Search Results (316)

This study conducts an in-depth analysis of the dynamic characteristics of a single reheat steam turbine generator unit and its speed control system under variable operating conditions. A comprehensive simulation model was constructed to comprehensively evaluate the impact of the heat extraction system on the dynamic behavior of the unit, which integrates the speed control system, actuator, single reheat steam turbine body, and once-through boiler dynamic coupling. This model focuses on revealing the mechanism of the heat extraction regulation process on the core operating parameters of the unit and the system frequency regulation capability. Based on the actual parameters of a 300 MW heat unit in a power plant in Guangxi, the dynamic response of the established model under typical dynamic conditions such as extraction flow regulation, primary frequency regulation response, and load step disturbance was simulated and experimentally verified. The results show that the model can accurately characterize the dynamic characteristics of the heat unit under variable operating conditions, and the simulation results are in good agreement with the actual engineering, with errors within an acceptable range, effectively verifying the dynamic performance of the heat system module and the rationality of its control parameter design. This study provides a reliable theoretical basis and model support for the accurate simulation of the dynamic behavior of heat units in the power system and the design of optimization control strategies for system frequency regulation. Full article

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 ${\displaystyle \frac{MHz}{°\mathrm{C}}}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples. Full article

Co-firing large-sized straw biomass in pulverized coal boilers is a potential pathway for carbon emission reduction in China’s thermal power plants. However, experimental data on large-sized straw combustion under pulverized coal boiler combustion conditions are critically lacking. This study selected typical large-sized wheat straw particles. Employing a two-mode experimental setup in a drop tube furnace (DTF) system simulating pulverized coal boiler conditions, we systematically investigated the combustion behavior and alkali metal release characteristics of this large-sized straw biomass, with combustion processes summarized for diverse particle types. The findings reveal asynchronous combustion progression across particle surfaces due to heterogeneous mass transfer and gas diffusion; unique behaviors distinct from denser woody biomass, including bending deformation, fiber branching, and fragmentation, occur; significant and morphology-specific deformations occur during devolatilization; fragmentation universally produces particles of varied shapes (needle-like, flaky, blocky, semi-tubular) during char combustion; and potassium release exceeds 35% after complete devolatilization and surpasses 50% at a burnout degree exceeding 80%. This work provides essential experimental data on the fundamental combustion characteristics and alkali metal release of large-sized wheat straw particles under pulverized coal boiler combustion conditions, offering engineering application guidance for the direct co-firing of large-sized flexible straw biomass in pulverized coal boilers. Full article

To compensate for the instability of renewable energy sources during China’s energy transition, large thermal power plants must provide critical operational flexibility, primarily through deep peaking. To investigate the combustion performance and wear and tear of a 600 MW pulverized coal boiler under deep peaking, the gas–solid flow characteristics and distributions of flue gas temperature, wall heat flux, and wall wear rate in a 600 MW tangentially fired pulverized coal boiler under variable loads (353 MW, 431 MW, 519 MW, and 600 MW) are investigated in this study employing computational fluid dynamics numerical simulation method. Results demonstrate that increasing the boiler load significantly amplifies gas velocity, wall heat flux, and wall wear rate. The maximum gas velocity in the furnace rises from 20.9 m·s⁻¹ (353 MW) to 37.6 m·s⁻¹ (600 MW), with tangential airflow forming a low-velocity central zone and high-velocity peripheral regions. Meanwhile, the tangential circle diameter expands by ~15% as the load increases. The flue gas temperature distribution exhibits a “low-high-low” profile along the furnace height. As the load increases from 353 MW to 600 MW, the primary combustion zone’s peak temperature rises from 1750 K to 1980 K, accompanied by a ~30% expansion in the coverage area of the high-temperature zone. Wall heat flux correlates strongly with temperature distribution, peaking at 2.29 × 10⁵ W·m⁻² (353 MW) and 2.75 × 10⁵ W·m⁻² (600 MW) in the primary combustion zone. Wear analysis highlights severe erosion in the economizer due to elevated flue gas velocities, with wall wear rates escalating from 3.29 × 10⁻⁷ kg·m⁻²·s⁻¹ (353 MW) to 1.23 × 10⁻⁵ kg·m⁻²·s⁻¹ (600 MW), representing a 40-fold increase under full-load conditions. Mitigation strategies, including ash removal optimization, anti-wear covers, and thermal spray coatings, are proposed to enhance operational safety. This work provides critical insights into flow field optimization and wear management for large-scale coal-fired boilers under flexible load operation. Full article

