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.

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.

Against the conflict between carbon emission and operation cost in integrated energy systems, a multi-objective optimal scheduling method for wind-solar-thermal-storage integrated energy system considering carbon capture is proposed. It explores how carbon capture equipment affects the renewable energy consumption, carbon emissions, and operating costs. Taking the electric load data of a typical day in a specific area as a reference and the improved IEEE 30-bus system as the example, the system economy is optimized. The results show that, compared with the wind-solar-thermal and wind-solar-thermal-storage scenarios without carbon capture, the operating costs of the integrated energy system considering carbon capture reduces by 5.19% and 2.86% respectively on typical days, and the carbon emissions decrease by 1 159 t and 1 013 t, respectively. The consumption rate of wind and solar power generation increases by 5.01% and 2.82%, respectively. Moreover, with the minimum system operation cost and carbon emissions as the optimization objectives, the non-dominated sorting genetic algorithm II is used for multi-objective optimization, and the system scheduling optimization scheme under different target weights is obtained by combining with the linear weighted sum method. The study finds that, increasing the weight of carbon emission target reduces the carbon emissions but raises the system operation costs and the cost per unit of carbon emission reduction. Specifically, when the target weight of carbon emissions rises from 0 to 0.5, the carbon emissions decrease by 5 159 t and the operating costs increase by 205 466 yuan. The carbon emission reduction cost per unit increases the least when the target weight shifts from 0.4 to 0.5. The most significant emission reductions occur when the target weight is within [0.2, 0.4]. The multi-objective optimal scheduling method considering carbon capture proposed above provides a reference for decision makers when weighing system carbon emissions and operating economy.

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.

The use of grid-forming inverters for grid-connection of photovoltaic units is the key to stable operation of the new energy grid in desert and gobi. The conventional PV load-shedding operation is greatly affected by irradiance and inaccurate power retention. To solve these problems, a PV active standby control strategy based on grid-configuration inverter is proposed. Firstly, a PV grid-connected structure containing reference and backup arrays is designed. Secondly, based on the two-stage PV topology, an active backup control is introduced at the front stage DC/DC and a grid-forming control strategy is introduced at the back stage DC/AC to realize active participation of PV units in grid frequency regulation. The control strategy introduces a constant DC capacitor voltage control to maintain the DC voltage while enhancing the inertia characteristics of the PV unit. Finally, the PV small signal model of the grid-forming inverter is established, and the influence of DC capacitor value on the PV frequency response is analyzed through the root trajectory. The simulation results verify the correctness and feasibility of the proposed control strategy.

The impedance inside weak current network is large, and when unbalanced loads are connected, it is unable to maintain the stability of its own voltage, resulting in three-phase voltage imbalance and output power fluctuations. Virtual synchronous generator (VSG) technology, as a grid-forming control, can provide support for voltage of the weak current network. However, under the connection of unbalanced loads, the VSG technology cannot maintain output voltage balance. To solve this problem, an improved VSG sequence decoupling control strategy is proposed. Firstly, the principle of three-phase imbalance and power fluctuation in VSG output voltage caused by unbalanced load connection is investigated. Secondly, a dual synchronous coordinate system decoupling (DDSRF) is adopted to separate the positive and negative sequence voltages of the power grid, and a positive and negative sequence control strategy is employed to control the negative sequence voltage component in dq rotating coordinate system. Finally, a VSG simulation model is built and the simulation results indicate that the proposed improved VSG sequential decoupling control strategy can suppress the unbalanced voltage output of the VSGs.

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.

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.

Virtual Synchronous Generator (VSG), as one of the primary technologies in grid-forming controls, provides inertia support to the power grid. However, due to the limited capacity of individual converters, when larger inertia support is required, multiple VSGs must run in parallel, making the coordinated control of multiple VSGs a subject of significant interest. In this regard, a state-space model for multiple VSGs in parallel is established, and the system stability is analyzed through the eigenvalues of the state variable matrix. Concurrently, a coordinated control strategy for multiple VSGs based on model predictive control is proposed, which introduces the angular frequency deviation and power angle difference as performance indicators to design the objective function. The optimal active power increment required is solved, and the output angular frequency is dynamically adjusted through the power-frequency coefficient, enabling active support for the output frequency and effectively suppressing system frequency fluctuations caused by VSG paralleling, thus the grid stability is enhanced. The results indicate that, compared with the conventional VSG paralleling systems, the proposed MPC-VSG parallel control method can shorten the transient response time of the system and improve its robustness under transient conditions. The simulation result confirms the effectiveness of the proposed approach.

