Search Results (11)

Coal-fired power plants account for a large share of the power generation market in China. The mainstream method of desulfurization employed in the coal-fired power generation sector now is wet flue gas desulfurization. This process is known to have a high cost and be energy-/materially intensive. Due to the complicated desulfurization mechanism, it is challenging to improve the overall sustainability profile involving energy-, cost-, and resource-relevant objectives via traditional mechanistic models. As such, the present study formulated a data-driven many-objective model for the sustainability of the desulfurization process. We preprocessed the actual operation data collected from the desulfurization tower in a domestic ultra-supercritical coal-fired power plant with a 600 MW unit. The extreme random forest algorithm was adopted to approximate the objective functions as prediction models for four objectives, namely, desulfurization efficiency, unit power consumption, limestone supply, and unit operation cost. Three metrics were utilized to evaluate the performance of prediction. Then, we incorporated differential evolution and non-dominated sorting genetic algorithm-III to optimize the multiple parameters and obtain the Pareto front. The results indicated that the correlation coefficient (R2) values of the prediction models were greater than 0.97. Compared with the original operation condition, the operation under optimized parameters could improve the desulfurization efficiency by 0.25% on average and reduce energy, cost, and slurry consumption significantly. This study would help develop operation strategies to improve the sustainability of coal-fired power plants. Full article

To meet the Chinese government’s energy-saving and emission-reduction policies, flexible peak regulation is necessary for traditional coal-fired boilers. Flexible peaking leads to large changes in boiler load, which affects the safety of the boiler water wall. In this paper, a 1000 MW ultra-supercritical unit was tracked for three years, and effective data were selected to study the temperature characteristics of the water wall under flexible peak regulation. The results show that the lower the load, the greater the temperature fluctuation of the water wall. The temperature distribution of the spiral water wall is more uniform. The position of the temperature valley value of the rear spiral water wall was found, and the load of more even temperature distribution was also found. The temperature change of the front vertical water wall was the most complex of all the water walls. The 643.9 MW load case showed different behavior to the temperature distribution of the water wall. The side water walls were heated evenly under the different loads. The characteristics of the temperature distribution of the side vertical water wall were found through statistical analysis. The fitting equation for the change rule of the temperature is presented. The higher the load, the better the equations. Finally, this paper gives some advice on how to avoid temperature deviation in the water wall, and the detailed research highlights the safe running of water walls. Full article

The flexible mode of operation of coal-fired units can accommodate large-scale renewable power integration into the grid, providing more grid capacity. The flexibility transformation of coal-fired units in thermal power plants can be achieved through main steam extraction and reheated steam extraction. A 300 MW subcritical unit, 600 MW subcritical unit and 660 MW ultra-supercritical unit with six flexible operation modes were chosen as the research model to investigate the thermal adaptability for flexible operation. The results show that from the perspective of the source of steam extraction, the main steam extraction scheme is suitable for the flexible adjustment of peak load capacity, and the reheated extraction scheme is suitable for the flexible operation of low load and high thermal efficiency. Moreover, from the perspective of thermal performance adaptability, the 600 MW unit has a wider load regulation capacity than the 300 MW and 660 MW units, and is suitable as the peak shaving unit. This work can provide theoretical guidance for different types of coal-fired units in choosing flexible operation schemes. Full article

To address the issue of traditional static evaluation models being unable to comprehensively analyze the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and entropy weight method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal-powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analyze ultra-supercritical coal-fired units, taking into account time weight. This allows us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the weight of the evaluation index is changed when using the dynamic comprehensive evaluation model of the improved CRITIC and EWM. The index with lower weight is increased by 6.2%, while the index with higher weight is decreased by 0.22%. This alteration in weight range can provide a more objective reflection of the relationship between evaluation indicators. This model offers significant advantages in improving evaluation accuracy, weight balance distribution, and generality. Full article

Aiming at the problem that the energy consumption of the boiler system varies greatly under the flexible peaking requirements of coal-fired units, an energy consumption prediction model for the boiler system is established based on a Least-Squares Support Vector Machine (LSSVM). First, the Mean Impact Value (MIV) algorithm is used to simplify the input characteristics of the model and determine the key operating parameters that affect energy consumption. Secondly, the Snow Ablation Optimizer (SAO) with tent map, adaptive t-distribution, and the opposites learning mechanism is introduced to determine the parameters in the prediction model. On this basis, based on the operation data of an ultra-supercritical coal-fired unit in Xinjiang, China, the boiler energy consumption dataset under variable load is established based on the theory of fuel specific consumption. The proposed prediction model is used to predict and analyze the boiler energy consumption, and a comparison is made with other common prediction methods. The results show that compared with the LSSVM, BP, and ELM prediction models, the average Relative Root Mean Squared Errors (aRRMSE) of the LSSVM model using ISAO are reduced by 2.13%, 18.12%, and 40.3%, respectively. The prediction model established in this paper has good accuracy. It can predict the energy consumption distribution of the boiler system of the ultra-supercritical coal-fired unit under variable load more accurately. Full article

