In context of the emerging energy internet, the energy router (ER) is one of the core components of multi-port energy conversion and active energy flow regulation. In this paper, ER is classified into three categories based on its functional characteristics: electrical ER, information ER, and multi-energy ER. Based on the differences between the categories, this paper divides the research on ER into four aspects: power conversion, which focuses on multi-port power conversion; energy routing, which is concerned with the optimization of power flow between ports; information processing and optimal control, which is characterized by an emphasis on intelligence, the coupling of information and energy flow; multi-energy, which has the comprehensive utilization of multiple energies as its main objective. Building on these four research aspects, this paper explores the topologies, control strategies, and optimization methods of ER and related techniques. It compensates for the limitation in coverage due to existing research focusing only on specific application scenarios. This paper also explores the potential of ER to promote the economic and stable operation of power grids. Finally, an outlook is provided on the prospective roles and applications of ER in next-generation energy systems.

The integration of a virtual power plant (VPP) into a weak grid may cause system unreliability and instability. Different allocations of renewable energy sources (RERs) and flexible power-adjustable devices (FPADs) in VPP have different impacts on system strength. Short circuit ratio (SCR) is an important index used to assess the grid strength. First, this paper proposes an integrated short circuit ratio (ISCR) index based on the network structure characteristics of the VPP grid-connected system (VPPGCS). The ISCR considers the interactions among FPADs in addition to the interactions of the RESs in VPP to assess system strength accurately. Then, a bi-level optimal allocation method for RESs and FPADs is proposed based on the proposed ISCR to enhance system strength and increase the output capacity of VPP. In the upper level, the location and capacity of RESs are optimized. It guarantees the maximum value of ISCR at connection points (CP). In the lower level, the location and capacity of FPADs are optimized. It ensures the ISCR value is above the critical short-circuit ratio (CSCR) to maintain the system strength. Location optimization is determined by the ISCR value at CP. Capacity optimization is solved using linear programming. Finally, case studies verify the effectiveness of the proposed optimization method in increasing VPP output capacity while maintaining VPPGCS strength.

Although the proportional current sharing has been widely studied, the heterogeneous characteristic of the different interfaced converters and power coupling terms among distributed generators (DGs) are rarely considered. Therefore, this paper proposes a secondary $H_{\mathrm{\infty }}$ consensus method with a periodic dynamic event-driven scheme for dc microgrids with power coupling to accomplish the precise proportional current-sharing. It is useful for reducing carbon. First, a generalized converter is constructed through equivalent transformation between rectifier and boost converter. Moreover, the heterogeneous characteristic of the interfaced converters regarding different DGs, such as wind and solar generators, is embedded into controller design. Furthermore, the standard linear heterogeneous multi-agent system with power coupling term is built. On this basis, the problem of proportional current sharing is modified into the output consistency problem of multi-agent systems. Furthermore, the $H_{\mathrm{\infty }}$ consensus approach is proposed to accomplish the precise proportional current sharing. Meanwhile, to shorten communication bandwidth, the periodic dynamic event-driven communication strategy is designed. Compared with traditional event-driven communication schemes, a lower communication frequency has been obtained through the proposed communication scheme. In addition, this communication scheme not only avoids Zeno-behavior, but also acquires the smallest sampling time interval. Finally, effectiveness of the proposed approach is verified by two test systems.

Generally, an accurate model can describe the operating states of a system more effectively and provide a more reliable theoretical basis for the system optimization and control. Different from the traditional intrusive modeling, a non-intrusive modeling method based on two-stage generative adversarial network (TS-GAN) is proposed for integrated energy system (IES). By using this method, non-intrusive modeling for the IES including photovoltaic, wind power, energy storage, and energy coupling equipment can be carried out. First, the characteristics of IES are analyzed and extracted based on the meteorological data, energy output, and energy price, and then the characteristic database is established. Meanwhile, the loads are classified as uncontrollable loads and schedulable loads based on frequency domain decomposition to facilitate energy management. Furthermore, TS-GAN algorithm based on the Stackelberg game is designed. In the TS-GAN, the first-stage GAN is used to generate the operating data of each equipment identified by non-invasive monitoring, and the second-stage GAN distinguishes the accumulated data generated by first-stage GAN and further modifies the generator models of the first-stage GAN. Finally, the effectiveness and accuracy of the proposed method are verified by the simulation of an energy region.

