上海交通大学学报 ›› 2021, Vol. 55 ›› Issue (7): 802-813.doi: 10.16183/j.cnki.jsjtu.2020.012

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基于典型运行场景聚类的电力系统灵活性评估方法

游广增1, 汤翔鹰2(), 胡炎2, 邰能灵2, 朱欣春1, 李玲芳1   

  1. 1.云南电网有限责任公司, 昆明 650011
    2.上海交通大学 电子信息与电气工程学院, 上海 200240
  • 收稿日期:2020-01-08 出版日期:2021-07-28 发布日期:2021-07-30
  • 通讯作者: 汤翔鹰 E-mail:xiangytang@sjtu.edu.cn
  • 作者简介:游广增(1982-),男,河南省周口市人,高级工程师,研究方向为电力系统分析与电力规划
  • 基金资助:
    上海市教委科研创新重大项目(2019-01-07-00-02-E00044);南方电网公司重点科技项目(YNKJXM20170008)

Flexibility Evaluation Method for Power System Based on Clustering of Typical Operating Scenarios

YOU Guangzeng1, TANG Xiangying2(), HU Yan2, TAI Nengling2, ZHU Xinchun1, LI Lingfang1   

  1. 1. Yunnan Power Grid Co., Ltd., Kunming 650011, China
    2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2020-01-08 Online:2021-07-28 Published:2021-07-30
  • Contact: TANG Xiangying E-mail:xiangytang@sjtu.edu.cn

摘要:

以风光水为代表的可再生能源电源会增加电力系统的不确定性.为了保证高比例可再生能源电力系统的灵活运行,提出一种典型运行场景电力系统灵活性评估方法.利用改进的K-means算法,将新能源和负荷的运行场景进行聚类组合得到典型运行场景.从区域内供需平衡、区域内潮流分布和区域间输电能力3个角度提出灵活性评估指标;计算每种典型场景的灵活性评估指标,并根据每种场景的出现概率计算得到综合评估指标以评估系统的整体灵活性.最后,基于南方某地区实际新能源和负荷历史数据在改进的IEEE 39节点系统上进行电力系统灵活性评估.结果表明,该聚类方法和灵活性指标可以有效反映电力系统的灵活性.

关键词: 场景聚类, 电力系统, 灵活性, 评估方法, 新能源

Abstract:

The development of renewable energy represented by wind, photovoltaic, and hydropower can increase the uncertainty of power systems. In order to ensure the flexible operation of power systems with a high proportion of renewable energy, a power system flexibility evaluation method based on typical operating scenarios was proposed. Through a modified K-means algorithm, the operating scenarios of renewable energy and load were clustered to obtain typical scenarios. The flexibility evaluation indexes were proposed from three perspectives including regional supply and demand balance, regional power flow distribution, and inter-regional transmission capacity. The flexibility evaluation index of each scenario, and the comprehensive evaluation index based on the appearance probability of each scenario were calculated to evaluate the flexibility of the system. Based on the actual historical output data of new energy and the load of a certain region in the south, the flexibility evaluation was performed on a modified IEEE 39 system. The results show that the proposed clustering method and flexibility index can effectively reflect the flexibility of the system.

Key words: scenario clustering, power system, flexibility, evaluation method, renewable energy

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