基于储能参与调节的源–储协调优化调度方法
Source-Storage Coordinated Optimal Scheduling Method Based on Energy Storage Participating in Regulation
DOI: 10.12677/SG.2021.116038, PDF,    科研立项经费支持
作者: 吴 悦, 韩旭杉, 周 强:国网甘肃省电力公司,甘肃 兰州;申自裕, 刘文颖:华北电力大学,新能源电力系统国家重点实验室,北京
关键词: 储能源–储协调优化调度新能源消纳场景分析法Energy Storage Source-Storage Coordinated Optimal Scheduling New Energy Consumption Scenario Analysis
摘要: 在我国“双碳”目标发展战略背景下,加快了以风光电为主的新能源发展速度,给电网调度运行带来了极大挑战,弃风弃光成为亟待解决的问题。与此同时,近年飞速发展的大容量储能以优异的充/放电调节特性与调节能力为新能源消纳提供了新途径。为此,本文提出了基于储能参与调节的源–储协调优化调度方法,首先分析了储能参与调节的源–储协调调度对新能源消纳的影响机理;进而考虑储能参与调节,以新能源消纳最大为目标建立源–储协调优化调度模型并进行求解,最后进行实例仿真计算,验证了本文所提源–储协调优化调度方法对新能源消纳的有效性。
Abstract: In the background of China’s “dual-carbon” target development strategy, the development of new energy, mainly wind power and photovoltaics, is accelerating. This has brought great challenges to the scheduling and operation of the power grid, and abandoning wind and light has become an urgent problem to be solved. At the same time, the rapid development of large-capacity energy storage in recent years provides a new way for new energy consumption with excellent charge/ discharge adjustment characteristics and adjustment capabilities. To this end, this paper proposes a source-storage coordinated optimal scheduling method based on improving the capacity of new energy consumption. Firstly, the influence mechanism of source-storage coordinated scheduling on new energy consumption is analyzed. Then, the source-storage coordinated optimal scheduling model was established and solved with the goal of maximizing the consumption of new energy. Finally, a case analysis is carried out on the background of large-scale wind power photovoltaic integration into the power grid, which verifies the effectiveness of the source-storage coordinated optimal scheduling method proposed in this paper for the consumption of new energy.
文章引用:吴悦, 韩旭杉, 周强, 申自裕, 刘文颖. 基于储能参与调节的源–储协调优化调度方法[J]. 智能电网, 2021, 11(6): 394-406. https://doi.org/10.12677/SG.2021.116038

参考文献

[1] 李政, 陈思源, 董文娟, 刘培, 杜尔顺, 麻林巍, 何建坤. 碳约束条件下电力行业低碳转型路径研究[J]. 中国电机工程学报, 2021, 41(12): 3987-4001.
https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2021&filename=ZGDC202112001&uniplatform=NZKPT&v=3UDY-INjhgp7gGHI5q7kjxrWxycnodJ9MuOcwE4D8sxhl9eTKG6B2NdtrvAGB-gk
[2] Aneke, M. and Wang, M. (2016) Energy Storage Technologies and Real Life Applications—A State of the Art Review. Applied Energy, 179, 350-377.
[Google Scholar] [CrossRef
[3] Amrouche, S.O., Rekioua, D., Rekioua, T., et al. (2016) Overview of Energy Storage in Renewable Energy Systems. International Journal of Hydrogen Energy, 41, 20914-20927.
[Google Scholar] [CrossRef
[4] 金力, 房鑫炎, 蔡振华, 陈东海, 李亦凡. 考虑特性分布的储能电站接入的电网多时间尺度源储荷协调调度策略[J]. 电网技术, 2020, 44(10): 3641-3650.
[5] 程庭莉. 含分布式储能的主动配电网多目标优化调度方法研究[D]: [博士学位论文]. 重庆: 重庆大学, 2018.
[6] 崔杨, 周慧娟, 仲悟之, 赵钰婷, 崔成伟. .考虑火电调峰主动性与需求响应的含储能电力系统优化调度[J]. 高电压技术, 2021, 47(5): 1674-1684.
https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2021&filename=GDYJ202105017&uniplatform=NZKPT&v=4wc-ki0R37SwiLi59aRleUt9mAAD-PuNE_h5grz_UVfN4dpfWFyErC86EHfWygNA
[7] 赵书强, 王扬, 徐岩, 殷加玞. 基于机会约束目标规划的高风电接入比例下大规模储能与火电协调调度[J]. 中国电机工程学报, 2016, 36(4): 969-977.
[8] 李军徽, 张嘉辉, 穆钢, 葛延峰, 严干贵, 史松杰. 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.
[9] 赵书强, 刘大正, 谢宇琪, 等. 基于相关机会目标规划的风光储联合发电系统储能调度策略[J]. 电力系统自动化, 2015, 39(14): 30-36+53.
[10] 陈玉敏. 基于场景分析的源荷储多时间尺度协调调度研究[D]: [硕士学位论文]. 北京: 华北电力大学, 2020.
[11] 刘波, 王凌, 金以慧. 差分进化算法研究进展[J]. 控制与决策, 2007, 22(7): 721-729.
[12] 林少伯, 韩民晓, 赵国鹏, 等. 基于随机预测误差的分布式光伏配网储能系统容量配置方法[J]. 中国电机工程学报, 2013, 33(4): 25-33+前插4.
[13] 于东, 孙欣, 高丙团, 等. 考虑风电不确定出力的风电并网协调优化模型[J]. 电工技术学报, 2016, 31(9): 34-41.