  Wind power is a clean and widely deployed alternative to reducing our
dependence on fossil fuel power generation. Under this trend, more turbines
will be installed in wind farms. However, the inspection of the turbines in an
offshore wind farm is a challenging task because of the harsh environment
(e.g., rough sea, strong wind, and so on) that leads to high risk for workers
who need to work at considerable height. Also, inspecting increasing number of
turbines requires long man hours. In this regard, unmanned aerial vehicles
(UAVs) can play an important role for automated inspection of the turbines for
the operator, thus reducing the inspection time, man hours, and correspondingly
the risk for the workers. In this case, the optimal number of UAVs enough to
inspect all turbines in the wind farm is a crucial parameter. In addition,
finding the optimal path for the UAVs' routes for inspection is also important
and is equally challenging. In this paper, we formulate a placement
optimization problem to minimize the number of UAVs in the wind farm and a
routing optimization problem to minimize the inspection time. Wind has an
impact on the flying range and the flying speed of UAVs, which is taken into
account for both problems. The formulated problems are NP-hard. We therefore
design heuristic algorithms to find solutions to both problems, and then
analyze the complexity of the proposed algorithms. The data of the Walney wind
farm are then utilized to evaluate the performance of the proposed algorithms.
Simulation results clearly show that the proposed methods can obtain the
optimal routing path for UAVs during the inspection.
