Boyuan Cao

This article investigates a mobile edge computing (MEC) network assisted by multiple unmanned aerial vehicles (UAVs) to address the computational and offloading requirements for mobile intelligent terminals (MITs) within crowded venues. The objective is to tackle intricate task processing and diminish MITs' waiting times. Considering the randomness of task arrival at the MITs and the imbalance between the amount of data and computation for complex tasks, a dual‐queue model with data cache queue and computation queue is proposed, with minimizing the weighted system total energy consumption and average delay as the optimization objectives. Lyapunov optimization theory is employed to convert the stochastic optimization problem into a deterministic one, and the initial deployment quantity and hovering position of the UAVs are determined by the density‐based spatial clustering of applications with noise (DBSCAN) method with noise. Then PPO algorithm for MIT task, resource allocation, and UAV trajectory optimization. Numerical results display the proposed scheme can efficaciously diminish energy consumption and delay by 10% and 33% respectively, compared with the baseline scheme. This paper proposes a practical and feasible solution for stochastic computing offloading in UAV‐assisted MEC, which fills the gap in existing research on regarding the consideration of complex task imbalances.

Purpose: This paper aims to focus on the finite element method in the frequency domain (FD-FEM) for the transient electric field in the non-sinusoidal steady state under the non-sinusoidal periodic voltage excitation. Design/methodology/approach: Firstly, the boundary value problem of the transient electric field in the frequency domain is described, and the finite element equation of the FD-FEM is derived by Galerkin’s method. Secondly, the constrained electric field equation on the boundary in the frequency domain (FD-CEFEB) is also derived, which can solve the electric field intensity on the boundary and the dielectric interface with high accuracy. Thirdly, the calculation procedures of the FD-FEM with FD-CEFEB are introduced in detail. Finally, a numerical example of the press-packed insulated gate bipolar transistor under the working condition of the repetitive turn-on and turn-off is given. Findings: The FD-CEFEB improves numerical accuracy of electric field intensity on the boundary and interfacial charge density, which can be achieved by modifying the existing FD-FEMs’ code in appropriate steps. Moreover, the proposed FD-FEM and the FD-CEFEB will only increase calculation costs by a little compared with the traditional FD-FEMs. Originality/value: The FD-CEFEB can directly solve the electric field intensity on the boundary and the dielectric interface with high accuracy. This paper provides a new FD-FEM for the transient electric field in the non-sinusoidal steady state with high accuracy, which is suitable for combined insulation structure with a long time constant.

Large-scale grid-connected power supply based on inverters brings severe challenges to the stability and security control of power system. Due to the simulation resources and calculation efficiency, it's necessary to equivalent the multi-inverter power supply in the new energy field when conducting the system stability and security simulation analysis. In this paper, for the scenario where multiple inverters of the same type are connected to weak grid, the open-loop transfer function and output impedance of the inverter grid-connected current are derived based on frequency analysis, and the stability judgment based on the impedance model in weak grid is obtained. Furthermore, the transfer functions of the inverter single equivalent and multiplication equivalent solutions are derived. The stability differences and key influencing factors are analyzed between the two equivalent solutions and the actual parallel multi-inverter system. Finally, the results of the theoretical analysis are verified by simulation based on an example. Through theoretical and simulation studies, the differences in the principles, effects of different equivalent schemes and the applicable conditions are clarified, and guidance is provided for reasonable selection of inverter equivalent solutions and simulation analysis.

In order to improve the enthusiasm of electric vehicle users to participate in the possession of power grid regulation, and resolve the pricing problem of electric vehicle charging service fee, this paper proposes an automatic adjustment mechanism of electric vehicle charging service fee based on intelligent contract. Firstly, This paper designs the deployment architecture and transaction process of intelligent contract. After that, this paper establishes the user ' s response contribution model and the charging station revenue model. On this basis, the service rate adjustment rules considering the user ' s response contribution and the charging station revenue are designed and applied to the charging contract settlement. The differential pricing mechanism of service rate automatically adjusted according to the response effect of user participation in power grid regulation is realized.