Feed Water Flow Rate Research Articles

Simulation of Dynamic Characteristics of Supercritical Boiler Based on Coupling Model of Combustion and Hydrodynamics

To accommodate the integration of renewable energy, coal-fired power plants must take on the task of peak regulation, making the low-load operation of boilers increasingly routine. Under low-load conditions, the phase transition point (PTP) of the working fluid fluctuates, leading to potential flow instability, which can compromise boiler safety. In this paper, a one-dimensional coupled dynamic model of the combustion and hydrodynamics of a supercritical boiler is developed on the Modelica/Dymola 2022 platform. The spatial distribution of key thermal parameters in the furnace and the PTP position in the water-cooled wall (WCW) are analyzed in a 660 MW supercritical boiler when parameters on the combustion side change under full-load and low-load conditions. The dynamic response characteristics of the temperature, mass flow rate, and the PTP position are investigated. The results show that the over-fire air (OFA) ratio significantly influences the flue gas temperature distribution. A lower OFA ratio increases the flue gas temperature in the burner zone but reduces it at the furnace exit. The lower OFA ratio leads to a higher fluid temperature and shortens the length of the evaporation section. The temperature difference in the WCW outlet fluid between the 20% and 60% OFA ratios is 11.7 °C under BMCR conditions and 7.4 °C under 50% THA conditions. Under the BMCR and 50% THA conditions, a 5% increase in the coal caloric value raises the flue gas outlet temperature by 32.7 °C and 35.4 °C and the fluid outlet temperature by 6.5 °C and 9.9 °C, respectively. An increase in the coal calorific value reduces the length of the evaporation section. The changes in the length of the evaporation section are −2.95 m, 2.95 m, −2.62 m, and 0.54 m when the coal feeding rate, feedwater flow rate, feedwater temperature, and air supply rate are increased by 5%, respectively.

Assembly and operation optimization of proton exchange membrane water electrolyzer for performance enhancement

Abstract Proton exchange membrane water electrolysis (PEMWE) for hydrogen production possesses wide-ranging and rapid dynamic response capabilities, offering promising applications in the consumption of new energy sources and the dynamic balancing of power grids with a high proportion of renewable energy. The assembly and operating conditions of PEMWE significantly affect its performance. Therefore, thoroughly studying and understanding the influence of PEMWE’s assembly and operating conditions on water electrolysis performance are crucial for enhancing PEMWE’s performance and promoting its applications. In this research, the influence of installation preload torque, feedwater flow rate, and operating temperature on the performance of the electrolyzer, including the electrochemical active specific surface area (ECSA), high-frequency resistance (HFR) and various types of polarizations (including activation polarization, ohmic polarization, and mass transfer polarization) during the operation of the electrolyzer, were detailedly investigated. The results showed that the optimal preload torque and operating temperature for the electrolyzer were 3 Nm and 80°C. Under these conditions, an optimized PEMWE performance would be achieved by ensuring that the feedwater flow rate exceeded the water consumption during electrolysis.

Cation selectivity during flow electrode capacitive deionization

Efficient separation of specific ions from aqueous media is crucial for advanced water treatment and resource recovery. Flow electrode capacitive deionization (FCDI) offers potential for selective ion removal through continuous operation. This study evaluates the performance of selective cation separation using a commercial activated carbon slurry in a multi-ion solution of monovalent (Li+, Na+, K+) and bivalent (Ca2+, Mg2+) cations. We assess ion removal and cation selectivity under different operational parameters, such as applied potential, slurry flow rate, and feed water flow rate. Our data show that bivalent cations, namely Ca2+ and Mg2+, are preferentially removal due to their higher charge-to-size ratio, aligning with hydrated ion sizes. The highest separation rate was observed for Ca2+ (5.7 μg cm−2 min−1), and the lowest for Li+ (0.2 μg cm−2 min−1). At the highest applied voltage (1.2 V), charge efficiencies reached 70 %, with an energy consumption of 41 Wh mol−1 for nearly complete cation removal. Optimal conditions were identified with a slurry flow rate of 6 mL min−1, feed water flow rate of 2 mL min−1, activated carbon content of 10 mass%, 1 mass% carbon black, and a cell voltage of 1.2 V. These findings highlight the importance of optimizing operational parameters to enhance ion removal.

