Heuristic algorithms for the Wind Farm Cable Routing problem

Davide Cazzaro, Martina Fischetti and Matteo Fischetti

Applied Energy, 2020, vol. 278, issue C, No S0306261920311223

Abstract: The Wind Farm Cable Routing problem plays a key role in offshore wind farm design. Given the positions of turbines and substation in a wind farm and a set of electrical cables needed to transfer the electrical power produced by the turbines to the substation, the task is to define a cable-connection tree that minimizes the overall cable cost. In the present paper we describe, implement and test five different metaheuristic schemes for this problem: Simulated Annealing, Tabu Search, Variable Neighborhood Search, Ants Algorithm, and Genetic Algorithm. We also describe a construction heuristic, called Sweep, that typically finds an initial high-quality solution in a very short computing time. We compare the performance of our heuristics on two datasets: one contains instances from the literature and is used as a training set to tune our codes, while the second is a very large new set of realistic instances (that we make publicly available) used as a test set. Some practical recommendations on the proposed heuristics are finally provided: according to our experiments, Variable Neighborhood Search obtains the best overall performance, while Tabu Search is our second best heuristic.

Keywords: Wind farm optimization; Cable routing problem; Metaheuristics; Computational analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.apenergy.2020.115617

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