To realize the intelligent interconnection and interaction between the intelligent integrated energy system （IES） and the power supply system of rail transit, a synergistic optimization strategy for the hydrogen-containing IES and the power supply system of rail transit is proposed based on the dynamic ladder-type carbon trading mechanism. This strategy can reduce the cost of energy supply and utilization, while enhancing the low-carbon energy supply of the multi-flow coupling system and the low-carbon energy consumption of the rail transit system. Firstly, a dynamic ladder-type carbon trading model is designed based on the level of renewable energy and loads in IES. Secondly, according to the electric and thermal output characteristics of gas turbine （GT） and hydrogen fuel cell （HFC）, the traditional combined heat and power （CHP） unit and hydrogen energy unit are coupled by the Kalina cycle to develop a hydrogen-containing flexible energy supply unit, which can enhance the flexibility of the energy supply. Then, a hydrogen-containing IES collaborative optimization model connecting to the power supply system of rail transit is established to achieve cross-system joint optimization of rail transit energy consumption and multiple heterogeneous energy supply units, fully exploring the low-carbon economic operation potential of the system. Simulation results show that the proposed strategy can effectively balance the low-carbon economy and flexibility of multi-energy system scheduling, which can provide references for the synergistic operation of IES and power supply system of rail transit.

This paper explores the effects of attaching radiative cooling films at different positions of solar cells in different seasons on their thermoelectric performance through experiments and simulations. The results show that attaching a radiative cooling film on the front side can significantly reduce temperature, but due to the decrease in transmittance, the electrical performance is lost by nearly 70%; while attaching a film on the back side can reduce the average temperature by 5.08 ℃ in summer, and the power is approximately increased by 2%, maintaining a high photoelectric conversion efficiency while effectively reducing the module temperature, In terms of the comprehensive performance of thermal management and power generation efficiency, it performs even better. In summer, the film on the back side has a good cooling effect, and in a low-temperature environment with an average ambient temperature of -10 ℃ in winter, the temperature difference of the module decreases by 0.59 ℃. By reducing the temperature difference, the service life can be extended. At the same time, the radiative cooling effect is affected by irradiance, ambient temperature and wind speed. The cooling effect of attaching a film is more prominent under high temperature and high irradiance conditions, while enhancing convection will weaken its cooling effect.

In view of the characteristics of multi-regional correlation of full-network power flow in the new-type power system, an optimization method for coordinated electricity-carbon operation and a new full-network multi-regional cooperative optimization method for dynamically matching coordinated electricity-carbon operation are proposed. Firstly, according to the characteristics of cascade multi-source load-storage units in sub-regions of the new-type power system, the differences in operational regulation efficiency of various load-storage units within the region are analyzed, and a gradient cooperative optimization method for load-storage unit indicators is proposed. Then, aiming at the diversified characteristics of electricity-carbon regulation of load-storage units under different operating modes, a fine-tuning optimization method for load-storage unit control parameters based on complete state space and operational mode feedback is studied, and a 'multi-level multi-core' convolutional neural network model is established. Finally, a simulation model is constructed for validation. Simulation results show that the proposed multi-level indicator cooperative electricity-carbon power flow optimization control strategy can effectively enhance the electricity-carbon coordination capability and electricity-carbon regulation level of the new-type power system.

To meet the inertia requirements of different voltage levels and dynamic operating conditions, this paper proposes an inertial fusion control technology of multi-voltage-level DC microgrid. Initially, a model of a multi-voltage-level DC microgrid is established, and the inertia characteristics of various levels of DC systems are analyzed. Subsequently, aiming to maximize inertia in each system level, the paper considers the involvement of battery storage and renewable energy side converters connected to the system bus. These are engaged in inertia regulation through increased output current feed-forward control and grouped adaptive control. Meanwhile, the low-voltage side use inertia control based on observation compensation with converters connected to their load side to suppress fluctuations. This approach allows converters with inertia regulation capabilities to participate in the graded fusion of inertia in the DC microgrid and designs the inertia parameters for each end. Finally, a multi-voltage-level DC microgrid hardware-in-the-loop simulation platform is constructed to validate the effectiveness of this control strategy.

In view of the problems that traditional crowbar protection is difficult to simultaneously suppress rotor current and DC bus voltage as well as absorb reactive power during low-voltage ride-through. This paper proposes a control strategy of multi-stage crowbar switching and reactive power compensation. During the fault period, the crowbar resistance is adjusted in real time by grading the crowbar, so as to achieve the purpose of suppressing the rotor overcurrent and DC bus overvoltage. At the same time as the multi-stage crowbar is put into operation, the GSC adopts the reactive power compensation strategy, so that the fan can provide certain reactive power support to the power grid. On this basis, the change of rotor flux linkage after the crowbars at all levels are put into operation is analyzed, analytical expressions for the stator and rotor short-circuit currents upon the activation of each crowbar stage are derived, and the resistance value for each stage is subsequently set. Then, the short-circuit current of GSC is analyzed according to the reactive power compensation strategy, and then the influence of multi-stage crowbar protection access and GSC additional reactive power compensation strategy on DFIG reactive power characteristics is further analyzed. Finally, the effectiveness of the proposed control strategy and the correctness of the short-circuit current expression are verified by simulation.

