Multi-Period Active Distribution Network Planning Using Multi-Stage Stochastic Programming and Nested Decomposition by SDDIP

• Published in: IEEE transactions on power systems Vol. 36; no. 3; pp. 2281 - 2292
• Main Authors: Ding, Tao, Qu, Ming, Huang, Can, Wang, Zekai, Du, Pengwei, Shahidehpour, Mohammad
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Decomposition; distributed energy resources; Distributed generation; Distribution network planning; ENGINEERING; Integer programming; Investment; Load modeling; multi-stage stochastic programming; Optimization; Planning; POWER TRANSMISSION AND DISTRIBUTION; Programming; Stochastic processes; Stochastic programming; Substations; Uncertainty
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2020.3032830

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.