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Industrial Internet upgrades the traditional industrial manufacturing to digitization, networking and intellectualization era, which calls for brand-new technology supports. As a promising solution, the emergence Digital Twin (DT) offers enhanced digital mapping capability with strong feasibility, security, economic and intelligence, which fits well with the concept of Industrial Internet. In this paper, we focus on establishing a new reference architecture of DT to support the development of Industrial Internet. It is composed of three interdependent layers (i.e., physical layer, DT layer and DT networks layer) and four critical attributes (i.e., privacy, security, awareness and real-time). We illustrate our perspectives for the functionality and relationship of the three layers, and features and feasible solutions of the four attributes. With those efforts, the proposed DT architecture can provide both smart manufacturing and networked services for Industrial Internet era. Moreover, we also illustrate the relevant and open challenges. Finally, the conclusion and future perspective are pointed out.

With the development of port automation and artificial intelligence, coordination with multi-geographic data centers (Geo-DCs) has become a viable solution to address the issue of limited port computing resources. This study proposes a distributed energy dispatch method for the port microgrid coordinated with Geo-DCs (Geo-DCPM), aimed at reducing port carbon emissions and operational costs. Consider the single point of failure problem and high construction costs of centralized data centers. Geo-DCs are first introduced to solve the problem of insufficient computing resources in ports. An energy consumption calculation model for Geo-DCs is established, considering the data load delay constraint and the data space transfer constraint caused by specific delay-sensitive loads in the port microgrid. Then, an energy dispatch model (EDM) is constructed for the Geo-DCPM, taking into account carbon capture costs. Moreover, based on mixed-integer linear programming, a distributed algorithm is proposed to solve the EDM problem. Finally, the simulation results verify the effectiveness of the proposed method. Compared with the centralized algorithm, the packet loss rate of the distributed algorithm combined with Geo-DCs is significantly lower, reduced by about 70%.

Abstract We‐Energy (WE), as an important energy unit with full duplex and multi‐energy carriers in the integrated energy system, uses the coupling matrix to connect the network‐side and demand‐side energy. However, the coupling matrix of WE is very hard to be formulated directly due to the complicated internal structure and the flexibility of operation mode. This paper proposes a multi‐step method for the modelling of WE. According to the method, the conversion process in the WE can be separated into several steps and the WE model can be built by the coupling matrix in each step. Then, the WE model is extended by considering the renewable energy, location of storage and different types of demand response. Because of the non‐linearity caused by the dispatch factors, the computational complexity increases greatly for solving the optimal scheduling issue of the WE. In order to reduce the computational burden, the variable substitution is added in the proposed modelling method. The results of simulation cases are presented to demonstrate the performance of the proposed modelling and calculation method.

This paper aims at developing a data-driven optimal control strategy for virtual synchronous generator (VSG) in the scenario where no expert knowledge or requirement for system model is available. Firstly, the optimal and adaptive control problem for VSG is transformed into a reinforcement learning task. Specifically, the control variables, i.e., virtual inertia and damping factor, are defined as the actions. Meanwhile, the active power output, angular frequency and its derivative are considered as the observations. Moreover, the reward mechanism is designed based on three preset characteristic functions to quantify the control targets: (1) maintaining the deviation of angular frequency within special limits; (2) preserving well-damped oscillations for both the angular frequency and active power output; (3) obtaining slow frequency drop in the transient process. Next, to maximize the cumulative rewards, a decentralized deep policy gradient algorithm, which features model-free and faster convergence, is developed and employed to find the optimal control policy. With this effort, a data-driven adaptive VSG controller can be obtained. By using the proposed controller, the inverter-based distributed generator can adaptively adjust its control variables based on current observations to fulfill the expected targets in model-free fashion. Finally, simulation results validate the feasibility and effectiveness of the proposed approach.

Although the deployment of alternating current (AC) -busbar plug-in electric vehicle (PEV) charging station with photovoltaic (PV) is a promising alternative, the interaction among subsystems always causes the instability problem. Meanwhile, the conventional generalized Nyquist criterion (GNC) is complex, and it is not suitable for the design of the AC system. Therefore, this paper proposes a modified infinity-one-norm (MION) stability criterion based on the impedance method to assess the stability of the foresaid charging station. Firstly, the typical structure and operation modes of the charging station are studied. Furthermore, each subsystem impedance matrix is built by small-signal method, and the MION stability criterion based on impedance method is proposed to assess the charging station stability. Compared with the previous simplified stability criteria based on the norm, the proposed criterion has lower conservatism. Furthermore, the design regulation for the controller parameters is provided, and the stability recovery way is provided by connecting the doubly-fed line and energy storage equipment, which are selected based on intermediate variable, i.e., short-circuit ratio (SCR). Finally, the effectiveness and conservatism of the proposed stability criterion are validated through simulation and experimental results.

In the present study, a bionic flapping mechanism of a spatial six-bar configuration was designed to transform a single rotation of a motor into a three degrees of freedom “flapping–twist–swing” cooperative motion of a flapping wing. The kinematics model of the flapping mechanism movement was constructed. The flapping trajectory of the wing based on the kinematics model was to mimic the motion of a pigeon wing in landing flight. To reduce the manufacturing complexity, the flapping mechanism was simplified with only two degrees of freedom (flapping and twist) retained. Finally, a prototype model with a 0.9 m wing span was built and tested. A comparison among the experimental data, theoretical calculation results, and ADAMS simulation results revealed that the difference in the flapping and the twist amplitude between experimental observations and theoretical calculation results was 12.5% and 2.3%, respectively. This was owing to the elastic deformation of the bar and the mechanism simplification. The comparison results also indicated that the maximum difference in the inertial force was 5.9% in up-stroke and 6.7% in down-stroke, respectively. The experimental results showed that the inertial force of the model with the wing patagium was approximately 2.2 N, and the maximum positive and negative lift was 2.1 N and −1.5 N, respectively. It is hoped that this study can provide guidance for the design of bionic flapping wing mechanisms of a flapping wing aircraft for short landing flight.

This paper investigates the issues of the distributed energy management problem (EMP) of Microgrids in the presence of communication delays. To address this issue, a consensus-based distributed algorithm is proposed to integrate the economic dispatch and demand response, which can optimally assign the energy among generation units and load units with the objective of maximizing the total social welfare of the power system. Different from existing energy management algorithms, a nonuniform time-varying delays model is considered and embedded into the design of our algorithm, such that each unit can achieve collaborative optimization without the requirement of fixed delays information, which has both theoretical merits and practical engineering value for the efficient and stable operation of Microgrids. Moreover, it is proved that the proposed algorithm can converge to the optimal solution under some sufficient conditions. Finally, the correctness and effectiveness of the proposed method are validated by several simulation results.

An investigation into the aerodynamic characteristics has been presented for a bio-inspired flapping wing aircraft. Firstly, a mechanism has been developed to transform the usual rotation powered by a motor to a combined flapping and pitching motion of the flapping wing. Secondly, an experimental model of the flapping wing aircraft has been built and tested to measure the motion and aerodynamic forces produced by the flapping wing. Thirdly, aerodynamic analysis is carried out based on the measured motion of the flapping wing model using an unsteady aerodynamic model (UAM) and validated by a computational fluid dynamics (CFD) method. The difference of the average lift force between the UAM and CFD method is 1.3%, and the difference between the UAM and experimental results is 18%. In addition, a parametric study is carried out by employing the UAM method to analyze the effect of variations of the pitching angle on the aerodynamic lift and drag forces. According to the study, the pitching amplitude for maximum lift is in the range of 60°~70° as the flight velocity decreases from 5 m/s to 1 m/s during landing.