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基于矩差分析的配电网分布式储能优化配置

Optimal Configuration of Distributed Energy Storage in Distribution Networks Based on Moment Difference Analysis

  • 摘要: 随着“双碳”目标的提出,未来配电网中会面临极高比例的光伏等新能源接入,电压越限、潮流返送等问题频繁发生。在充分利用配电网已有调压手段和无功补偿的基础上,由于分布式光伏装机容量太大无法就地消纳,光伏大功率返送导致节点电压越上限。针对此问题,提出了一种基于矩差分析的分布式储能优化配置方法。提出了光伏矩和负荷矩的概念,进而提出了矩差的概念,对矩差和节点电压之间的关系进行了公式推导和理论分析,得出了配电网节点电压与矩差之间的关联关系,并详细阐述了光伏矩和负荷矩的计算方法。在此基础上,提出了一种基于矩差分析的配电网储能优化配置方法,以发生光伏返送时保证配电网所有节点不发生电压越上限为目标。IEEE 33节点配电网系统算例表明,与传统的智能优化算法相比,所提方法直接确定储能安装位置,计算效率高,计算结果准确,工程实用性强。

     

    Abstract: With the introduction of the "double carbon" goal, the future distribution network will face a very high proportion of new energy such as photovoltaic. The increasing penetration of distributed photovoltaics in the distribution network leads to frequent issues such as voltage violations and reverse power flow. This paper proposes an optimization configuration method for distributed energy storage based on moment difference analysis, which is built upon the existing voltage regulation methods and reactive power compensation in distribution networks. The method is proposed to address situations where the on-site accommodation of distributed photovoltaic capacity is not feasible due to its large size, and the high-power return of photovoltaics causes node voltage to exceed limits. The paper introduces the concept of "photovoltaic moment" and "load moment", and subsequently presents the concept of "moment difference". It derives formulas and provides theoretical analysis of the relationship between "moment difference" and node voltage. The paper details the methods for calculating the photovoltaic moment and load moment. Based on this, a new method of energy storage optimization configuration of distribution network based on moment difference analysis is proposed. The goal is to ensure that no node in the distribution network exceeds the upper voltage limit when photovoltaic power is returned. An example of IEEE 33 node distribution system shows that compared with traditional intelligent optimization algorithms, the proposed method can directly determine the installation location of energy storage, which has high computational efficiency, accurate calculation results and strong engineering practicability.

     

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