The internal combustion process in a boiler in power plants has a direct impact on boiler efficiency and NOx generation. The objective of this study is to propose an intelligent deep learning modeling and multi-objective optimization approach that considers NOx emission concentration and boiler thermal efficiency simultaneously for boiler combustion in power plants. Firstly, a hybrid deep learning model, namely, convolutional neural network–bidirectional gated recurrent unit (CNN-BiGRU), is employed to predict the concentration of NOx emissions and the boiler thermal efficiency. Then, based on the hybrid deep prediction model, variables such as primary and secondary airflow rates are considered as controllable variables. A single-objective optimization model based on an improved flow direction algorithm (IFDA) and a multi-objective optimization model based on NSGA-II are developed. For multi-objective optimization using NSGA-II, the average NOx emission concentration is reduced by 5.01%, and the average thermal efficiency is increased by 0.32%. The objective functions are to minimize the boiler thermal efficiency and the concentration of NOx emissions. Comparative analysis of the experiments shows that the NSGA-II algorithm can provide a Pareto optimal front based on the requirements, resulting in better results than single-objective optimization. The effectiveness of the NSGA-II algorithm is demonstrated, and the obtained results provide reference values for the low-carbon and environmentally friendly operation of coal-fired boilers in power plants. Full article

This article presents an analysis on natural gas heating in residential areas, focusing on two primary systems: (1) local heating, where piped gas is delivered directly to individual dwellings equipped with autonomous gas boilers, and (2) district heating, where gas or an alternative fuel powers a central heating plant, and the generated heat is distributed to buildings via a thermal network. The choice between these systems should first consider safety and environmental factors, followed by the urban characteristics of the settlement. In particular, building typology—such as size, function, and spatial configuration—and urban topology, referring to the relative positioning of buildings, play a crucial role. For example, very tall buildings often exclude the use of piped gas due to safety concerns, whereas in other cases, economic efficiency becomes the determining factor. To support decision-making, a comparative cost analysis is conducted, assessing the required infrastructure for both systems, including pipelines, boilers, and associated components. The study identifies representative residential building types in selected urban areas of Serbia and Czechia that are suitable for either heating approach. Additionally, the article examines the broader energy context in both countries, with emphasis on recent developments in the natural gas sector and their implications for urban heating strategies. Full article

Denitrification technology in thermal power plants plays a critical role in reducing nitrogen oxide (NOx) emissions, thereby improving air quality and mitigating climate change. This study conducts a numerical simulation of the SCR (Selective Catalytic Reduction) system at the Chizhou Power Plant to optimize its flow field configuration. The original system exhibited severe flow non-uniformity, with local maximum velocities reaching 40 m/s and a velocity deviation coefficient of 28% at the inlet of the first catalyst layer. After optimizing the deflector design, the maximum local velocity was reduced to 21 m/s, and the velocity deviation coefficient decreased to 14.1%. These improvements significantly enhanced flow uniformity, improved catalyst efficiency, and are expected to extend equipment service life. The findings provide a practical reference for the retrofit and performance enhancement of SCR systems in similar coal-fired power plants. Full article

