Abstract
As a promising choice of alternative energy, wind power will account for a major part of energy generation in future Energy Internet. With the exploitation of wind power, multiple wind turbines (WTs) are deployed at remote and harsh areas, in which the adverse working environment may lead to enormous WT operating and maintenance costs. Deploying unmanned aerial vehicles (UAVs) for WT detection and sensory data processing in wind farms has been considered as a promising technology to reduce the costs and improve inspection efficiency. In this paper, a mobile edge computing (MEC) driven UAV routine inspection scheme is proposed, in which the UAV not only detects WTs in multiple sorties, but also provides computing and offloading services. To provide seamless communication service, UAV can offload the sensory data to the ground station or satellite optimally. In order to minimize the total completion time, we jointly optimize the UAV trajectory and computation operations, while guaranteeing the data processing accuracy. In the proposed scheme, in order to overcome the influence of wind on UAV trajectory planning, a low complexity WT routine inspection trajectory and UAV scheduling approach is designed firstly. Then, we present an iterative optimization solution to minimize the energy consumption of computation processing, via finding the optimal offloading trajectory and computation offloading parameters. Finally, simulation results show that the proposed scheme can effectively improve the efficiency of UAV routine inspection system performance.
Highlights
Despite the unprecedented economic development achieved by human society, the world faces several challenging energy issues, including energy inefficiency, environmental pollution, and grid information insecurity [1], [2]
PROBLEM SOLUTION we propose a detection trajectory planning and unmanned aerial vehicles (UAVs) scheduling (DTPUS) approach and an iterative offloading trajectory and computation offloading (IOTCO) algorithm to obtain the optimal solutions of the routine inspection trajectory and computation offloading mode respectively
SIMULATION RESULTS we present the simulation results to validate the performance of the proposed DTPUS approach and IOTCO algorithm
Summary
Despite the unprecedented economic development achieved by human society, the world faces several challenging energy issues, including energy inefficiency, environmental pollution, and grid information insecurity [1], [2]. Borrowing attractive characteristics from the Internet, Energy Internet provides efficient interconnection among energy generation, transmission, distribution, transformation, storage, and consumption with novel information and communication technologies (ICT) such as Internet of things [5], software-defined network [6], The associate editor coordinating the review of this manuscript and approving it for publication was Huiqing Wen. and cloud computing [7]. To promote the development of the Energy Internet in an environment-friendly fashion, the penetration of renewable energy has to increase. Considering the intermittent and fluctuating characteristics of renewable energy sources, the high penetration of renewable energy requires the stable operation of power generation equipment, and real-time communication and control between different networks [8], [9]. The exposed blades of WT are vulnerable to pulsating wind loads and environmental factors, leading to frequent malfunctions and even blade damage [11]
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