Due to the uneven distribution of load centers and renewable resources in geographical locations, the reasonable allocation of resources in a wider range requires cross-regional electricity transmission. With the development of inter-regional electricity transmission and the power market, generators participating in the inter-regional market clearing may exercise market power through cooperative game strategies to maximize their own interests, resulting in the reduction of the utilization rate of inter-regional electricity transmission channels and thus influencing the recovery of lines’ permitted income. In response to the above problems, this paper proposed a tri-level model to optimize inter-regional electricity transmission price considering the cooperative game strategy of inter-regional units in the electricity market environment. The upper layer is a transmission electricity price optimization model with the goal of stable recovery of permitted income. The middle layer is a decision-making model of the report volume with the goal of the maximum revenue of the alliance.The lower layer is the regional power market clearing model with the participation of power generators outside the region. An modified C&CG algorithm was implemented to solve the proposed model, decomposing the model into master and sub-problem to be solved in alternating iterations. The master and sub-problems as the two-layer model were solved by converting Carlo-Kuhn-Tucker condition (KKT) and big M method into equivalent monolayer model, while the bilinear terms in the master and sub-problem models were transformed by strong duality theorem and variable discrete parametric method. Finally, PJM-5 node system demonstrates the proposed tri-level optimization model can better reflect the strategic decision and market power behavior of cross-region clearing interest alliance formed by power generators outside the cooperative game strategy, ensuring the formulation of transmission price can realize the stable recovery of the permitted income of the line under the influence of the cooperative game strategy of power producers outside the region.

As a clean, pollution-free secondary energy source with high energy density, hydrogen energy is an ideal energy storage carrier for large-scale consumption of new energy. The electric-heat-hydrogen integrated energy system (EHH-IES), which couples hydrogen energy storage system (HESS) and renewable energy, provides new ideas and solutions for the consumption of new energy. Therefore, this paper focused on how to put in hydrogen energy storage equipment in an economically rational way, and aims to solve the problem of reasonable allocation of hydrogen energy storage equipment capacity and consider the impact of source and load uncertainty on the operation of electrothermal hydrogen integrated energy system. This paper proposed a method for optimizing the capacity of HESS in an EHH-IES considering seasonal storage and source-load uncertainty. Aiming at the relatively large prediction error of wind power and high forecasting accuracy of electric, heat and gas loads at first, the uncertain set and sampling scenario were used to elaborate source and load uncertainty, respectively. Then a bi-level robust stochastic optimization model for configuring hydrogen energy storage considering source-load uncertainty and seasonal storage was constructed, where the upper model optimizes the capacities of devices in hydrogen energy storage with the objective of minimizing total cost of annualized investment costs and operating costs, and the lower model was constructed as a two-stage robust stochastic optimization model to simulate the optimal operation scheme of the EHH-IES under the worst scenario of output wind power in typical days. Since the model is difficult to solve directly, particle swarm optimization and column and constraint generation algorithms were used to solve this type of complex model. Finally, through the analysis of case studies of an EHH-IES, the effectiveness of the proposed method was verified. The obtained solution for the optimal configuration of hydrogen energy storage system can promote the consumption of wind power and improve the economics of the system operation.

With the deepening of the two-carbon target, the penetration rate of renewable energy is increasing year by year, and its consumption problem has attracted much attention. Distributed renewable energy cluster is a new mode of accommodating renewable energy. It is necessary to consider the influence of source-load uncertainty in planning and operation. In this paper, based on the new photovoltaic grid-connected planning of distributed photovoltaic cluster, considering the uncertainty of source and load, a distributed photovoltaic cluster expansion planning method based on two-stage robust optimization was proposed. Considering the difference between the planning stage and the operation stage, it established a two-stage distributed robust optimization model, which takes the minimum annual equivalent cost as the objective and considers the unit output constraint and the power grid carrying capacity. In order to improve the computational efficiency, the historical data of regional distributed renewable energy and random load were reduced and modified by combining K-means clustering with extreme scenario method. Based on the modified scenario set, a probability distribution fuzzy set based on Wasserstein distance was constructed. The column and constraint generation algorithm was used to decompose the two-stage distributed robust optimization model into the main problem and the sub-problem. The main problem and the sub-problem were solved by iteration, which further improves the efficiency of the solution. In order to solve the sub-problem, Lagrange duality was introduced to transform the sub-problem into a deterministic optimization problem. Finally, a distributed photovoltaic cluster was taken as an example to carry out an example analysis. The results show that the proposed two-stage distributional robust optimization method for distributed photovoltaic clusters can coordinate the economy and robustness of the planning operation scheme. Model control parameters can be flexibly adjusted according to the size and reliability of historical scene sets to meet the different requirements of reliability and economy in various engineering application scenarios.