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. Full article

In order to meet the flexibility operation needs of coal-fired units under the goal of carbon peak and carbon neutralization, it is imperative for circulating fluidized bed (CFB) units to participate in deep peak regulation. By systematically summarizing deep peak regulation operation practice of existing SC and subcritical-parameter-levels CFB units, the feasibility of deep peak regulation technology of an ultra-supercritical (USC) CFB unit under development and being built is analyzed and demonstrated; meanwhile, the deep peak regulation capacity of the boiler is also predicted. The results show that by analyzing the structural characteristics and design performance of the USC-CFB boiler, for technical problems such as stable combustion under low load, hydrodynamic safety, denitration performance under wide load, and rapid boiler load change rate existing in deep peak regulation, technical measures were implemented by selecting advanced boiler furnace type, adopting good design technology of the secondary rising water wall and uniformity design of bed temperature and bed pressure, strengthening the reducing atmosphere inside the furnace, improving the performance of wear-resistant refractory materials, quickly controlling the furnace bed material stock under variable load, optimizing the control strategy of CFB unit, and so on. The boiler achieved good operation characteristics and good deep peak regulation performance, and the pollutant emissions can steadily achieve ultra-low emission standards. When the USC-CFB unit participates in deep peak regulation, the minimum stable combustion load of the boiler can reach 20~30% BMCR, and a boiler load change rate under 30% BMCR or above could reach 1.5~2% BMCR/min, while that below 30% BMCR could reach 1% BMCR/min. The research results can provide references for the deep peak regulation of in-service supercritical (SC) CFB units and design optimization of similar USC-CFB units. Full article

Performance guarantees and tests of thermal power plants are usually carried out at 100% rate output capacity. However, fossil-fired power plants have decreased full load hours, affecting energy efficiency, and are subjected to frequent load changes caused by variable renewable electricity and potential grid stability. Therefore, this study is conducted to calculate and draw the characteristic curves for all stable loads of coal-fired power units including the 60%, 75%, and 100% rate output. The study focuses on the corrected plant net heat rates—gross unit outputs, net standard coal consumption rates—throttle steam pressures, and corrected plant net efficiencies—carbonic emission rates. In addition, the experimental investigation for energy efficiency and carbonic emission of the latest larger-scale (+600 MW) coal-fired power generation units in Vietnam are also implemented using a performance guarantee calculation software called “PG_Cal” version 0.0, which is based on a mass and energy balance method by MATLAB programing language. From the results of this study, it is suggested that the performance guarantees and tests of new coal-fired units should be carried out at different stable loads, including minimum load. Vietnam should apply the ultra-supercritical technology for new units in order to increase their efficiency and decrease carbon dioxide emissions. Full article

This article presents the performance analysis of a 700 MW future planned advanced ultra-supercritical (A-USC) coal-fired power plant fitted with post-combustion carbon capture and storage (CCS) technology. The reference A-USC unit without CCS achieves a net efficiency of 47.6% with CO₂ emissions of 700 kgCO₂/MWh. Relatively to subcritical units, the net efficiency of the A-USC is 8%-pts higher while CO₂ emissions are 16.5% lower. For a CO₂ removal rate of 90%, the net efficiency of the CCS integrated A-USC unit is 36.8%. The resulting net efficiency loss is 10.8%-pts and the electricity output penalty is 362.3 kWh_el/t_CO2 for present state CCS technology. The study continues with the assessment of interface quantities between the capture unit and the steam cycle affecting the performance of the A-USC. Improved CO₂ absorbents could alleviate the net efficiency loss by 2–3%-pts, and enhanced CO₂ compression strategies and advanced heat integration could further reduce the efficiency loss by 0.5–1.2%-pts and 0.4–0.6%-pts, respectively. The total efficiency gain from CCS technology upgrades is estimated at 3.6%-pts, thus bringing down the net efficiency loss to 7.2%-pts and the electricity output penalty to 241.7 kWh_el/t_CO2. Full article

The ultra-supercritical (USC) coal-fired boiler-turbine unit has been widely used in modern power plants due to its high efficiency and low emissions. Since it is a typical multivariable system with large inertia, severe nonlinearity, and strong coupling, building an accurate model of the system using traditional identification methods are almost impossible. In this paper, a deep neural network framework using stacked auto-encoders (SAEs) is presented as an effective way to model the USC unit. In the training process of SAE, maximum correntropy is chosen as the loss function, since it can effectively alleviate the influence of the outliers existing in USC unit data. The SAE model is trained and validated using the real-time measurement data generated in the USC unit, and then compared with the traditional multilayer perceptron network. The results show that SAE has superiority both in forecasting the dynamic behavior as well as eliminating the influence of outliers. Therefore, it can be applicable for the simulation analysis of a 1000 MW USC unit. Full article

In this paper, an improved system to efficiently utilize the low-temperature waste heat from the flue gas of coal-fired power plants is proposed based on heat cascade theory. The essence of the proposed system is that the waste heat of exhausted flue gas is not only used to preheat air for assisting coal combustion as usual but also to heat up feedwater and for low-pressure steam extraction. Air preheating is performed by both the exhaust flue gas in the boiler island and the low-pressure steam extraction in the turbine island; thereby part of the flue gas heat originally exchanged in the air preheater can be saved and introduced to heat the feedwater and the high-temperature condensed water. Consequently, part of the high-pressure steam is saved for further expansion in the steam turbine, which results in additional net power output. Based on the design data of a typical 1000 MW ultra-supercritical coal-fired power plant in China, an in-depth analysis of the energy-saving characteristics of the improved waste heat utilization system (WHUS) and the conventional WHUS is conducted. When the improved WHUS is adopted in a typical 1000 MW unit, net power output increases by 19.51 MW, exergy efficiency improves to 45.46%, and net annual revenue reaches USD 4.741 million while for the conventional WHUS, these performance parameters are 5.83 MW, 44.80% and USD 1.244 million, respectively. The research described in this paper provides a feasible energy-saving option for coal-fired power plants. Full article