To achieve efficient coupling between coal-fired power plants (CFPP) and compressed air energy storage (CAES), a system that couples the flue-gas side of CFPP with CAES is proposed. During the energy release phase of this coupled system, the flue gas from CFPP is used to heat the high-pressure air before it enters the expander. This avoids introducing additional heat sources, which would increase costs, or extracting steam from the turbine side to heat the high-pressure air, which would affect the output of the thermal power unit. Subsequently, to reduce the effect of extracted flue gas on the operation of a single thermal power unit, a CAES coupled system sharing the flue gas of two thermal power units is established. Based on the above thermodynamic models of the systems, modeling is carried out using EBSILON software and performance analysis is conducted. Then, an optimal economic operation strategy for the plant-level coupled system is proposed. The results show that, at full load, compared with the steam-coupling scheme, the flue-gas-coupling scheme reduces the standard coal consumption rate by 2.15 g/(kW·h), increases the heat consumption rate by 37.06 kJ/(kW·h), raises the energy utilization coefficient by 0.33 percentage point, and decreases the auxiliary power rate by 0.20 percentage point. The overall electrical efficiency, round-trip efficiency, and CAES operating efficiency of the flue-gas-side coupling are all higher than those of the steam-side coupling. After the economic optimization of the plant-level coupled system, the net revenues of four typical days increase by 143 700, 157 600, 188 100 and 208 700 yuan, respectively.

For a supercritical carbon dioxide (S-CO₂) recompression Brayton (RB) system with two-stage compression and intercooling process, two system models with different layouts are constructed. The effects of key parameters such as low-pressure stage pressure ratio and split ratio on the system performance are explored. The results indicate that, the minimum and optimum splitting ratios exist for the RB cycle, the two-stage compression cycle of the main compressor (TCIP-RB), and the two-stage compression cycle of the recompressor (RTCIP-RB) under the design conditions. Moreover, the thermal efficiency of the TCIP-RB cycle is higher than that of the other two cycles within a certain range of split ratios. When the above three systems adopt the optimal split ratios, the maximum efficiency of the TCIP-RB cycle is 50.95%, which surpasses that of the RB and RTCIP-RB cycle by 3.20% and 3.98%, respectively. At different low-pressure stage pressure ratios, TCIP-RB and RTCIP-RB cycles have an optimal split ratio to maximize the thermal efficiency of the system, and the maximum thermal efficiency decreases with the increase of the low-pressure stage pressure ratio.

It is crucial to improve the dynamic performance of the yaw system of wind turbines in multiple operating scenarios. Therefore, a predictive control strategy for wind turbine yaw system model based on reinforcement learning is proposed, which achieves multi-objective parameter dynamic optimization through the dual-delay depth deterministic policy gradient (TD3) algorithm. Firstly, a multi-step model predictive controller for the yaw system (YMPC) is established to address the conflicting control objectives of power loss rate and yaw actuator utilization rate. Secondly, based on the optimization objectives and wind conditions of the yaw system, a dual-delay depth deterministic strategy gradient (TD3) intelligent agent is designed to determine the input state, action, and reward mechanism of the YMPC. The TD3 intelligent agent is then used to tune the weight coefficients and control step size of the YMPC. Finally, the effectiveness of this method was validated using typical daily data from wind farms in northern China. The results indicate that the proposed strategy significantly improves the overall performance of the yaw system compared with the YMPC with fixed control parameters.

As an emerging large-scale electricity storage technology, the Carnot battery has the advantages of low cost, large capacity, and being free from geographical limitations. Aiming at the current situation that the low discharge cycle efficiency restrains further improvement of round-trip efficiency of the Carnot battery, combined with the heat demand of the thermally integrated Carnot battery and the relatively high discharge efficiency of the Kalina cycle, a heat pumped-Kalina cycle Carnot battery system driven by extraction steam of a coal-fired power station is proposed. A thermodynamic model of the Carnot battery system is established, and the influences of thermal energy storage temperature, temperature difference in thermal energy storage, and ammonia mass fraction on thermodynamic performance of the Carnot battery are mainly studied. The results show that, with different temperature differences of thermal energy storage and at different temperatures, the round-trip efficiency can reach 44.8%~108.0%. With the increase of the ammonia mass fraction, the round-trip efficiency will be significantly improved. However, when the ammonia mass fraction exceeds 90%, the efficiency will drop sharply, and the Kalina cycle is close to a one-component cycle. Therefore, when designing a Carnot battery based on the Kalina cycle, the ammonia mass fraction should be controlled within 80%~90%.