A Thermodynamic Analysis of a Proton Exchange Membrane Electrolyzer

A thermodynamic, first law analysis was conducted to understand the temperature of a proton exchange membrane electrolyzer when operated at a constant voltage and feed water flow rate. When using the electrolyzer voltage, current, liquid water feed rate and temperature, the electrolyzer operating temperature can be calculated. Heat losses can also be accounted for but are currently neglected. Carpet plots show the resulting electrolyzer temperature under varying conditions. The calculated temperatures are in very good agreement with measurements conducted in our laboratories.

A Thermodynamic Analysis of a Proton Exchange Membrane Electrolyzer

A thermodynamic, first law analysis was conducted to understand the temperature of a proton exchange membrane electrolyzer when operated at a constant voltage and feed water flow rate. When using the electrolyzer voltage, current, liquid water feed rate and temperature, the electrolyzer operating temperature can be calculated. Heat losses can also be accounted for but are currently neglected. Carpet plots show the resulting electrolyzer temperature under varying conditions. The calculated temperatures are in very good agreement with measurements conducted in our laboratories.

Comparison study of two control strategies for the small pressurized water reactor

The control strategy has a significant impact on the control performance of the reactor system. This paper investigates the feedwater flow and steam flow control strategies for small pressurized water reactors. First, the mathematical model of the SPWR Nuclear Steam Supply System is introduced. Second, a dual-constant control strategy was proposed, and the feedwater flow rate and steam pressure control systems under the two control modes were designed. Moreover, a steam bypass control system was designed to avoid excessive steam pressure under the feedwater flow control mode, and the reactor power and pressurize control systems were introduced. Simulation results indicate that the two control modes both meet the SPWR control requirements. However, the feedwater flow control mode has better reactor coolant temperature and steam pressure control performances during the load rejection transient, owing to the timely discharge of heat from the reactor coolant system through the steam bypass system.

Computational boundary improvement and performance optimization of the flue gas waste heat cascade utilization system of the ultra-supercritical 1000 MW generator set

Abstract There is no uniform performance test rule and standard calculation method for efficiency improvement of a system that utilizes waste heat from flue gas and it is mainly carried out through turbine parameters, without considering boiler system performance. Given the above problem, in this paper, the steam turbine, boiler and waste heat from the flue gas step-up utilization system are calculated by establishing a thermal model of ultra-supercritical secondary reheating 1000 MW unit. At the same time, unit design data and field performance test results are used for verification. Analysis comparing simulation outcomes with experimental data revealed that the discrepancies in the heat consumption rate per unit, the efficiency of the boiler, and the rate of coal consumption for power generation peaked at a marginal variance of 0.2%. The optimum operating parameters of the system for low-grade flue gas recovery in a cascading manner are obtained through variable operating condition calculations. The optimum value of high-pressure bypass feed-water flow rate is 52 kg/s at 970 MW operating condition. At the same time, the difference between high-pressure bypass effluent and high plus effluent temperatures should be controlled to be close to 0°C, and the optimal value of low-pressure bypass condensate flow rate is 53 kg/s. As the flow of flue gas in the bypass increases, the efficiency of heat exchange in the bypass economizer also increases, resulting in greater absorption of heat in the utilization apparatus for flue gas waste heat, leading to a more effective energy-saving outcome. However, it is necessary to regulate the temperature of both the primary and secondary air to levels that exceed the minimum requirements for the safe functioning of the coal mill.

