Grid-forming energy storage system is expected to solve the problems like insufficient frequency modulation resources and disturbance resistance decline of large-scale new energy-based power grid. However, its active support ability is greatly limited due to its inherent power coupling characteristics, plus power overshoot, oscillation and even instability problems are most likely to occur with parameter variation. To solve this problem, a full-order small signal model for grid-forming energy storage system is developed, its frequency response characteristics are analyzed according to the output power state space model and its characteristic roots. On this basis, by analyzing the sensitivity and participation factors of the state space matrix parameters, the stable boundary of the grid-forming energy storage converter is given, and the influence of key parameters of the grid-forming energy storage converter on its dynamic power coupling, frequency support and other grid related characteristics is clarified. The simulation and semi physical experimental results have verified the correctness and feasibility of the theoretical analysis, providing a basis for the design of grid connected parameters and stable operation of grid-forming energy storage converters.

Under the background of “dual-carbon” goal, the combined heat and power units with once through boilers are required to have the ability to quickly change load. To address this need, a strategy based on linear time-varying model predictive control (LTV-MPC) for coordinating electricity and heat to change unit load is proposed, which can simultaneously utilize boiler heat storage and heat network heat storage to improve the rate of variable load. Firstly, the deviation of the heat load signal is integrated to establish an equivalent heat load model, which is used as one of the controlled variables in the prediction model. Then, by taking rapid load tracking, stable unit operation, and timely compensation for heating as the objective of MPC rolling optimization, the optimal control law for each moment is solved online, and then it is applied to the unit. In addition, the operational constraints of the unit are explicitly addressed to ensure that changes in the heating extraction flow rate do not affect the operational stability of the low-pressure cylinder. Finally, simulation verification is conducted on a 350 MW unit, and the results show that this strategy can accurately track the 5%Pe/min variable load command. Furthermore, the heat load recovery time is reduced by 26% compared with that of the electric heating coordinated variable load strategy based on PID. The simulation results have verified the superiority of the proposed strategy in improving the fast load changing capacity of heating units.

The development of efficient energy storage technologies is critical as global energy demand rises and environmental issues become increasingly serious. Large eddy simulation is employed to model the phase change heat storage process in a packed bed system consisting of a double-layer cascade capsule-stacked structure based on the pore scale. The temperature, streamlines, and vortex distributions of phase change materials (PCMs) with various melting points and physical properties are investigated within the structure. The thermal characteristics of the capsule-type stacked structure are analyzed at different entrance velocities, and the simulation results are validated by experimental data. The simulation results demonstrate that, the interstitial flow and vorticity fields of the stacked structure exhibit significant dynamic characteristics during heat storage. At the pore scale, the phase transition induces streamline bending, vortex formation, and the increase of local velocity. After the phase transition, the flow field and vorticity tends to stabilize, with low-vorticity regions occupying most of the area. Eventually, the vortex structure is analyzed by the Q-criterion, revealing that the high-intensity vortices are primarily concentrated near the tank wall.

In the context of achieving “dual-carbon” goals, power units function as adaptable power sources for integrating new energy sources, posing significant challenges to their power generation flexibility. The dry-wet joint cooling system plays a pivotal role in ensuring the safe and stable operation of power units. Therefore, there is an urgent need to optimize the operational strategy of the dry-wet joint cooling system to enhance its flexibility and economic efficiency. Focusing on the dry-wet joint cooling system of a 660 MW generator set, a multi-layer perceptron (MLP) neural network model has been established to predict the outlet temperature of the cooling water. A mixed integer nonlinear programming (MINLP) model is formulated and linearized based on actual operating condition constraints. By solving the MLP-MINLP optimization model, the optimal operation strategy for variable-frequency fans in each operating condition of dry-wet joint cooling system is determined, successfully reducing its power consumption. The results indicate that, after optimizing the configuration of variable-frequency fans, there is a significant reduction in total power by approximately 11.16%, and implementing different frequency operations for variable-frequency fans can reduce total power by about 3.62%~5.38% in a limited manner. The MLP-MINLP optimization model can achieve precise and low-power operation of dry-wet joint cooling system, offering a viable solution for optimizing dry-wet joint cooling systems.

The W-shaped flame boiler with closed middle storage pulverizing system is designed to burn low volatile lean coal and anthracite. Blending coal with high proportion of bituminous coal is able to improve the adaptability of fuel and the flexibility of the boiler. It is necessary to solve the technical problems such as explosion prevention of the pulverizing system, anti-burning of pulverized coal pipes and prevention of serious slagging in the furnace. Therefore, an inert explosion-proof pulverizing technology, in which low temperature flue gas is used for temperature adjustment, is proposed. This method solves the problem of explosion prevention of coal pulverizing system effectively. By increasing the capacity of cooling air from primary fan to reduce the temperature of hot primary air conveying pulverized coal and the adaptability of the burners to blended bituminous, the safety of the primary air pipes and the burners will be guaranteed. With the optimization of refractory belt arrangement and combustion adjustment, this method not only controls the slagging, but also improves the performance of combustion in the furnace effectively. By these integrated technologies presented above, the goal of co-firing 70% bituminous coal safely and economically in the W-shaped flame boiler with closed ball mill medium storage pulverizing system is achieved.

