Local over-temperature is one of the main reasons for boiler tube failures (BTF). By accurately monitoring and controlling tube wall temperature, local over-temperature can be avoided. Based on the measured flue gas parameters and numerical simulation, a method of thermal deviation calculation is proposed in this study for the on-line calculation of the tube wall temperature of boiler superheaters. The full-size three-dimensional numerical simulation was presented on the combustion in a pulverized coal-fired boiler of 1000 MW ultra-supercritical (USC) unit. A difference in the thermal deviation of the vertical direction was innovatively introduced into a segmented discrete model, and the thermal deviation condition conforming to reality was introduced into the calculation. An on-line calculation system developed based on the current calculation method was applied in a 1000 MW USC unit. The calculated local high-temperature zone was consistent with the actual over-temperature position and conformed to the law of the allowable metal temperature of the final superheater (FSH) serpentines segment. The comparison results showed that the calculated data by this method were more reflective of tube wall temperature change with boiler loads than the measured data. According to the calculated local over-temperature zone, the immediate warning response can effectively reduce the possibility of over-temperature BTF.

It is of great importance to obtain the exact location and severity of slagging deposits on the waterwall surface of an operational boiler to avoid aimless soot-blowing and reduce steam consumption. In this paper, an effective waterwall surface temperature monitoring method is proposed to determine the slagging locations. It has been noted that the temperature difference of the waterwall surface before and after soot-blowing varied with the waterwall location, with more than 80 °C covered with slag and less than 20 °C found clean. According to this, a slagging temperature index was developed to describe the severity of slagging deposits on the waterwall surface. Results indicated that the process of slagging deposit growth included four stages, with the slagging temperature fluctuating in the range of about 90–110 °C in stage III, followed by a rapid drop below 60 °C in stage IV. Furthermore, a digital image monitoring system was used to validate the slag growth process and study the relationship between deposit thickness growth and area expansion. This novel approach provides automated and accurate guidance for each soot blower around the furnace, which reduces soot-blowing steam consumption and avoids serious slagging on the waterwall surface.

The urban energy system is greatly dependent on the District Heating System (DHS). However, many difficulties with regulation and control are caused by its large scale and numerous coupling variables. Additionally, reliance on manual experience means it can be challenging to guarantee heating comfort and effectiveness in the regulation of DHS. This paper proposes a data-driven temperature response prediction model to predict secondary loop supply temperature based on the heating substation’s historical operating status, valve opening degree, weather conditions, etc. Further, the XGBoost model was established in this article with different input and prediction steps. The results show that the XGBoost model with 72 input steps and 24 prediction steps has better performance. As an application example, the model was applied to an urban central heating system. Based on this data-driven model, different operation strategies on primary loop valve opening are compared for temperature response analysis. Operators can check the temperature responses of different valve control strategies before being applied. This paper guides the regulation behavior of the DHS, which is of great significance for the operation of the actual DHS.

The application of thermal energy storage (TES) has been proved effective to improve the energy utilization efficiency of renewable energy and industrial waste heat energy. In this paper, a modified one-dimensional dimensionless model for the thermocline thermal energy storage tank is derived to simulate the system more accurately. An adaptive strategy for solving region compartmentalization is proposed for reducing computing time. Based on the proposed model, the effects of three different parameters on the performance of the thermocline tank are studied. The results show that increasing the inlet velocity can reduce the thickness of the thermocline and improve the system efficiency. Increasing the temperature difference between hot and cold water leads to a thicker thermocline, but the thermal energy stored in the tank increases. Increasing the tank height has no effect on the motion characteristic of thermocline, but the system efficiency can be increased.

Thermal stimulation represents an effective method for enhancing reservoir permeability, thereby improving geothermal energy recovery in Enhanced Geothermal Systems (EGS). The phase-field method (PFM) has been widely adopted for its proven capability in modeling the fracture behavior of brittle solids. Consequently, a coupled thermo-mechanical phase-field model (TM-PFM) was developed in COMSOL 6.2 Multiphysics to probe thermal fracturing mechanisms in reservoir rocks. The TM-PFM was validated against the analytical solutions for the temperature and stress fields under steady-state heat conduction in a thin-walled cylinder, three-point bending tests, and thermal shock tests. Subsequently, two distinct thermal fracturing modes in reservoir rock under high-temperature conditions were investigated: (i) fracture initiation driven by sharp temperature gradients during instantaneous thermal shocks, and (ii) crack propagation resulting from heterogeneous thermal expansion of constituent minerals. The proposed TM-PFM has been validated through systematic comparison between the simulation results and the corresponding experimental data, thereby demonstrating its capability to accurately simulate thermal fracturing. These findings provide mechanistic insights for optimizing geothermal energy extraction in EGS.