Optimizing reverse osmosis desalination from brackish waters: Predictive approach employing response surface methodology and artificial neural network models

A mathematical model frame has been developed to optimize the performance of reverse osmosis (RO) desalination in brackish waters with medium to high salt concentrations using response surface methodology (RSM) and artificial neural network (ANN), specifically catered towards efficiently operating RO desalination systems. The RSM model aims at predicting RO performance with second-order polynomials based on 15 experimental datasets. Inputs for RSM model include feed TDS concentration, feed water flow rate, and concentration-to-desalination ratio, while the outputs consider rejection, membrane flux, performance index, and specific energy consumption. The Genetic Algorithm optimized back-propagation Neural Network was employed to update network weights and biases, leading to an optimal ANN network structure of 3–10-4. A ratio of 70 % training, 15 % validation, and 15 % test data was chosen to establish an ANN model that predicts the performance of RO desalination. The ANN model demonstrated significantly higher prediction accuracy than the RSM model, with impressive correlation coefficients of 0.9936 for the performance index and 0.9932 for SEC prediction, and low RMSE of 0.85 for rejection. To maximize the performance index and minimize specific energy consumption, a two-step optimization method was further set up by applying the RSM model to initially determine optimal process conditions followed by the ANN model to enhance the accuracy of performance forecasts. Optimal process conditions were proposed for specific feed TDS scenarios, which involved setting a feed TDS concentration limit to meet drinking water standards.

A reduced model for pilot-scale vacuum-enhanced air gap membrane distillation (V-AGMD) modules: Experimental validation and paths for process improvement

A fast and robust computational model of a spiral-wound vacuum-enhanced air gap membrane distillation (V-AGMD) module at the pilot-scale is proposed and implemented. In contrast with data-driven models available in the literature, a physics-based approach is adopted for more reliable generalization beyond the validation dataset. A total of 86 experimental results, of which 41 are described in this work and 45 come from independent sources available in the literature, are used in the validation effort with quite favorable results. With the confidence on the robustness of the methodology due to the wide range of operational parameters and the use of spiral-wound modules of four different sizes included in the validation comparisons, a physical analysis is conducted varying the air gap pressure, the number of feedwater channels, the feedwater flow rate, and the membrane area. Improvements of up to 60% in both water productivity and energy efficiency can be achieved by intensifying the vacuum in the air gap or decreasing the number of feedwater channels. These parameters achieve performance gains due to less resistance in the air gap for vapor to migrate through it, in the former case, and a reduced temperature polarization effect, in the latter case. Smaller flow rates favor energy efficiency at the expense of water productivity by simultaneously decreasing transport-phenomena-related irreversibility and the partial pressure difference across the membrane and the air gap. In addition, this tradeoff between energy efficiency and driving force is shown to lead to an optimum value for the membrane area beyond which the permeate flow rate through the membrane starts to fall due to the small driving force. An illustrative case is predicted to achieve energy efficiency metrics, such as a gain-output ratio of 12.7, competitive with multi-effect distillation.

Моделирование установки замедленного коксования в программе MatLab

In order to prevent the occurrence of an emergency situation in the oil and gas industry, it is necessary to use control, automation and alarm systems. In this regard, artificial intelligence technologies have recently become in-creasingly popular. Neural networks are of particular interest. To implement the task of regulating, automating and predicting technological processes in the oil industry, it is possible to use neural network modeling of chemical and technological processes. Examples of using neural network modeling in practice are given. The results of neural network modeling of a delayed coking plant of one of the operating enterprises are presented. A delayed coking installation was modeled in the UniSim Design software package, which allowed us to obtain an initial data array for a neural network. The neural network was built in the MatLab program, and the program code was created. Graphs of error and regression are presented. The analysis of the results presented on the regression and error graphs is given. As a result of testing the model, minimal discrepancies between experimental and predicted data were obtained, which indicates the adequacy of the neural network model. An additional test of the program was also performed. The results of training and testing of the model are presented. The results obtained can later be used to create programs at different levels of control, since the model allows you to estimate the amount of losses during the operation of the installation at a certain flow rate of feed water supplied to the installation as a turbocharger.