Hydrogen vehicles have developed rapidly in recent years. Compared with hydrogen cars, hydrogen buses have greater safety risks due to their large sizes and large passenger capacity, so it’s of great significance to study the hydrogen leakage-explosion accidents and risks of hydrogen buses in station. The study predicted the dispersion of hydrogen under different leakage conditions after the failure of critical components of hydrogen bus with software FLACS. It studied the overpressure characteristics of the explosion after the explosion induced by the vapor cloud under different ignition locations according to the volume concentration distribution characteristics of hydrogen. And it analyzed the impact range of the accident, quantified the consequences of the explosion accident, and put forward the explosion risk prevention and control suggestions. Based on the risk analysis of hydrogen leakage in the parking lot, it put forward a risk analysis method of hydrogen leakage and explosions.The results show that the environmental wind and the planning layout of the station will affect the hydrogen dispersion after leakage. When the environmental wind direction is perpendicular to the length of the parking lot ceiling, it is most conducive to the dispersion of hydrogen; the dispersed velocity after the hydrogen leakage in the large sides station is fast; the hydrogen volume concentration decreases rapidly; the overpressure generated by ignition induced gas cloud explosion is less powerful; the maximum overpressure in the most severe leakage scenario is approximately 12.38 kPa. The high sensitivity hydrogen sensors can be installed near the TPRD device of hydrogen bus and at the corresponding ceiling position in the middle of the parking space to improve the sensitivity of real-time monitoring of hydrogen leakage.The risk of gas cloud explosion accident after hydrogen leakage in the parking lot is approximately 3.64×10^-7 times per year, which is lower than the risk acceptable level, indicating the bus parking lot meets the safety requirements. The research results provides reasonable suggestions for the layout of hydrogen sensors in hydrogen buses and station, as well as the planning and construction of station.

The existing State of Charge (SOC) estimation methods assume constant parameters for the battery model and do not consider the dynamic changes in these parameters, resulting in imprecise SOC estimates. In view of this limitation, the paper introduced an algorithm that combines online identification of battery model parameters with SOC estimation. Based on the second-order RC equivalent circuit model, it used Multi Innovation Least Squares (MILS) algorithm to identify the parameters in the lithium-ion battery model online, so as to modify the battery model in real time. At the same time, based on the modified battery model, it estimated the battery state of charge through Multi Innovation Extended Kalman Filter (MIEKF) algorithm. MILS algorithm can solve the problem of initial error accumulation in the process of online parameter identification, and can realize online accurate identification of model parameters. MIEK algorithm combines multi-innovation theory and Kalman filter theory, adds forgetting factor to weaken historical data and correct weight, solves the problem of data oversaturation, and has high accuracy and convergence. The experimental results show that, when identifying the parameters of the battery model, the Root Mean Square Error (RMSE) of the MILS algorithm is 1.4 mV, the RMSE of the RLS algorithm is 1.9 mV, and the estimation accuracy is improved by 26.3%. For the SOC estimation after parameter identification, the RMSE estimated by the MIEKF algorithm is 0.003 7, while the RMSE estimated by the EKF and AEKF algorithms are 0.007 3 and 0.005 2, respectively. The MIEKF algorithm improves the estimation accuracy by 49.31% compared to the EKF algorithm and by 28.84% compared to the AEKF algorithm. Moreover, in the case of an incorrect initial SOC value, the proposed algorithm can converge to the true value after about 30 seconds of battery operation. The algorithm proposed in the paper is an effective estimation method with high accuracy and good robustness.

The swash plate piston pump is widely used in the hydraulic system of helicopter fatigue test, because its flow characteristics are critical to the stability of the hydraulic system. This paper used the three-dimensional geometric method to analyze the movement track of the plunger in the swash plate piston pump, and derived the formula of the overflow area based on the graphic analysis method. The corresponding Matlab program was compiled to realize the automatic calculation of the overflow area of oil suction and drainage stage.It constructed a single piston flow model considering flow reversal and leakage, combining AMESim software realized the transformation of the three-dimensional calculation model of the piston pump to a one-dimensional calculation model. Based on the calculation results of the initial operating conditions, this paper analyzed the flow characteristics of the piston pump and the reasons for its flow pulsation. The accuracy of the one-dimensional computational model was verified by the flow pulsation calculation results of the three-dimensional model based on the Computational Fluid Dynamics (CFD) method. On this basis, it analyzed the influence of different operating conditions (including operating temperature, working pressure and piston pump regulating parameters) on the outlet flow pulsation rate. And it analyzed the key points of adjusting and controlling the piston pump in helicopter fatigue test from the angle of reducing the flow pulsation rate and improving the test accuracy. The one-dimensional calculation model proposed in the paper can significantly improve the simulation calculation speed of piston pump, facilitate the improved design of the subsequent piston pump and be added to the virtual digital test platform as a subsystem.

Virtual synchronous generator (VSG) simulates the operation mechanism of synchronous generator and introduces active frequency modulation and reactive voltage regulation control link. Different from the traditional current control converter, it is a voltage control strategy. Based on control configuration and power grid and source coordination characteristics, this paper constructed small signal analysis models, analyzed the oscillation modes under variable control parameters and power system parameters. Then it obtained high frequency resonance characteristics of voltage controlled VSG and proposed suppression control strategy. Firstly, this paper established the small-signal analysis models of voltage control virtual synchronous generator and traditional flow converter control and electrical link, respectively. Through eigenvalue analysis method, the oscillation mode and damping ratio of all the eigenvalues were quantitatively analyzed, and it is found that the voltage control virtual synchronous generator has a high frequency oscillation mode similar to the traditional converter. And it analyzed the control parameter change of the virtual synchronous generator and the high frequency resonance damping mechanism of the power grid scene. Then, based on the control strategy of voltage controlled virtual synchronous generator, with the active damping method, the virtual impedance control strategy based on the current inner ring front channel was proposed to suppress the high-frequency resonance. Finally, the proposed control strategy was verified in the loop experiment results using Matlab/Simulink simulation and RT-LAB controller. The results show that the virtual impedance control link effectively plays a positive damping role. Compared with the passive damping method, in the case of no additional measuring point and external control amount, the voltage control VSG network side damping characteristics are improved, the transient response ability is enhanced, and the high frequency instability phenomenon is effectively suppressed.