To further improve the accuracy and reliability of transient stability assessment (TSA), a feature selection method (Powershap) based on the combination of statistics and Shapley values is proposed, and a power system transient stability assessment model is established. Firstly, the input feature set is constructed based on the steady-state components during the operation of the power system. Powershap is used to divide the dataset into multiple subsets for training, and key feature sets are selected. Then, multiple CatBoost models are trained using key feature sets and transient stability assessments are conduct to generate transient stability assessment models. Finally, simulation experiments are conducted on the New England 10-machine 39-node system and the New England 54-machine 118-node system with the addition of new energy generation, and evaluation results are provided. The experiments show that, in the 10-machine 39-node system in New England, using the Powershap feature selection method for classification can achieve an accuracy of 99.79%. On the improved New England 54-machine 118-node system, its accuracy can reach 99.49%, indicating that the method can effectively perform transient stability assessment of power systems. It is verified that the proposed TSA model has good robustness and generalization ability.

With the deepening of power electronicization in power system, grid-forming converters with voltage source characteristics will become conventional equipment in modern power systems. In order to conduct accurate and efficient control and operation analysis for power systems equipped with grid-forming equipment and to study their safety and stability characteristics, it is necessary to reduce the complexity of grid-forming converter model with strong nonlinear characteristics. Conventional simplification methods based on current loops and voltage control loops neglect the potential effect of inner loop control and line coupling impedance on the synchronous stability of the equipment. Ensuring the accuracy of stability analysis can be challenging in certain scenarios. Therefore, based on the existing order reduction methods, fully considering the small-signal characteristics of inner loop control and the influence of line coupling impedance, a series of improved simplified models are proposed. Moreover, the adaptability of each simplified model to frequency domain, eigenvalues, and time domain analysis is discussed. It turns out that there is no simplified model that can always maintain high accuracy in all scenarios. It is concluded that the simplification method needs to be changed according to the scenario. According to the analysis results, the relevant basis for selecting the simplified model of the converter and adjusting the control parameters is summarized.

As a large scale of physical energy storage technology, compressed air energy storage technology is widely used in consumption of renewable energy and peak shaving of power grids. A compressed air energy storage system coupled with molten salt thermal storage is designed, and the composite system is modeled using Ebsilon software. Based on the operating conditions of the energy storage system supplying hot water, steam, and electricity, the exergy efficiency, thermal efficiency, and economic performance under different operating modes are studied. The results indicate that, the composite system achieves the highest exergy efficiency (64.98%) at a storage pressure of 7 MPa and an exhaust temperature coefficient of 1.96. The highest thermal efficiency (91.55%) is attained at a storage pressure of 12 MPa. In the application scenario of combined heat, steam, and electricity cogeneration, the optimal energy storage duration is 6 hours. Additionally, at gas storage pressures of 7 MPa and 12 MPa, the optimal power generation durations are 6 hours and 8 hours. This research provides theoretical guidance for the study of cogeneration of power and heating using compressed air energy storage system coupled with molten salt thermal storage system.

The stability and cost-effectiveness of power supply has been a pressing issue in areas such as isolated islands where power resources are relatively scarce and natural resources is abundant. Conventional stand-alone microgrids mostly rely on the non-dominated sorting genetic algorithm (NSGA-II) for capacity allocation, which has slightly insufficient local search capability when dealing with multi-objective optimization problems with real loads. In order to overcome this limitation, the improved strength Pareto evolutionary algorithm (SPEA2) is used to optimize the capacity allocation of wind-PV-diesel-battery stand-alone microgrid, which takes the economic cost, loss-of-load probability, and carbon emission as the optimization objectives, to achieve a more comprehensive and efficient capacity allocation. By importing the weather and load data of an isolated island and generating the real Pareto frontier of the independent microgrid with wind, PV, diesel and storage, the analysis results of SPEA2 are compared with that of multi-objective search based on indicator selection (IBEA) and NSGA-II algorithms. Compared with the NSGA-II algorithm, the anti generational distance evaluation IGD index of the SPEA2 increases by 46.83%, the spatial evaluation method Spacing index rises by 60.28%, and the real Pareto coverage CPF index grows by 35.14%, indicating the SPEA2 shows a more excellent performance. Finally, the parameters of each part are reasonably configured according to the results of capacity optimization. It shows that the joint output meets the load demand, which provides a new way of thinking for the energy management of isolated islands and other areas with scarce power resources, and also provides a valuable reference for the optimal design of multi-energy microgrids.

To address the frequency fluctuations and exceeding limits caused by load changes when wind hydrogen coupling system is connected to the weak current grid, a grid type virtual synchronous generator (VSG) moment of inertia self-adaptive control strategy based on dynamic feedback of hydrogen storage system pressure is proposed. Firstly, a physical simulation model of the grid type wind hydrogen coupling system is established, the closed-loop transfer function of active power is derived, and the influence of rotational inertia and damping coefficient on the power frequency oscillation characteristics of the system is analyzed. Then, considering the dynamic changes in pressure of the hydrogen storage system, the moment of inertia calculation is optimized in real time to ensure stable operation of the wind hydrogen coupling system under grid frequency fluctuations and load active power fluctuations. Finally, the strategy is validated using MATLAB/SIMULINK platform. The results show that, using the grid type self-adaptive method can accelerate the frequency recovery of the system, significantly improve the dynamic response ability of the system, and achieve stable operation of the wind hydrogen coupling system.