In high-temperature, high-pressure, and corrosive industrial environments, frictional wear of metallic components stands as a critical determinant governing the long-term operational reliability of mechanical systems. To address the challenge of traditional lubricating coating failure under a broad temperature range (−50 to 500 °C), this study developed a phosphate-based composite lubricating coating. Through air-spraying technology and orthogonal experimental optimization, the optimal formulation was determined as follows: binder/filler ratio = 6:4, 5% graphite, 15% MoS₂, and 10% aluminum powder. Experimental results demonstrated that at 500 °C, the coating forms an Al–O–P cross-linked network structure, with MoS₂ oxidation generating MoO₃ and aluminum powder transforming into Al₂O₃, significantly enhancing density and oxidation resistance. Friction tests revealed that the composite coating achieves a friction coefficient as low as 0.12 at room temperature with a friction time of 260 min. At 500 °C, the friction coefficient stabilizes at 0.24, providing 40 min of effective protection. This technology not only resolves the high-temperature instability of traditional coatings but also ensures an environmentally friendly preparation process with no harmful emissions, offering a technical solution for the protection of high-temperature equipment such as thermal power plant boiler tubes and petrochemical reactors. Full article

Circulating fluidized bed combustion (CFBC) ash, a byproduct typically generated from coal-fired CFBC power plant boilers, contains high content of free lime and anhydrite. Due to its chemical composition, CFBC ash exhibits self-cementing properties; however, its performance is limited. One approach to enhancing the self-cementing properties of CFBC ash is through the incorporation of mineral admixtures such as gypsum. This study investigated the influence of desulfurization gypsum (DG) on the self-cementing behavior of CFBC ash. To this end, paste and mortar specimens were prepared and evaluated for their hydration and mechanical characteristics. The hydration behavior was analyzed using isothermal calorimetry, thermogravimetric analysis (TGA), setting time measurements, and X-ray diffraction (XRD) analysis. Mechanical properties were assessed by measuring the compressive strength at various curing ages. Additionally, changes in microstructure were examined by evaluating the pore size distribution through mercury intrusion porosimetry (MIP). The experimental results indicate that the appropriate incorporation of DG enhances the hydraulic reactivity of CFBC ash and significantly improves the compressive strength. Full article

Currently, ecological energy production is one of the most pressing issues in power engineering. In addition, environmental pollution caused by various emissions and the challenge of waste disposal remain significant global concerns. One potential solution to these problems is the conversion of waste into useful energy through combustion. In this study, experimental investigations were carried out on the combustion of municipal solid waste (MSW) in a grate furnace of a 400 kW hot water boiler. The experiments included the combustion of both MSW and traditional brown coal. Data were collected on the concentrations of various substances in the exhaust gases, and thermal imaging was performed to assess heat losses from the boiler surface. When burning waste compared to coal, SO₂ concentrations were significantly lower, ranging from 3.43 to 4.3 ppm, whereas for coal they reached up to 122 ppm. NO_X concentrations during MSW combustion peaked at 106 ppm, while for coal combustion they reached 67.5 ppm. A notable increase in CO concentration was observed during the initial phase of coal combustion, with levels reaching up to 2510 ppm. The thermal efficiency of the boiler plant reached 84.4% when burning waste and 87% when burning brown coal. Full article

The estimation of available active power in coal-fired thermal power plant units involves considerable complexity and remains a critical task for plant operators. To avoid compromising system stability, operators often operate the thermal unit below its full capacity. To address this issue, the aim of this paper is to facilitate the process of estimating the maximum active electrical power by applying an assistive system based on ANFIS (Adaptive Neuro-Fuzzy Inference System), a method that combines the strengths of neural networks and fuzzy logic. Since the generated electric energy is directly linked to the amount of thermal energy produced, the analysis is focused on the boiler combustion process. It has been shown that the key factors in this process are the coal mills and their achievable capacity, as well as the calorific value of coal. Therefore, the proposed assistive system is based on the estimation of the available capacity of each active mill, which is then combined with the estimated calorific value of the coal to determine the achievable active electrical power of the unit. The conducted analysis and experiments confirm the validity of this approach. Full article

