An optimization drone routing model for inspecting wind farms

The use of wind turbines to generate electricity is growing worldwide. They comprise an extended area of hundreds of square miles, making the inspection process difficult and time-consuming. Recently, there has been an increasing interest in using a drone, or also known as unmanned aircraft systems, for inspecting wind turbines. Motivated by leveraging drone technology, this paper provides a routing optimization model to reduce the total operation time for inspecting a wind farm. We assume that one drone and one ground vehicle which carries the drone and extra batteries and charging equipment are available. The optimization model is solved in two steps. The first step clusters the wind turbines and optimizes the drone routing in each cluster by solving the classical traveling salesman problem using an integer linear programming model. The second step optimizes the ground vehicle routing by solving the equality generalized traveling salesman problem using an integer linear programming model. We test our proposed model using three case studies created by using actual wind farm locations. We compare the results with two models. One model assumes no clustering of the wind turbines, and the other model uses a greedy approach for determining the ground vehicle route. The results show that the proposed model is more efficient at different flight speeds and endurances. Also, we confirm that the efficiency increases as the drone flies faster or it has longer flight endurance.