Multi-stage humidification–dehumidification system integrated with a crystallizer for zero liquid discharge of desalination brine

Desalination plants discharge a massive volume of brine every day, which negatively affects the ecosystem, particularly the subsurface ecology and marine life. To mitigate the brines' detrimental effects on the environment and facilitate the recovery of salt crystals and freshwater, the Zero Liquid Discharge (ZLD) approach was proposed. This study proposes four different configurations of multistage humidification dehumidification systems integrated with a crystallizer, exploring their energy and economic implications. Key findings from the study include the higher Gained Output Ratio (GOR) in series configurations due to lower temperature differences, resulting in lower heater energy consumption. The crystallizer significantly enhances water productivity, but it is a major consumer of both electricity (85%) and thermal energy (50.45–57.7%) in the system. Increasing the heat source temperature reduces the Specific Electrical Energy Consumption (SEEC) and the specific area while slightly increasing the Specific Thermal Energy Consumption (STEC). Elevated cooling water temperature raises SEEC and specific area but has negligible effects on STEC. Higher feed water flow rates increase SEEC but lower both STEC and specific area. Feed salinity elevation decreases productivity, SEEC, STEC, and specific area. The crystallizer constitutes 15.43–26.44% of the total capital cost, with series configurations incurring higher costs. Unit freshwater production costs, considering salt selling, range from 1.733 to 4.821 $.m−3. In a waste heat scenario, parallel configurations become profitable, where freshwater can be distributed at zero cost, while the produced salt crystals can be sold at an even lower price of $58.09 per tonne and $57.04 per tonne, respectively.

Mechanism of Silica Nanoparticle-Induced Particulate Fouling in Vacuum Membrane Distillation.

Membrane distillation (MD) is a process driven by the vapor pressure difference dependent on temperature variation, utilizing a hydrophobic porous membrane. MD operates at low pressure and temperature, exhibiting resilience to osmotic pressure. However, a challenge arises as the membrane performance diminishes due to temperature polarization (TP) occurring on the membrane surface. The vacuum MD process leverages the application of a vacuum to generate a higher vapor pressure difference, enhancing the flux and mitigating TP issues. Nevertheless, membrane fouling leads to decreased performance, causing membrane wetting and reducing the ion removal efficiency. This study investigates membrane fouling phenomena induced by various silica nanoparticle sizes (400, 900, and 1300 nm). The patterns of membrane fouling, as indicated by the flux reduction, vary depending on the particle size. Distinct MD performances are observed with changes in the feed water temperature and flow rate. When examining the membrane fouling mechanism for particles with a porosity resembling actual particulate materials, a fouling form similar to the solid type is noted. Therefore, this study elucidates the impact of particulate matter on membrane fouling under diverse conditions.

Investigating the energy storage performance in optimal design of a solar hybrid multi‐generation system with distillatory

AbstractIn this study, a cogeneration system of heating, cooling and power used with the solar flat plate collectors (FPCs) and photovoltaic panels (PVs) integrates with a multi‐effect distillation through thermal vapor compression (MEE‐TVC), investigated as the first system to meet the loads of heating, cooling, electricity and fresh water. As an innovation, the combination of the first system with cooling and thermal storage tanks have been investigated. The systems are optimized with MATLAB and single‐objective genetic algorithm. The total annual cost considered as the objective function to compare the two systems and 36 and 61 design variables are obtained for the first and second systems, respectively. The design parameters considered for optimization included the capacity of the diesel engine as the prime mover, electrical chiller capacity, absorption chiller capacity, size of the boiler, partial loads of the diesel engine for each hour of the 2 days (1 day for hot months and 1 day for cold months), partial loads of the chillers for each hour of the first days (second day has no cooling load), number of FPCs and PVs, number of effects in the desalination unit, driving steam pressure, feed water flow rate, driving steam flow rate, and electric cooling ratio. The optimization aimed to fulfill the heating, cooling, electricity, and fresh water requirements of a residential town situated in Bandar Abbas, Hormozgan province, Iran. The second system's optimization results were compared with first system. The results have shown that the objective function for the first system was and the initial investment cost was , and for the second system the objective function was and the initial investment cost was . Therefore, by using energy storage, the objective function was reduced by 11.30%.