To promote low-carbon transformation and achieve carbon peak and neutrality in the energy field, this study proposes an operational optimization model considering the energy- and load-side dual response (ELDR) mechanism for electrothermal coupled virtual power plants (VPPs) containing a carbon capture device. The organic Rankine cycle (ORC) waste heat boiler (WHB) is introduced on the energy side. The integrated demand response (IDR) of electricity and heat is performed on the load side based on comprehensive user satisfaction (CUS), and the carbon capture system (CCS) is used as a flexible resource. Additionally, a carbon capture device operation mode that makes full use of new energy and the valley power of the power grid is proposed. To minimize the total cost, an optimal scheduling model of virtual power plants under ladder-type carbon trading is constructed, and opportunity-constrained planning based on sequence operation is used to address the uncertainty problems of new energy output and load demand. The results show that the application of the ELDR mechanism can save 27.46% of the total operating cost and reduce CO₂ emissions by 45.28%, which effectively improves the economy and low carbon of VPPs. In particular, the application of a CCS in VPPs contributes to reducing the carbon footprint of the system. Full article

It is important to predict air pollutant emissions from coal-fired power plants using real-time technological parameters to improve environmental efficiency. Since the relationship between emissions and parameters is nonlinear, machine learning models are needed to forecast emissions under various boiler operating modes. This study develops and tests Deep Sparse Transformer Networks for predicting pollutant time series, accounting for long-term dependencies. Data were collected from a 4000 MW coal-fired power plant in Ekibastuz, Kazakhstan, covering 67,527 records for 14 indicators at 10 min intervals. Fractal R/S analysis confirmed long-term memory in SO₂, PM_2.5, and NO_x series, guiding window length selection. The results show that the model achieves slightly better accuracy for SO₂ (R² 0.95–0.38), while NO_x and PM_2.5 have similar dynamics (R² 0.93–0.26). However, accuracy drops notably after 12 points, making the model best suited for short-term forecasts. These findings support environmental monitoring services and help optimize plant parameters, contributing to lower emissions and advancing carbon neutrality goals. Full article

In the age of widespread renewable energy integration, coal-fired power plants are transitioning from a primary baseload role to a more flexible peak-shaving capacity. Under frequent load changes, the thermal efficiency will significantly decrease. In order to achieve efficient dynamic operation, this study proposes a comprehensive mechanical model of a 300 MW drum-type boiler. Based on the Modelica/DYMOLA platform, the multi-domain equations describing energy and mass balance are programmed and solved. A comprehensive evaluation of the energy transformation within the boiler’s heat exchange components was performed. Utilizing the principles of exergy analysis, this study investigates how fluctuating operational conditions impact the energy dynamics and exergy losses in the drum and heating surfaces. Steady-state simulation reveals that the evaporator and superheater units account for 81.3% of total exergy destruction. Dynamic process analysis shows that the thermal inertia induced by the drum wall results in a significant delay in heat transfer quantity, with a dynamic period of up to 5000 s. The water wall exhibits the highest total dynamic exergy destruction at 9.5 GJ, with a destruction rate of 7.9–8.5 times higher than other components. Full article

Heavy fuel oil (HFO) is a widely used fuel in compression ignition engines, primarily in Brazilian thermoelectric plants, mainly due to its availability, low cost, and low operational expenses. However, heavy fuel oil is not compatible with most diesel engines and combustion systems in use and must be treated to maintain combustion process efficiency. The high viscosity of heavy fuel oil must be reduced before being introduced into the engine. To achieve this, appropriate heating devices are added to the fuel lines, with steam being the primary working fluid in these devices. Steam-generating boilers that burn fossil fuels, including HFO itself, are the most viable option from an economic standpoint and in terms of utilizing locally available fuels for this function. However, the need to mitigate the effects of environmental pollution has encouraged the adoption of other types of boilers, such as electric ones. In this work, a case study of a combustion steam generator installed in a Brazilian thermoelectric plant is developed. This study involves the thermodynamic and combustion modeling of the steam generator through the balancing of the respective thermodynamic and combustion equations. The models and the proposed chemical formula of HFO were validated, and through simulations using real data collected during the boiler’s operation throughout 2024, it was also possible to estimate the carbon dioxide emissions produced. Additionally, a hypothetical scenario was simulated in which the combustion boiler currently installed in the plant is replaced by two electric boilers. A simple economic analysis demonstrated that such a replacement would result in a total steam production cost of only 25% of the amount spent on the current combustion boiler, in addition to reducing $C{O}_2$ emissions to the atmosphere by 62.55 tons. Full article