A Branch-and-Price-and-Cut Algorithm for the Cable-Routing Problem in Solar Power Plants

Zhixing Luo (), Hu Qin (), T. C. E. Cheng (), Qinghua Wu () and Andrew Lim ()
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Zhixing Luo: School of Management and Engineering, Nanjing University, Nanjing 210093, China
Hu Qin: School of Management, Huazhong University of Science and Technology, 430074 Wuhan, China
T. C. E. Cheng: PolyU Business School, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Qinghua Wu: School of Management, Huazhong University of Science and Technology, 430074 Wuhan, China
Andrew Lim: Department of Industrial and Systems Engineering, National University of Singapore, Singapore 117576

INFORMS Journal on Computing, 2021, vol. 33, issue 2, 452-476

Abstract: A solar power plant is a large-scale photovoltaic (PV) system designed to supply usable solar power to the electricity grid. Building a solar power plant needs consideration of arrangements of several important components, such as PV arrays, solar inverters, combiner boxes, cables, and other electrical accessories. The design of solar power plants is very complex because of various optimization parameters and design regulations. In this study, we address the cable-routing problem arising in the planning of large-scale solar power plants, which aims to determine the partition of the PV arrays, the location of combiner boxes, and cable routing such that the installation cost of the cables connecting the components is minimized. We formulate the problem as a mathematical programming problem, which can be viewed as a generalized capacitated minimum spanning tree (CMST) problem, and then devise a branch-and-price-and-cut (BPC) algorithm to solve it. The BPC algorithm uses two important valid inequalities, namely the capacity inequalities and the subset-row inequalities, to tighten the lower bounds. We also adopt several acceleration strategies to speed up the algorithm. Using real-world data sets, we show by numerical experiments that our BPC algorithm is superior to the typical manual-based planning approach used by many electric power planning companies. In addition, when solving the CMST problem with unitary demands, our algorithm is highly competitive compared with the best exact algorithm in the literature.

Keywords: photovoltaic power plant; cable routing; branch-and-price-and-cut; dynamic programming; label-setting algorithm (search for similar items in EconPapers)
Date: 2021
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