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Integrated energy systems （IES）， characterized by multi-energy complementarity， can enhance energy utilization and improve economic efficiency through effective scheduling. To achieve optimal scheduling for IES， the energy characteristics of heating and cooling system networks are considered， and an energy transport model for these systems is developed. By leveraging the flexibility of heating and cooling loads and the energy storage properties of the thermal networks’ working medium， a virtual energy storage model for the IES， integrating cooling， heating， and power systems， is developed. The heating and cooling systems are integrated as scheduling resources in the system’s optimal operation， with the objective of minimizing daily operational costs. An optimal scheduling method for IES， considering virtual energy storage， is proposed to achieve energy complementarity among the systems. Simulation results demonstrate that this method effectively balances the mismatch between output and load using the virtual energy storage system， responds proactively to time-of-use tariffs， reduces the peak-valley difference in purchased electricity， and significantly lowers the system’s economic costs.

In traditional microgrid with droop control,the bus frequency decreases with the increase of load,and a corresponding frequency regulation control strategy is taken to keep frequency around the rated value. Control strategies based on proportional integral (PI) are commonly used to recover the bus frequency at present. Because of the possibility of changes in structure and system parameters of microgrid,the quick response and quick restoration of frequency may not be fulfilled with PI control. To solve this problem,the single neuron adaptive PI control method is used as frequency recovery algorithm in microgrid central controller in the second control layer to realize non-error control. In order to accelerate frequency recovery and improve the robustness of microgrid,the proportionality coefficient of the single neuron PI controller is optimized online by fuzzy controller. By comparing this method with original single neuron adaptive PI control with fixed neuron proportionality coefficient in simulation. It is proved that this modified method can improve transient performance of frequency recovery control and accelerate frequency recovery of microgrid.

Regional integrated energy system (RIES) can realize multi-energy conversion and complementation so as to improve energy efficiency, which also brings more security risks. The regional integrated energy system security region (RIESSR) is a security analysis method to describe the safe area for the operating points of RIES based on the N-1 guideline. As a controllable device, energy storage (ES) which is installed in the energy hub (EH) plays an important role in improving system security. Therefore, this paper establishes the model of practical security region of RIES integrating energy storage, and studies the impact of ES on total supply capability (TSC) and practical security boundary. Finally, a specific case is set to simulate and verify the model. By comparing the scenario with ES and the scenario without ES, it can be seen that the solution result of TSC increases and the security region extends across quadrant when the RIES is integrated with ES system. The capacity and location of the ES also impact on TSC and RIESSR.

Efficient and reliable utilization of renewable energy at the user's end is the key to achieving a low‐carbon life. This paper proposed a new distributed energy system around the comprehensive utilization of solar energy by integrating solid oxide fuel cell (SOFC), energy storage equipment, photovoltaic thermal (PVT) collector, and heat pump. By integrating the use of SOFC and PVT, we can further minimize reliance on fossil fuels, while employing the coupling of PVT and heat pump effectively mitigates the inherent challenges of solar energy's variability and intermittency, all while enhancing overall system efficiency. On this basis, we apply the heat current method to construct a cross‐scale heat current model of the components and the system by considering the energy transfer, conversion, and storage characteristics of the system. By employing this model, we simulate the system's operation throughout an entire typical day, assess the COP enhancement of the PVT‐coupled heat pump system, analyze the influence of diverse operating conditions on daily system performance, and evaluate the economy of the energy storage devices in the system. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices. This method integrates features including photovoltaic (PV) systems, energy storage coupling, varied energy roles, and energy supply and demand dynamics. The system model is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously. To strike a balance between optimality and feasibility, renewable energy resources are modeled with considerations for forecasting errors, Gaussian distribution, and penalty factors. Furthermore, this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs. Rooted in surplus theory and finite time projection, the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints. The algorithm greatly reduces the communication burden through event triggering mechanism. Finally, both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm. [ABSTRACT FROM AUTHOR]

The axle box bearing serves as a critical rotational component for high-speed trains. Thus, it is of great significance to obtain accurate loading conditions for axle box bearings for its reliability design. In this study, a bearing-vehicle coupled system dynamic model, consisting of an equivalent bearing model characterized by the time-varying stiffness in the bearing, a nonlinear high-speed train dynamic model, and a slab track model, is developed. The validity of the proposed coupled dynamic model is demonstrated by comparing the simulated results with those obtained in a field test and the literature, respectively. Subsequently, the influence of long- and short-wavelength irregularities on the dynamic responses of bearings is investigated using the proposed coupled model in terms of dynamic loads of the axle box bearing. The results obtained by the proposed model are further compared with those calculated using a traditional vehicle dynamic model that represents the bearing as a revolute joint, so as to illustrate the advantages of the proposed model. The results suggest that the loading responses of the bearing calculated by the two models exhibit differences, which are simultaneously related to the structural damping of the bearing and the mode frequency change of the system. [ABSTRACT FROM AUTHOR]

With the development of the economy, people's demand for green energy has increased significantly. However, the traditional single fossil energy supply system cannot meet the needs of low-carbon. Therefore, this study employs energy hub to establish a multi-energy flow network that enables the integration of carbon flow within the network. Additionally, by utilizing the multi-energy flow trend, a carbon flow tracking method is adopted to achieve real-time carbon flow calculation. Results show that this network calculates the electricity cost of 20043 yuan, gas cost of 67253 yuan, and carbon emission cost of 3152 yuan. Compared with the traditional energy flow system, gas cost is reduced by 4.3% and 1.7%, electricity cost by 21.3% and 15.0%, and carbon emission cost by 8.7% and 6.6%. The two-way sharing carbon flow calculation model calculates that the user side and power supply side of the node each bear half of the network loss, proving two-way sharing effectiveness. Test results on IEEE5 machine 14-node system show that the calculation method can accurately find high-emission and low-emission areas, making the carbon emission allocation between power generation and user more fair and reasonable. This research can effectively reduce emissions cost, accurately calculate emissions flow in real time, and facilitate reasonable emission reduction planning. [ABSTRACT FROM AUTHOR]

Rail corrugation can cause the vibration fatigue failure of the bogie, especially in the metro vehicle. Whereas the existing maintenance limit of rail corrugation is mainly based on operating safety and wheel-rail noise emission and neglects the vibration fatigue failure problems arising from the rail corrugation. It is thus desirable to develop a maintenance limit for rail corrugation from the vibration fatigue failure point of view. Considering that the axle box acceleration spectrum defined in IEC 61373 serves as a basic input for the evaluation of the vibration fatigue life of the bogie, the axle box acceleration thus can be taken as a basic boundary condition for the high-frequency vibration of wheel-rail. This paper thus developed a methodology to determine the maintenance limit based on the axle box acceleration spectrum and the transfer function of the wheel-rail system. In this method, the transfer function was identified by the measured rail corrugation and axle box acceleration. Subsequently, the maintenance limit was derived by the axle box acceleration spectrum defined in IEC 61373 together with the transfer function. The newly developed maintenance limit is considered more reliable to suppress the vibration fatigue failure of the bogie arising from the rail corrugation. [ABSTRACT FROM AUTHOR]