It is of great significance to carry out health condition assessment and fault early warning of auxiliary equipment for safe operation of thermal power units in new power system. By taking the forced draft fan of a supercritical 660 MW thermal power unit as the research object, a method to construct dynamic memory matrix based on multiple characteristic parameters is proposed. The application shows that the proposed method can improve calculating speed of model effectively while ensuring the accuracy of calculated results. This work also presents a calculation method of weighted coefficients to modify the multivariate state estimation technique (MSET). The global similarity and parameter similarity indexes are introduced for fault early warning and recognition. An early fault warning model based on dynamic matrix and weighted MSET is utilized to simulate faults of forced draft fan. The results indicate that the weighted MSET model can not only improve the prediction accuracy of abnormal parameters under fault conditions effectively, but also reduce the influence of abnormal parameters on the predicted results of normal parameters. Consequently, the model proposed can realize both early warning of forced draft fan faults and recognition of abnormal parameters.

The conventional steam valve predominantly manages power regulation tasks while also addresses limited-scale primary frequency regulation. Condensate throttling can change energy distribution of the unit to a certain extent, and serve as a potential and selectable auxiliary frequency regulation method. To delve deeper into the frequency regulation capability of condensate throttling, the working principle and advantages are dissected, and static and dynamic models of the condensate throttling system are established, the frequency regulation characteristics are analyzed and the frequency modulation boundary conditions are outlined. To comprehensively enhance the dynamic performance of the condensate throttling primary frequency regulation, the system dynamic model is linearized, and then a model-switching fuzzy predictive control strategy is proposed. In this control strategy, fuzzy logic is introduced into the predictive controller algorithm to dynamically adjust control weighting coefficients in real-time, and predictive models are dynamically switched according to operational changes to enhance control quality. Case studies based on actual data from a certain 600 MW unit are conducted, indicating the static and dynamic frequency modulation capabilities of condensate throttling increase with the unit load, which has engineering application value in primary frequency regulation. Compared with the conventional PID and self-tuning fuzzy parameter PID controllers, the proposed control strategy exhibits superior adjustment time and performance metrics under various operating conditions, demonstrating better adaptability to changes in operating conditions.

Ammonia cofiring in coal-fired boilers is one of the promising technical routes for decarbonization of existing coal-fired power plants. However, ammonia cofiring may potentially result in drastic increase of NO_x emissions due to its high nitrogen content. Effective control of NO_x emissions is thus one of the key factors that affect the technical feasibility of ammonia cofiring in coal-fired boilers. The formation of NO_x during ammonia-coal cofiring is affected by the ammonia combustion as well as its interaction with the coal combustion process. There are significant differences in volatile content of different coal types which may strongly affect the NO_x formation characteristics of ammonia cofiring. For this reason, the NO_x formation characteristics of ammonia cofiring with bituminous and lean coals that have distinct volatile contents are investigated by an experimental rig that allows for flexible control of the combustion environment of ammonia. The results show that, the NO_x emissions from bituminous and lean coals show different trends with the increase of ammonia cofiring ratio under different ammonia cofiring modes. Because of the significant differences in volatile matter content between bituminous and lean coals and the consequent differences in the amount of O₂ consumption, the distributions of O₂ concentration in the furnace are substantially different between the two coals. This results in different competition relationships between the NO formation and reduction reactions of ammonia in the furnace, which consequently leads to different NO_x formation and emission characteristics between the two coals.

Aiming at the problem of wind turbine off-grid due to lack of high voltage ride through (HVRT) capability of wind power, the internal mechanism of wind turbine off-grid due to voltage increase of junction point caused by DC fault is elaborated. The dynamic reactive power response characteristics of energy storage system and static var generator (SVG) during HVRT are analyzed. Through real-time monitoring of the voltage of the junction point, the priority of the control strategy during HVRT crossing is divided into reactive power regulation inside the wind farm (cooperative control of energy storage system and doubly fed induction generator (DFIG)) and SVG reactive power regulation. On this basis, a collaborative control strategy of energy storage system, DFIG and SVG is proposed to improve the HVRT capability of wind farms. At the same time, the voltage reference value for adverse situations after fault removal is reset to avoid unnecessary reactive power flow. Finally, a simulation model is built based on MATLAB/Simulink platform to verify the correctness and effectiveness of the theoretical analysis and control strategy. The research results provide new ideas for fully exploring the reactive power regulation capability of wind farms and greatly reducing the burden of SVG reactive power compensation.

Carbon capture and storage is an important way to achieve the “dual-carbon” goal. The exhaust gas of the supercritical water-coal to hydrogen coupled CO₂/H₂O mixed working medium thermal power generation system is low pressure and low-temperature CO₂/H₂O mixed gas. In order to achieve zero carbon emission and heat recovery, condensation separation of CO₂/H₂O is a necessary way. Fluent is used to simulate the condensing heat transfer characteristics of CO₂/H₂O mixture outside the horizontal bifurcation tube bundle. The volume of fluid (VOF) model, the component transport model, and the phase transition model written by the user-defined functions (UDF) are employed to load the mass, energy, and component source terms of the two-phase flow. The formation and development process of the liquid film on the wall surface, and the distribution of streamlines, velocity vectors, and liquid-phase volume fractions in the vicinity of droplets, as well as the effects of velocity, vapor superheat, and noncondensable gas content on the heat transfer coefficients and the thermal resistance of the diffusion layer, are investigated. The results show that, the simulation results are in agreement with the experimental data, and the liquid film thermal resistance hardly varies with the steam superheat but decreases with the increase of CO₂ content, inlet flow rate and total pressure. The thermal resistance of the mixed gas diffusion layer increases with the CO₂ content and steam superheat, and decreases with the increase of inlet flow rate. The total heat transfer coefficient increases with the steam superheat, inlet flow rate and pressure, and decreases with the CO₂ content, and the local condensation heat transfer coefficient is negatively correlated with the liquid film thickness. A new dimensionless correlation formula for heat and mass transfer of condensation is proposed for low pressure CO₂/H₂O condensation process.