To address the problem of grid connection failure caused by low frequency and voltage stability in power system during pre-synchronization process of grid-forming converters, a pre-synchronization control strategy for grid-forming converters based on improved linear active disturbance rejection control (LADRC) is proposed. Firstly, the phase locked loop (PLL) control strategy is used to synchronize the phase and amplitude of the grid voltage with the feedback control of phase deviation, which can avoid the stability problems caused by low precision of the PLL and the slow response speed. On this basis, introducing LADRC in angular frequency output of the active frequency branch module can effectively suppress the frequency oscillation of the system, so as to ensure the normal pre-synchronization process of the grid-forming converter and realize successful grid-connection. Finally, on the MATLAB/Simulink simulation platform, a pre-synchronization control model for grid-forming converters based on improved LADRC is established verified through simulation. The results show that, the proposed strategy can effectively suppress the system frequency oscillations and accelerate the pre-synchronization process of the system, ensuring safe operation of the grid-forming converter and ultimately achieving successful grid connection. The simulation results verify the effectiveness of the proposed method.

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.

Integrated wind storage system, namely the wind power generation equipped with energy storage, has a black-start capability, which can be controlled to use the system as a black-start power source. On this basis, a black start program for the integrated wind storage system is developed based on a single wind turbine. Firstly, the energy storage device is started through grid-forming control, and to avoid the self-excitation generated by excitation inrush or resonance in the process of transformer input, the inertia link is added based on the original voltage-loop control to realize soft-start strategy. Then, the energy storage system establishes the AC frequency and voltage to realize restoration of the wind turbine generators and the loads. After the wind-storage integrated system is stably started, the electrical energy is transmitted to the 35 kV busbar through the main transformer and transmission line, to complete the black start process. Finally, a simulation model of the integrated wind-storage system is built on the PSCAD/EMTDC platform to validate the black-start scheme using the soft-start strategy, which keeps the voltage stable and the power balanced, and completes the start-up of the system, and at the same time suppresses the excitation inrush current effectively.

With the increasing proportion of new energy in power grid system, the domestic capacity of peak regulation, frequency regulation and voltage regulation is increasing, which greatly affects the flexibility of the power grid. In this regard, the focus is on analyzing and researching the related fields of grid-forming energy storage. Firstly, the technical characteristics of grid-following and grid-forming control are compared and analyzed, and the development status of grid-forming energy storage in Xinjiang is summarized. At the same time, a demonstration project of a grid-forming energy storage power station in Xinjiang is selected to test the low voltage ride-through, inertia response and damping characteristics, and a grid-connected test method for grid-forming energy storage power stations covering multi-level and full-scale scenarios is proposed. The test results can provide reference for grid-connected performance evaluation of grid-forming energy storage. Finally, the development of grid-forming energy storage in Xinjiang is predicted and analyzed, and the development advantages of grid-forming energy storage in new energy-rich areas are summarized.

A combined reactive power control strategy for permanent magnet direct-drive wind turbine and distributed hybrid energy storage system is proposed. Firstly, the reactive power regulation capability of the permanent magnet direct-drive wind turbine and energy storage system is analyzed, and it is determined that both the wind turbine and energy storage system can participate in reactive power regulation through converter control. Secondly, the reactive power control strategy is put forward, which is presented in terms of signal reception, initial allocation, and internal allocation. In initial allocation, the equal margin allocation method is adopted. In internal allocation, the proportional allocation with the priority output of energy storage is considered. Finally, the effectiveness of the strategy is verified by simulation, it shows that the power grid voltage can be supported by fully utilizing the reactive capacity of the wind turbine and energy storage system.

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.

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.