An important application in the growing field of unmanned aerial vehicles (UAVs) is in monitoring and inspection of high voltage power lines and electrical networks. The UAV-based monitoring method will save energy, simplify access to impassable or remote areas, reduce inspection cost, and automate the inspection process. However, the battery capacity of a medium scale drone limits their travel distance and mission duration. It is crucial to improve the energy feeding system of drones and overcome the battery capacity problem to foster the use of drones for routine monitoring operations. In this study, we focus on presenting wireless techniques available for drone mission duration improvement as well as discuss and practically examine the most feasible and reliable technique to charge UAV using power lines.

Wireless power transfer provides an opportunity to charge electric vehicles (EVs) without electrical cables. Two categories of this technique are distinguished: Stationary Wireless Charging (SWC) and Dynamic Wireless Charging (DWC) systems. Implementation of DWC is more desirable than SWC as it can potentially eliminate challenges associated with heavy weight batteries and time-consuming charging processes. However, power transfer efficiency and range, lateral misalignment of coils as well as implementation cost are issues affecting DWC. These issues need to be addressed through developing coil architectures and topologies as well as operating novel semiconductor switches at higher frequencies. This study presents a small-scale dynamic wireless power transfer system for EV. It specifically concentrates on analyzing the dynamic mutual inductance between the coils due to the misalignment as it has significant influence on the EV charging process, particularly, over the output power and overall efficiency. A simulation study is carried out to explore dynamic mutual inductance profile between the transmitter and receiver coils. Mutual inductance simulation results are then verified through practical measurements on fabricated coils. Integrating the practical results into the model, an EV DWC power transfer simulation is conducted and the relation between dynamic mutual inductance and output power are discussed technically.

In the given research, a new multicriterion (multiobjective) optimization algorithm has been considered to solve the problem of electric vehicles (EV) scheduling in a smart network in view of sustainable energy sources based on the cost and pollution minimization. By considering the environmental and economic problems, the application of EVs as a proper charging/discharging scheduling model and green energy sources plays an important role in the power system. This study focuses on multicriteria scheduling through uncertainty factors via inexhaustible assets and EVs, presenting a battery storing framework and reducing both the operation costs and the amount of the framework's pollution while improving the procedures. For this purpose, a new optimization algorithm has been considered to address the mentioned problem taking into account some clean energy sources and emission. The proposed model is examined in smart grid environment based on real-life model by Demand Response Program (DRP) evaluation and the uncertainties in sustainable energies. The proposed optimization algorithm shows more desirable results in comparison with other models, while the efficiency of the suggested approach is studied and evaluated in two power systems, i.e., a 33-bus standard power system and a 94-bus Portugal network. The obtained results validate the proposed method.

Wireless power transfer is a rapidly developing technology utilized to charge electric devices via an air gap. The wide interest towards the development and use of this new charging technique is due to its simplicity, freedom from annoying charging cables, higher efficiency, and smaller charging time. Along with its technical advancements, wireless power transfer technology contributes to the significant reduction of pollutants and CO2 emissions into the atmosphere by the conventional vehicles. However, the implementation of wireless charging for electrical vehicles still present challenges in terms of power transfer efficiency, energy transfer range, utilization of heavy batteries with low energy density and time spent on vehicle charging. One of the ways to address these existing limitations is the development of inmotion (dynamic) wireless power transfer technology. With the incorporation of dynamic wireless charging, there is no need for batteries and the time for charging will sufficiently decrease. This article aims to give a comprehensive explanation of wireless power transfer fundamentals. In particular, different tuning topologies for less inductance leakage are discussed. The output characteristics of each topology are simulated in SIMULINK/Matlab software.

Unmanned Aerial Vehicles (UAVs) or drones have recently gained popularity in various non-military applications. Power systems monitoring, especially high voltage powerlines inspection is one of the sectors where drones can be utilized. However, battery capacity limitations of medium scale drones present a serious problem for realizing their practical use in power systems sector. We propose one of the possible solutions for charging UAVs from the powerlines via a wireless power transfer technique. The experimental results demonstrate the potential benefits of the proposed approach.