Development of automatic control system of drum boiler on the basis of fuzzy controller with pid-controller adaptation

The aim of the study is to reduce energy losses in a drum steam boiler by introducing an automatic control system realized on the basis of fuzzy adaptation of proportional-integral-derivative (PID) controller coefficients using fuzzy term-multiplications. Control algorithms of the main technological parameters of the boiler unit (air quantity, fuel quantity, steam pressure, feed water flow rate), reducing energy costs due to the maintenance of the ratio of fuel and air pressure in accordance with the mode map of the boiler unit (optimal technological process of combustion and steam formation in a steam boiler) are developed. The structural scheme of the object control is offered, in which, besides regulation of values of technological parameters, full compensation of mutual influence of all regulation circuits is made.

Towards long-term operation of flow-electrode capacitive deionization (FCDI): Optimization of operating parameters and regeneration of flow-electrode

This study systematically optimized the key operating parameters and interpreted their effecting mechanisms in a flow-electrode capacitive deionization (FCDI) system. The optimal voltage, activated carbon electrode content, electrolyte concentration, feedwater flowrate, and electrode flowrate for desalinating low salinity feedwater (1.0 g L−1 NaCl) were determined to be 1.8 V, 2.0 wt%, 10.0 g L−1, 80 mL min−1, and 60 mL min−1, respectively. The variations of the above parameters can affect the system conductivity, the thickness and stability of the electric double layers, and/or the degree of concentration polarization, thereby influencing the desalination performance. Moreover, a sensitivity analysis identified the operating voltage as the dominant parameter with the most significant influence on the FCDI system. Subsequently, a long-term operation was carried out under single-pass mode. The results showed that the lab-scale FCDI system was able to constantly maintain the desalination efficiency of 1.0 g L−1 feedwater (NaCl) at 40–60 % for multiple operating cycles. Over 99.8 % of electrode material regeneration and desalination efficiency recovery was able to be obtained during a 60-h operation, demonstrating that the FCDI system showed strong stability and long-term operation potential.

EXPERIMENTAL ANALYSIS OF HEAT TRANSFER AND THERMAL PERFORMANCE OF PARABOLIC TYPE SOLAR COLLECTOR WITH RIBBED SURFACE TEXTURE FOR CLEAN ENERGY EXTRACTION

This paper examines the performance of a parabolic type solar collector (PTSC) that uses both plain tube and ribbed surface textured tube channels for elevating the water temperature used for various applications. The performance of a solar water heater is evaluated experimentally. During the experiment, the solar radiation intensity and the feed water flow rate of 1.0 kg/min to 5.0 kg/min in steps of 1 kg/min are taken into consideration for analyzing the effect of ribbed textured tubes on the thermal effectiveness, frictional factor, convective transfer of heat, Reynolds number, and the Nusselt number of the PTSC. Furthermore, the overall performance of the PTSC is analyzed considering the above thermo-physical parameters. Based on the result of this study, at a flow rate of 3.0 kg/min, the thermal efficiency is found to be enhanced by about 28.25%, the friction factor is augmented by about 0.23%, the convective heat transfer coefficient is improved by 24.22%, and the Nusselt number is increased by about 26.32%. On average, an overall improvement in the performance of 8.25% is observed for the ribbed textured tube than that of the plain tube. The experimental error analysis shows that the standard deviation for both plain and ribbed textured tubes is in the range of 3.2, which is in the acceptable limit.

Molten Salt Reactor Loss of Flow Accident Analysis using the NERTHUS Dynamic Model

