): 58-67.
[11] Selim K S, Abdalbaki S M.On the relationship between virtual water network and crops intra-trade among Nile basin countries[J]. Water Policy, 2019, 21(3): 481-495.
[12] Hassan R, Thiam D R.Implications of water policy reforms for virtual water trade between South Africa and its trade partners: economy-wide approach[J]. Water Policy, 2015, 17(4): 649-663.
[13] Youkhana E L W. Virtual water trade: a realistic policy option for the countries of the Volta Basin in West Africa?[J]. Water Policy, 2009, 11(5): 569-581.
[14] 张慧, 唐勇, 唐红兵, 等. 虚拟水库模型及虚拟水库水位计算方法: 中国, CN109117592A[P].2019-01-01.
[15] 马琴, 刘懿, 孟长青, 等. 基于虚拟水库模型的无资料地区小流域山洪预警方法[J]. 水电能源科学, 2019, 37(6): 60-63.
Ma Qin, Liu Yi, Meng Changqing, et al.Method of mountain flood warning in small watershed without data based on virtual reservoir model[J]. Water Resources and Power, 2019, 37(6): 60-63.
[16] 范玉宏, 丁珩, 张维, 等. 电力现货市场建设关键问题研究[J]. 湖北电力, 2018, 42(2): 49-54.
Fan Yuhong, Ding Heng, Zhang Wei, et al.Study on key issues in power spot market construction[J]. Hubei Electric Power, 2018, 42(2): 49-54.
[17] 赵波, 汪湘晋, 张雪松, 等. 考虑需求侧响应及不确定性的微电网双层优化配置方法[J]. 电工技术学报, 2018, 33(14): 3284-3295.
Zhao Bo, Wang Xiangjin, Zhang Xuesong, et al.Two-layer method of microgrid optimal sizing considering demand-side response and uncertainties[J]. Transactions of China Electrotechnical Society, 2018, 33(14): 3284-3295.
[18] 张晓辉, 李阳, 钟嘉庆, 等. 基于安全因子及协同因子的源网多目标协调规划[J]. 电工技术学报, 2021, 36(9): 1842-1856.
Zhang Xiaohui, Li Yang, Zhong Jiaqing, et al.Multi-objective coordinated planning of source network based on safety factor and coordination factor[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1842-1856.
[19] 郭通, 李永刚, 徐姗姗, 等. 考虑多主体博弈的火电机组灵活性改造规划[J]. 电工技术学报, 2020, 35(11): 2448-2459.
Guo Tong, Li Yonggang, Xu Shanshan, et al.Planning of flexibility retrofits of thermal power units considering multi-agent game[J]. Transactions of China Electrotechnical Society, 2020, 35(11): 2448-2459.
[20] 熊宇峰, 司杨, 郑天文, 等. 基于主从博弈的工业园区综合能源系统氢储能优化配置[J]. 电工技术学报, 2021, 36(3): 507-516.
Xiong Yufeng, Si Yang, Zheng Tianwen, et al.Optimal configuration of hydrogen storage in industrial park integrated energy system based on stackelberg game[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 507-516.
[21] 周斌, 宋艳, 李金茗, 等. 基于多群组均衡协同搜索的多目标优化发电调度[J]. 电工技术学报, 2015, 30(22): 181-189.
Zhou Bin, Song Yan, Li Jinming, et al.Multiobjective optimal generation dispatch using equilibria-based multi-group synergistic searching algorithm[J]. Transactions of China Electrotechnical Society, 2015, 30(22): 181-189.
[22] 郭向伟, 耿佳豪, 刘震, 等. 基于反激变换器的双目标直接均衡方法[J]. 电工技术学报, 2021, 36(6): 1269-1278.
Guo Xiangwei, Geng Jiahao, Liu Zhen, et al.The dual-objective direct balancing method based on flyback converter[J]. Transactions of China Electrotechnical Society, 2021, 36(6): 1269-1278.
[23] 袁立强, 陆子贤, 孙建宁, 等. 电能路由器设计自动化综述—设计流程架构和遗传算法[J]. 电工技术学报, 2020, 35(18): 3878-3893.
Yuan Liqiang, Lu Zixian, Sun Jianning, et al.Design automation for electrical energy router-design workflow framework and genetic algorithm: a review[J]. Transactions of China Electrotechnical Society, 2020, 35(18): 3878-3893.
[24] 黄辉, 吴正, 邹安安, 等. 基于遗传算法的汽车EPS电动助力转向电动机多目标优化[J]. 电气技术, 2019, 20(2): 48-52.
Huang Hui, Wu Zheng, Zou Anan, et al.Multi-objective optimization of electric power steering motor based on genetic algorithm[J]. Electrical Engineering, 2019, 20(2): 48-52.