In light of the intricate nature of surface defects in wind turbine blades, conventional convolutional neural networks face problems such as threshold screening and non-maximum suppression processes, which increase computational complexity and are not conducive to model deployment. A novel defect detection model that integrates real-time-detection transformer (RT-DETR) with YOLOv5 algorithm is proposed. Firstly, the backbone network of YOLOv5 is redesigned based on RepVGG and FasterNet to reduce the computational complexity of the model. Recognizing the presence of small-sized targets within the detection tasks, an efficient channel attention (ECA) mechanism is integrated into the neck network’s feature fusion component, thereby augmenting the expressiveness of the output features. Finally, the detection head of original network is reconstructed with the Decoder from RT-DETR, minimizing the effect of non-maximum suppression on the model’s performance. The experimental results show that, the average detection accuracy and accuracy of YOLO-RT are 87.2% and 92.7%, respectively, on a self-constructed dataset of wind turbine blade surface defects, reflecting improvements of 4.4 and 8.0 percentage points over the original YOLOv5 model. The detection rate reaches 118.3 frames per second, surpassing that of alternative detection models. The enhancements introduced in this algorithm significantly improve both detection accuracy and speed, making it highly suitable for practical applications in detecting surface defects on wind turbine blades.

Effective monitoring of chloride ion indicators in precision treated effluent plays a crucial role in ensuring the quality of the effluent, adjusting operational processes, and extending operating cycles. According to the theory of ion exchange equilibrium, the operating characteristics, effluent quality, and resin regeneration requirements of hydrogen type and ammonium type operation modes for precision treatment were analyzed and compared. Through laboratory simulation experiments and tracking experiments of the operating cycle of a precision treated mixed bed in a certain power plant, the migration characteristics of chloride ions in the effluent of precision treatment were mainly studied. The results show that, the requirement for regeneration degree of resin in the hydrogen stage is low, and the main focus of this stage is desalination, which is not prone to chlorine leakage. As the pH value of the effluent increases during the conversion stage, the requirement for resin regeneration also increases. When the condensate contains chloride ions, chloride ion displacement is prone to occur. During ammonium type operation, the mixed bed no longer focuses on desalination, and the mass concentration of chloride ions in the effluent is equivalent to that in the condensate. Therefore, effective monitoring of chloride ions is necessary for ensuring the quality of effluent water, especially during ammonium type operation. At the same time, using chloride ions as one of the monitoring indicators can not only ensure the quality of effluent water effectively, but also guide the adjustment of precision treatment operation process, and significantly extend the precision treatment operation cycle while ensuring the safe operation of the unit.

An analytical model for a combined heat and power (CHP) system driven by deep geothermal energy based on heat pipes was developed. The dynamic heat extraction characteristics of the heat pipes are obtained through numerical calculations based on the heat pipe-geothermal rock layer model. By analyzing the thermodynamic and thermo-economic performance of the direct expansion CHP system, the effects of heat pipe structure (heat pipe diameter, length, and insulation layer length), operating time, and geothermal temperature gradient on the performance of the system are investigated. The results show that, lower steam condensation temperature of the heat pipes leads to greater heat extraction, which helps shorten the investment recovery of the system. However, reducing the condensation temperature also decreases thermal efficiency of the CHP system. Moreover, there exists an optimal steam condensation temperature that minimizes the system’s levelized cost of electricity (LCOE). The heat extraction rate from the heat pipes declines rapidly in the first five years, and then gradually stabilizes. To maintain stable heat extraction over long term (30 years) and avoid interference between adjacent heat pipes, the center distance between any two heat pipes should be kept above 80 meters. The economic performance of the CHP system is closely related to the structural parameters of the heat pipes. At an optimal steam condensation temperature, increasing the heat pipe diameter and length, and selecting target zones with higher geothermal gradients can effectively reduce both the investment payback period and the LCOE.

