Multi-Period Active Distribution Network Planning Using Multi-Stage Stochastic Programming and Nested Decomposition by SDDIP
Multi-Period Active Distribution Network Planning Using Multi-Stage Stochastic Programming and Nested Decomposition by SDDIP
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DOI：
10.1109/tpwrs.2020.3032830
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发表时间：
2021-05
影响因子：
6.6
通讯作者：
Tao Ding;Ming Qu;Can Huang;Zekai Wang;P. Du;M. Shahidehpour
中科院分区：
文献类型：
--
作者：
Tao Ding;Ming Qu;Can Huang;Zekai Wang;P. Du;M. Shahidehpour
本文提出了一种带有分布式发电（DG）的多周期主动配电网规划（ADNP）。拟议 ADNP 的目标是在投资和运营限制的情况下最大限度地降低总规划成本。本文提出了一种多阶段随机优化模型来解决多个时期的 DG 不确定性，其中仅使用当前阶段的信息顺序做出决策。提出了一种嵌套分解方法，该方法应用随机对偶动态整数规划（SDDIP）方法来解决所提出的 ADNP 方法的计算困难性。 33节点配电系统和大型906节点系统的数值结果和讨论验证了所提出的ADNP方法及其求解方法的有效性。
This paper presents a multi-period active distribution network planning (ADNP) with distributed generation (DG). The objective of the proposed ADNP is to minimize the total planning cost, subject to both investment and operation constraints. The paper proposes a multi-stage stochastic optimization model to address DG uncertainties over several periods, in which the decisions are made sequentially by only using the present-stage information. A nested decomposition method is proposed which applies the stochastic dual dynamic integer programming (SDDIP) method to address computational intractabilities of the proposed ADNP approach. The presented numerical results and discussions on a 33-bus distribution system and a large-scale 906-bus system verify the effectiveness of the proposed ADNP method and its solution method.