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


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.

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.