Generally, energy trading in smart grid is realized by microgrids. Correspondingly, energy trading in energy internet relies on small-scale energy systems, named as We-energies (WEs). Previous works on the distributed energy trading focused on the trading platform or trading mechanism based on distributed communication. However, most ignored the fact that there is no express delivery of energy trading, and the transmission of energy depends on a fixed physical topology. Energy transactions without considering the transmission distance will increase the difficulty of energy scheduling and the transmission cost of energy. Aiming at this problem, an aggregation game among WEs is proposed for two-way multi-energy trading, and a distributed algorithm is designed to solve the Nash equilibrium. Since each WE only needs to communicate with its neighbors to exchange information, this distributed process reduces communication burden and improves information security. Furthermore, a multi-energy transmission optimization model is established to determine the transmission path of the transmission energy, which can minimize the transmission cost. Subsequently, to reduce the influence of real-time fluctuations of renewable energy and load, a receding horizon control algorithm is designed to improve the reliability of the proposed game. Finally, the effectiveness in dealing with two-way multi-energy trading of the proposed strategy is verified through simulations on the five connected WEs.

Although the dead-time optimization design of resonant converters has been widely researched, classical design methods focus more on achieving zero-voltage switching (ZVS) operation. The body diode loss is always ignored, which results in low-efficiency of the converter, especially, in energy router (ER). To deal with this problem, this paper proposes an adaptive dead-time modulation scheme for bidirectional LLC resonant converters in ER. First, the power loss of the MOSFET is analyzed based on the dead-time. Then, a novel dead-time optimization modulation principle is proposed. It can eliminate the body diode loss of MOSFET compared with existing literature. Based on the optimization modulation principle, this paper proposes an adaptive dead-time modulation scheme. To this end, the converter adopting the scheme no longer needs to calculate dead-time, which simplifies the parameter design process. Meanwhile, this scheme enables dead-time to dynamically change with working conditions according to the dead-time optimization modulation principle. With these effects, the ZVS operation is achieved, and the body diode loss of MOSFET is also eliminated. Furthermore, a digital implementation method is designed to make the proposed modulation scheme have fast-transient response. Finally, experimental results show that the proposed dead-time modulation scheme enables converters to achieve ZVS operation in all working conditions, and has higher efficiency than classical dead-time design methods.

The bi-directional energy conversion components such as gas-fired generators (GfG) and power-to-gas (P2G) have enhanced the interactions between power and gas systems. This paper focuses on the steady-state energy flow analysis of an integrated power-gas system (IPGS) with bi-directional energy conversion components. Considering the shortcomings of adjusting active power balance only by single GfG unit and the capacity limitation of slack bus, a multi-slack bus (MSB) model is proposed for integrated power-gas systems, by combining the advantages of bi-directional energy conversion components in adjusting active power. The components are modeled as participating units through iterative participation factors solved by the power sensitivity method, which embeds the effect of system conditions. On this basis, the impact of the mixed problem of multi-type gas supply sources (such as hydrogen and methane generated by P2G) on integrated system is considered, and the gas characteristics-specific gravity (SG) and gross calorific value (GCV) are modeled as state variables to obtain a more accurate operational results. Finally, a bi-directional energy flow solver with iterative SG, GCV and participation factors is developed to assess the steady-state equilibrium point of IPGS based on Newton-Raphson method. The applicability of proposed methodology is demonstrated by analyzing an integrated IEEE 14-bus power system and a Belgian 20-node gas system.