A double-layer optimization site selection method for energy storage with grid-forming demand in novel power system is proposed, which considers the response of energy storage to peak shaving and frequency regulation in the power system and establishes a multi-objective double-layer optimization model. The operation layer counts the wind and solar power abandonment and network losses into the economic penalty, and takes the optimal annual operating cost of the system as the objective, considers the benefits of peak shaving and frequency modulation. The planning layer evaluates the security of the system and models the system by taking the optimal comprehensive annual operating cost of the system as the objective. Simulation and analysis of the algorithms are carried out using the improved empire competition algorithm. The peaking and frequency regulation economics and energy storage siting in the optimal scenario are illustrated through multi-scenario comparisons. Finally, the IEEE-33 node arithmetic system is simulated and analyzed to verify the validity of the proposed model. Furthermore, uncertainty factor indicators are selected to conduct sensitivity analysis on total costs, and the indicators that need more attention to affect economic costs are determined.

Under the “dual-carbon” background, in order to realize low-carbon emission and maximize wind power consumption of the microgrid system, an optimal scheduling strategy with a two-layer model of integrated energy system (IES) containing carbon capture power plant (CCPP) and power-to-gas (P2G) coupling and vehicle into the grid (V2G) is proposed. Firstly, at the low-carbon technology level, to address the problem that the CCPP and P2G equipment operate out of sync in time, a liquid storage tank is added as a CO₂ buffer station in the middle of the CCPP and the P2G equipment, and a mathematical model containing the CCPP, the P2G equipment and the gas turbine is established. Moreover, a laddered carbon transaction is established to impose low-carbon emission constraints on the IES. Secondly, in order to fully utilize the dual characteristics of EV load and energy storage, strategies are formulated to guide EV charging and discharging during wind abandonment hours and peak hours of the IES to carry out energy time shifting. Finally, at the level of economic efficiency, the integrated operating cost minimization is taken as the objective function, and MATLAB is used to invoke the GUROBI solver to solve the problem. By setting up different scenarios for comparison, the results show that the scheduling strategy can improve the level of microgrid wind power consumption while realizing the low-carbon economic operation of the system.

The large-scale integration of wind power into grid makes it difficult to sustain the peak regulation resources of the existing system, and the wind power consumption is hindered. Therefore, considering the uncertainty of wind power output and electricity price, it proposes a distribution robust optimization method for deep peak regulation of electrolytic aluminum load cooperating with thermal power and energy storage system based on Wasserstein distance. Firstly, combined with the load characteristics of electrolytic aluminum, considering the optimization of deep peak regulation capacity of the energy storage auxiliary thermal power units, an electric power system optimization framework for deep peak shaving of the electrolytic aluminum load and thermal power-energy storage system is established. Secondly, drawing on the idea of the robust model of Wasserstein distance distribution, the Wasserstein fuzzy set constraint of the purchase and sale price of the upper power grid and the output of renewable energy is constructed, and the distribution robust optimization model for deep peak regulation of the electrolytic aluminum load and thermal power-energy storage system is designed. Finally, simulation is performed to verify that the proposed method can effectively improve the peak regulation pressure, reduce the operating cost of the system, and promote the consumption of wind power. The economics and robustness of the method are verified by comparative analysis.

With the high proportion of new energy connected to power grid, multi-machine parallel coordinated control of energy storage inverter has become a key problem. Virtual synchronous generator (VSG) algorithm can provide damping, inertial support and stable voltage frequency for grid-forming energy storage system. However, the parallel synchronization, stability, state of charge (SOC) of each stack and impedance of each line should be considered in the coordinated control of parallel operation of multiple energy storage inverters. To solve this problem, a parallel mathematical model of energy storage inverter is established, the methods of reactive power allocation considering virtual impedance and active power allocation considering SOC are analyzed, and an improved VSG control strategy combining self-adaptive virtual impedance and SOC equalization is proposed. Finally, a model is built on the MATLAB/Simulink simulation platform, and the coordination control of each energy storage inverter is analyzed under the discharge condition with the all vanadium redox flow battery pack as the energy storage system. The validity of the improved VSG control strategy is verified, and the problem of over-discharge caused by voltage drop, reactive power and SOC difference caused by impedance difference is solved effectively, the utilization efficiency of the battery and the energy storage inverter is improved, and the life loss of the battery is reduced.

Under the background of wide application of low nitrogen and oxygen combustion technology and deep peaking technology, the high temperature corrosion failure of water wall tubes is more serious in service process. The high-temperature corrosion behavior characteristics of the boiler water wall tube and high-speed arc spraying PS45 coated tube from a power plant were comparatively investigated. Moreover, the corrosion surface morphology, corrosion products compositions and corrosion cross section characteristics were systematically analyzed by means of SEM, EDS and XRD. The results show that, the high-speed arc spraying PS45 coating can effectively improve the high temperature corrosion resistance of water wall tubes, and the thickness of the surface corrosion layer is small. In the process of high temperature service, the PS45 coating shows better corrosion resistance due to its high content of Cr and Ni, and the thickness of the surface corrosion products layer is thin. However, the microscopic pores between the coating particles will lead to intrusion of high-temperature corrosion reactions, and even cause direct corrosion of the water wall tubes at the coating/substrate interface.