考虑灵活性的地区电网新能源消纳能力评估方法
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1.广东电网有限责任公司阳江供电局;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;3.广东电网有限责任公司电力调度控制中心

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广东电网有限责任公司科技项目资助(031700KK52180002)


Assessment method of renewable energy accommodation capacity of regional power grid considering flexibility
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Affiliation:

1.Yangjiang Power Supply Bureau of Guangdong Power Grid Corporation,;2.State Key Laboratory of Power Transmission Equipment &3.System Security and New Technology, Chongqing University;4.Yangjiang Power Supply Bureau of Guangdong Power Grid Corporation;5.Guangdong Power Grid Co., Ltd. Power Dispatching Control Center;6.Guangdong Power Grid Co., Ltd. Power Dispatching Control Center, Guangzhou, Guangdong

Fund Project:

Supported by Science and Technology Projects of Guangdong Power Grid Corporation (031700KK52180002)

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    摘要:

    在我国南方水电富集的地区,水电站可以作为一种灵活性电源用于提高电网的新能源消纳能力。为此,本文提出了一种考虑灵活性的地区电网新能源消纳能力评估方法,该方法能够保证系统安全可靠的同时,全额消纳新能源。首先,考虑源荷功率的相关性,采用K均值聚类技术生成典型场景;然后,通过灵活性电源的优化调度,使得系统在正常运行状态下全额消纳新能源,并在故障状态下使负荷削减量的期望值最小;最后,选取我国南方某沿海地区110 kV电网进行算例分析,研究新能源渗透率和最小负荷削减量期望值的关系,进而评估系统的新能源消纳能力,验证所提方法的有效性。

    Abstract:

    In some areas of South China with rich water resources, hydropower station is a flexible power source which can be used to promote the renewable energy accommodation capacity of power grid. This paper proposes a renewable energy accommodation capacity assessment method of regional power grid considering flexibility. The method can ensure fully accommodating for renewable energy in the premise of safety and reliability. First, representative scenarios are generated using K-means clustering considering the correlation between the power sources and loads. Second, by optimizing the flexible generator dispatching, renewable energy can be fully used under normal operation states, and the expectation of load-shedding is minimized under fault conditions. Finally, a 110 kV regional power grid in a coastal area of South China is used to verify the effectiveness of the proposed method. The relationship between renewable energy penetration and expectation of minimum load-shedding is captured, and the renewable energy accommodation capability of the selected network is evaluated.

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历史
  • 收稿日期:2019-11-15
  • 最后修改日期:2019-11-29
  • 录用日期:2019-11-29
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