Background Molten salt reactors (MSRs) can have different behavior to various types of accidents compared to conventional reactors. MSRs also have different safety limitations that many are unfamiliar with. With limited operating time, simulations with a dynamic model are a valuable method of analyzing the effects of potential accidents scenarios. Methods The model used in this work is the NERTHUS Dynamic Model in MATLAB-Simulink, which is a generic MSR design agnostic to any specific reactor design. The type of accident investigated in this work are pump failures in each of the fluid loops (i.e., primary, secondary, and tertiary) with no control rod movement and the only response being a trip to the once-through steam generator feedwater at different delay times. Pump failure was modeled as an exponential decay curve to represent the effects momentum would have on the resulting flow coastdown. Results The results of these simulations show that an MSR could be safely powered down in the event of a pump failure by decreasing the feedwater flow rate to the steam generator in a timely manner. A delayed response leads to fluid temperatures in the loops rapidly decreasing to the point where freezing of the coolant salts can become a concern. Conclusions The trending behavior across the simulations is that the temperatures between the reactor core outlet and the location of the pump failure increase compared to pre-transient conditions. The temperatures of the loops further downstream than the pump failure will decrease unless action is taken.

A Novel Configuration of Hybrid Reverse Osmosis, Humidification–Dehumidification, and Solar Photovoltaic Systems: Modeling and Exergy Analysis

The pressing demand for clean water worldwide has increased attention to developing innovative desalination processes. In this work, the second law of thermodynamics is used to examine and assess two coupled desalination systems: a separation-based reverse osmosis (RO) system and a thermal desalination-based humidification–dehumidification (HDH) system. The HDH unit configuration used here is based on the working principle of the heat pump, where the process is open-air, open-water, and air-heated. The RO system is equipped with a pressure exchanger (PX) and has been examined under various operating circumstances, such as different feed water pressures, salinities, and flow rates. To improve the system’s sustainability, a solar photovoltaic system (PV) was integrated. An exergy model was used to precisely evaluate the system components and the hybrid systems by employing a proper exergy efficiency definition. The evaluation of the second law of thermodynamics for the RO–HDH–PX and RO–HDH–PX–PV systems indicated maximum efficiencies of 23% and 23.25%, respectively. A cost analysis was also performed on the hybrid RO–HDH–PX–PV desalination system using two approaches: the first included a battery storage system, whereas, in the second, the battery was not considered. When a battery storage system is included, the cost per cubic meter varies from USD 3.22 to USD 5.10. In contrast, it varies from USD 3.96 to USD 7.12 without a battery storage system.

Digital twin modeling and operation optimization of the steam turbine system of thermal power plants

The increasing deployment of renewable energy sources necessitates peak regulation services from thermal power plants, impacting their energy efficiency. Central to these plants, the steam turbine system significantly influences their operational efficiency. A digital twin model of this system was developed, integrating mechanism-driven and data-driven modeling methods. The neural network data-driven approach was specifically utilized for parameters such as feedwater pump speed and steam flow rate to the pump turbine. Other parameters were modeled with mechanism data hybrid driven modeling method. This model computes vital metrics such as low-pressure turbine exhaust steam enthalpy, work done and heat absorption per unit mass of steam, system efficiency, feedwater mass flow rate, and water-coal ratio—key for evaluating and enhancing the system's energy efficiency. An investigation into a reference case showed a decline in efficiency below design levels due to aging. By optimizing the live steam pressure and the cold-end system, relative improvements in energy efficiency of 0.35 % and 0.14 %, respectively, were achievable.

Thermodynamic modeling and optimization of a novel hybrid system consisting of high-temperature PEMFC and spray flash desalination

The current study proposes a novel hybrid system consisting of the high-temperature proton exchange membrane fuel cell (HTPEMFC) and spray flash desalination (SFD) system to harvest the waste heat from HTPEMFC. The output power density and energy efficiency are analyzed to evaluate the system performance. Comparing the hybrid system with the stand-alone HTPEMFC system reveals that the maximum power density and energy efficiency of the proposed system are 69% and 40% higher than those of the stand-alone HTPEMFC system. Moreover, many parametric studies are conducted to determine how the performance of the hybrid system depends on its design and operating conditions. The cell working temperature exhibits contrary effects on the HTPEMFC and SFD system. The doping level should be less than 30 considering the stability of the membrane and the improvement of thermodynamic performance. A lower flow rate of feed water or a higher flow rate of cooling water is conducive to the proposed system. Finally, the multi-objective optimization is performed based on the genetic algorithm.