To enhance the consumption capacity of distributed photovoltaic （PV） and improve the power supply reliability of rural areas, this paper proposes a hierarchical coordinated planning method of PV and energy storage system for rural microgrids. Firstly, the medium and long-term load forecasting model based on the DenseNet-Autoformer network is proposed, which uses the autocorrelation mechanism to extract the deep time-series features, and comprehensively considers factors such as meteorology and economy on long-term monthly electricity consumption; Secondly, the Wasserstein generative adversarial network-gradient penalty method is used to expand the PV power samples. On this basis, the typical source and load scenarios are obtained via Gaussian mixture clustering; Finally, taking into account the electricity self-sufficiency and the off-grid reliability, the PV and storage configuration plan of the distribution transformer area is optimized, and the power supply reliability under extreme scenarios is quantified based on chance constraints. Meanwhile, considering the overall energy self-sustained ability of the 10 kV feeder, the feeder-level PV and storage configuration plan is optimized. The simulation results show that the proposed method can enhance the energy self-sustained ability and PV consumption capacity of rural microgrids and improve the power supply reliability in extreme scenarios.

Under the background of global climate change, extreme weather events such as extreme high temperature, cold and freezing temperature, and strong wind and heavy rain occur frequently, which seriously threaten the operational reliability of integrated energy system （IES）. Based on this, we firstly focus on the reliability assessment methods of integrated energy system under extreme weather, and analyze the impacts of three types of extreme weather, namely, extreme high temperature, severe cold and freezing temperature, and strong wind and rainstorm, on the energy production equipment （including power generation, heat supply, and energy storage equipment） and the energy transmission network in various aspects. Secondly, we comprehensively review the integrated energy system reliability assessment methods under these extreme weather conditions, and explore the shortcomings of the existing methods in terms of meteorological data processing, system coupling modeling, multi-method fusion, toughness quantification, and multi-factor considerations. Finally, possible future research directions are proposed for the operational reliability assessment of integrated energy systems under extreme meteorological conditions, aiming to provide certain theoretical and practical references for improving the accuracy and effectiveness of IES reliability assessment under extreme meteorological conditions, so as to guarantee the safety and stability of energy supply.

To address the high energy consumption and significant carbon reduction challenges in steel plate degreasing for industrial equipment manufacturing, this study proposes a novel PV/T-coupled ground-source heat pump heating system for degreasing （PV/T-GSHPHD） and its corresponding operational strategy. A comprehensive energy conversion model was established for system components, and an optimization configuration model was developed to enhance economic efficiency while ensuring soil thermal balance through typical scenario clustering analysis. The optimal system components and their respective capacities were determined based on these models. Results show that the optimal PV/T-GSHPHD system configuration consists of a PV/T module, a ground-source heat pump, a heat collection tank, and a thermal storage tank, with soil heat supplementation achieved via the PV/T module. Compared to a conventional electric boiler heating system, the PV/T-GSHPHD achieves 69.1% reduction in annual heating costs and 83.3% reduction in environmental costs, demonstrating significant economic and environmental advantages. The analysis of operating characteristics of the system on typical days indicates that the PV/T-GSHPHD effectively reduces grid peak loads year-round, with only 13% of its equivalent electricity sourced from the grid during summer, thereby alleviating regional electricity supply pressures. This study highlights the technical and economic viability of PV/T-GSHPHD as a sustainable alternative for industrial degreasing heating applications.

The cascaded H-bridge topology exhibits distinct advantages in the field of photovoltaic （PV） power generation with its modular design, smaller filtering inductance, and simplified layout. However, the three-phase cascaded H-bridge inevitably inherits the inherent issue of the single-phase full-bridge inverter, namely, double-line frequency voltage ripple on the DC-link. This issue leads to an output voltage deviation of photovoltaic array from its maximum power point, thereby reducing the power generation efficiency of system. To address this issue, this paper presents an innovative control method based on adaptive third-harmonic injection, which effectively avoids over-modulation risks under varying power factor angles. The method can calculate the optimal third-harmonic injection based on the real-time operating conditions of the system, thereby achieving optimal suppression of DC-link voltage ripple. Finally, a full-scale experimental platform is constructed, and experimental results confirm the effectiveness and feasibility of the proposed method.

This paper proposes a detection method for protection mismatch risk settings tailored for high-penetration renewable energy integration scenarios. Using a typical topology of high-penetration distributed renewable energy systems, the degradation mechanism of protection performance is analyzed in depth. Furthermore, the constraints on correct protection operation are revealed by investigating the root causes of protection misoperation and failure to trip. Based on this analysis, the mapping relationship between DG output and protection mismatch risk settings is quantitatively examined. The boundary of protection failure is further determined using a dual-loop iteration method based on the backbone particle swarm optimization （PSO） algorithm. Finally, a comprehensive identification procedure for protection mismatch risk settings is developed. The effectiveness of the proposed approach is validated through simulations using the PSCAD/EMTDC and Matlab/Simulink platforms.