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东南大学电气工程学院,江苏省南京市 210096
Received:07 September 2023,
Revised:2023-12-15,
Published Online:20 May 2024,
Published:10 July 2024
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张梓麒,陈中.主动配电网多元主体灵活性和随机性的转换机制与刻画方法[J].电力系统自动化,2024,48(13):79-88.
ZHANG Ziqi,CHEN Zhong.Transformation Mechanisms and Characterization Methods for Flexibility and Uncertainty in Active Distribution Networks with Multiple Entities[J].Automation of Electric Power Systems,2024,48(13):79-88.
张梓麒,陈中.主动配电网多元主体灵活性和随机性的转换机制与刻画方法[J].电力系统自动化,2024,48(13):79-88. DOI: 10.7500/AEPS20230907004.
ZHANG Ziqi,CHEN Zhong.Transformation Mechanisms and Characterization Methods for Flexibility and Uncertainty in Active Distribution Networks with Multiple Entities[J].Automation of Electric Power Systems,2024,48(13):79-88. DOI: 10.7500/AEPS20230907004.
能源变革背景下,分布式光伏、储能系统及互动型负荷规模化接入配电网。在调控优化模型中,由于资源特性的差异,配电网及用户侧等多元主体既有潜力作为具有灵活性的控制变量,也可能仍为具有随机性的参数。当负荷互动能力强、储能配置容量大、预测误差小时,这些主体可能表现出灵活性;反之,则可能表现出随机性。文中首先研究了灵活性和随机性的转换机制,基于聚合功率的鲁棒优化结果,推导了多元主体在控制变量和参数之间的一般性转换条件。然后,考虑时序耦合下聚合功率可行范围或波动范围最优,基于两阶段鲁棒优化,刻画了控制变量的可控区间和参数的不确定区间。最后,通过算例验证了转换条件及刻画方法的有效性,为电网多层级协同优化问题的建模和快速求解提供了支撑。
In the context of energy transition
large-scale distributed photovoltaic (PV)
energy storage systems and interactive loads are integrated into the distribution network. In dispatching and optimization models
due to differences in resource characteristics
various entities
such as distribution networks and end-users
possess the potential to act as flexible control variables or may still exhibit randomness. These entities may demonstrate flexibility when their load interaction capabilities are strong
energy storage capacities are high
and prediction errors are low; conversely
they may exhibit uncertainty. Firstly
this paper investigates transformation mechanisms of flexibility and uncertainty and derives general transformation conditions between control variables and parameters of various entities based on robust optimization results with aggregated power. Secondly
considering the optimal controllable or uncertain range of power aggregation under temporal coupling
a two-stage robust optimization approach is employed to delineate the controllable range of control variables and the uncertain interval of parameters. Finally
case studies are conducted to validate the effectiveness of the transformation conditions and characterization methods
which provides support for the modeling and rapid solving of multi-level coordinated optimization problems in the power grid.
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