Open AccessFeeder‐corridor‐based distribution network planning model with explicit reliability constraints
Author(s) -
Li Zihao,
Wu Wenchuan,
Zhang Boming,
Tai Xue
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.1093
Subject(s) - integer programming , network planning and design , reliability (semiconductor) , linear programming , mathematical optimization , flexibility (engineering) , computer science , set (abstract data type) , graph , graph theory , operations research , engineering , power (physics) , mathematics , computer network , statistics , physics , theoretical computer science , quantum mechanics , combinatorics , programming language
Most distribution network planning models rely on predefined candidate electric line routes (branches), i.e. the planning model is to select a subset of the candidate branches to form a network with minimal investment cost and guarantee the power supply to consumers with specified reliability. However, the manually presented candidate branch set may be thoughtless while the exhaustively generated a large set of candidate branches may make the planning model intractable. In this study, the authors propose a distribution network planning model based on feeder corridors instead of the candidate branches, since feeder corridors are commonly given in municipal planning. Based on the graph model formulated by feeder corridors, the proposed planning model can generate the network with minimal investment cost while meeting the specific reliability requirement. Furthermore, since post‐fault load restoration strategies between feeders are fully incorporated, the proposed model is applicable for mesh networks. The planning model is formulated as a mixed‐integer linear programming (MILP) problem and can be effectively solved by off‐the‐shelf software. Simulation results show the effectiveness and flexibility of the proposed method.