Co-firing biomass in coal-fired plants is considered as one of the important technologies for achieving carbon emission reduction. Based on the 660MW ultra-supercritical lignite coal fired plant in Inner Mongolia, this study conducted the first domestic experiment on co-firing cow manure. Cow manure is a typical herbaceous biomass. the first domestic large scale coal-cow manure co-combustion experiment in a 660 MW ultra supercritical lignite-fired power unit in Inner Mongolia was carried out. The ability of coal mill to grind biomass and coal mixed fuels was investigated, and the effect of mixing compacted cow manure on the milling performance was analyzed. Moreover, the effects of co-firing compacted cow manure on the combustion characteristics, unburned carbon content in fly ash, boiler efficiency, and pollutant emissions at different loads were studied. The results indicate that, without the addition of new devices, the change in coal mill current before and after co-firing 15% and 20% compacted cow manure with single coal mill changed slightly. With co-firing 15% compacted cow manure and the coal fineness R₂₀₀ increasing from 8.3% to 12.4%, the R₉₀ increased from 35.8% to 40.0%. With co-firing 20% compacted cow manure and the coal fineness R₂₀₀ increasing from 8.3% to 14.4%, the R₉₀ increased from 35.8% to 54.4%. The pressure difference between the coal mill inlet and outlet varied significantly and was closely related to the coal feed rate. With the furnace compacted cow manure co-firing ratio of 2.9% (15% co-firing with coal mill B) and 6.4% (20% co-firing with coal mill B), the changes of exhaust temperature before and after co-firing were both between 1.0~2.5 ℃. With the furnace compacted cow manure co-firing ratio of 7.1% (16.0% co-firing with coal mills B and D) and 8.7% (15% co-firing with coal mills B, C, and D), the exhaust temperature before and after co-firing increased by 3.3 ℃ and 3.6 ℃ at 450 MW and 550 MW, respectively, which was significant. At 250 MW, 450 MW, and 550 MW loads, the change of CO mass concentration was less than 5 mg/m³, and the decrease in boiler thermal efficiency before and after co-firing remained 0.06~0.28 percentage points. Co-firing compacted cow manure can reduce NO_x and SO₂ emissions. When the mixing ratio of compacted cow manure on two and three coal mills was 15% and 20%, the annual CO₂ emission reduction would be 140 312, 210 467, 160 356 and 240 534 tons, respectively.

The dynamic models of steam generation system and power generation system are developed to study the dynamic characteristics of power-to-heat molten salt heat storage and power generation system, and the reliability of the models is validated. The dynamic characteristics of the system are analyzed for the disturbance of molten salt work temperature, flowrate and steam valve opening. Moreover, the performance of the system in the load reduction transient process is investigated in the 100%THA~50%THA load interval. The results show that, the main steam temperature and reheat steam temperature respond quickly to the molten salt temperature disturbance, and their response is obviously faster than that of the unit load and main steam pressure. The molten salt flowrate disturbance has a significant effect on the unit load and main steam pressure, and the unit load increases by 12.44% and the main steam pressure increases by 1.18 MPa with 15% increase in molten salt flowrate. The main steam valve opening controls the main steam pressure and load fluctuation. With the addition of the control system, the maximum load reduction rate of the unit in the 100%THA~50%THA load interval is 14%Pe/min with the limiting condition of temperature deviation.

The formation and emission of SO₃ in coal-fired flue gas pose serious threats to both the safe and economical operation of power plants and the atmospheric environment. To solve this problem, the SO₃ removal performance of sodium-based, calcium-based and magnesium-based absorbents is investigated, and the performance variations of Na₂CO₃, Ca(OH)₂ and CaO under different operating conditions are studied. The results indicate that, under the coexistence of SO₂ and SO₃, the absorbers would react with SO₃ in the flue gas preferentially, and the effectiveness of SO₃ removal by various absorbents ranked from highest to lowest is as follows: Na₂CO₃>NaHCO₃>Mg(OH)₂>MgO>Ca(OH)₂>CaO. Under certain experimental conditions, the SO₃ removal efficiencies of all the absorbents could reach higher than 80% when the chemical equivalent ratio of absorbent to SO₂ reached 2:1. Pre-calcination treatment for the absorbents enhanced their pore structures, facilitating SO₃ diffusion into the absorbent and improving the SO₃ absorption efficiency. Increasing reaction temperature, chemical equivalent ratio, and initial SO₃ mass concentration can promote the SO₃ removal. Additionally, a moderate increase in H₂O volume fraction aided SO₃ removal. When the absorbent is significantly excessive, external diffusion is the main controlling step affecting the chemical reaction rate, while the type of absorbent has a relatively minor impact on it.