Power Plant System Research Articles

Capacity Value Assessment for a Combined Power Plant System of New Energy and Energy Storage Based on Robust Scheduling Rules

With the rapid increase in new energy penetration, the uncertainty of the power system increases sharply. We can smooth out fluctuations and promote the more grid-friendly integration of new energy by combining it with energy storage. This paper proposes an evaluation method for assessing the value of a combined power plant system of new energy and energy storage using robust scheduling rules. Firstly, the k-means clustering algorithm is improved by using the elbow method in order to generate typical scenarios that can be used for the operation optimization of the combined power plant system of new energy and energy storage. Then, a two-stage robust optimization model of the combined power plant system of new energy and energy storage with a min–max–min structure is constructed according to the uncertainty of new energy. In this model, the operation constraints and coordinated control of wind–solar–thermal–storage units are considered. By constructing the uncertainty set of the new energy output, the overall operating cost of the system is minimized and uncertainty adjustment parameters are introduced to flexibly adjust the conservatism of the scheduling rules. Furthermore, based on the column and constraint generation algorithm and strong duality theory, the original problem can be decomposed into a master problem and subproblems with mixed integer linear characteristics for an alternating solution, so as to obtain the optimal solution of the original problem, and finally obtain the robust scheduling rule with the lowest operating cost under the worst scenario. Finally, based on the wind and solar power output curves and the output of each unit under the robust scheduling rules, combined with the value estimation method of the combined power plant system of new energy and energy storage, the value of the combined power plant system of new energy and energy storage is evaluated. Through the establishment of models and example analysis, it is proven that raising the quantity of the grid-connected power generated with new energy will cause an increase in the volatility of the power system; it will also bring considerable benefits to new energy plants, and the energy storage can improve the stability of the system. The above can provide references for the subsequent energy storage configuration in the planning of a combined power plant system of new energy and energy storage.

Optimal design and analysis of lubricating oil system in marine nuclear power based on adaptive genetic algorithm

Lubricating oil system is one of the important auxiliary systems of marine nuclear power plants. It can play the role of reducing wear, cooling, cleaning, and sealing, to ensure the normal operation of the lubricating oil users. But the traditional design process of the lubricating oil system is complex and inefficient. Aiming at this shortcoming, a new design method for lubricating oil systems is proposed in this study based on the new hybrid genetic multi-objective optimization algorithm. The mathematical model of the lubricating oil system is developed on the basis of the model base established by SQL Server according to the actual equipment. The optimization algorithm is integrated into the design process so that the economic index and reliability index can be considered comprehensively. Through sensitivity analysis, the optimization parameters that have a great impact on the optimization objective are selected as optimization variables. Finally, two sets of optimization schemes are obtained. Scheme 1 is the optimal scheme of system weight and volume, and Scheme 2 is the optimal scheme of reliability. For the former, the weight and volume are optimized by 35.25% and 35.16%, respectively; for the latter, the reliability is optimized by 2.04%.

IoT Implementation for Monitoring and Controlling Solar Power Plant Systems

IoT Implementation for Monitoring and Controlling Solar Power Plant Systems

In-situ thermophysical measurement of flowing molten chloride salt using modulated photothermal radiometry

Molten salts are leading candidates for high-temperature heat transfer fluids (HTFs) for thermal energy storage and conversion systems in concentrated solar power (CSP) and nuclear energy power plants. The ability to probe molten salt thermal transport properties in both stationary and flowing status is important for the evaluation of their heat transfer performance under realistic operational conditions, including the temperature range and potential degradation due to corrosion and contamination. However, accurate thermal transport properties are usually challenging to obtain even for stagnant molten salts due to different sources of errors from convection, radiation, and corrosion, let alone at flowing status. To the best of authors’ knowledge, there is no available in-situ technique for measuring flowing molten salt thermal conductivity. Here, we report the first in-situ flowing molten salt thermal conductivity measurement using modulated photothermal radiometry (MPR). We could successfully perform the first in-situ thermal conductivity measurement of flowing molten NaCl-KCl-MgCl2 in the typical operating temperature (520 and 580 °C) with flow velocities ranging from around 0.3 to 1.0 m s−1. The relative change of the molten salt thermal conductivity was measured. Gnielinski’s correlation was also used to estimate the heat transfer coefficient h of the flowing NaCl-KCl-MgCl2 in the given experimental condition. The work showed the potential of the MPR technique serving as an in-situ diagnostics tool to evaluate the heat transfer performance of flowing molten salts and other high-temperature HTFs.

Suitable Analysis of Micro-Increased Capacity Model on Cold-End System of Nuclear Power Plant

The cold-end system of a nuclear power plant is a key complex node connecting the power generation system with the variable environmental conditions, and its operation, economy, and stability have become the main obstacles to further improving the performance of the first and second circuits. The current research on the interactions between the cold-end system and the thermal cycle of nuclear power mainly adopts the micropower model, while the existing condenser model does not take into account the influence of the turbine exhaust resistance and exhaust flow and other factors on the condenser vacuum change caused by the change in the circulating water flow rate and temperature in determining the optimal vacuum. This ignores the interactions between the equipment and the interconnections between the parameters, which results in the reduction of the model’s accuracy. This paper takes a nuclear power unit as an example, adopts the “constant flow calculation” method to calculate the heat balance of the two-loop thermal system of the nuclear power plant, and constructs an integrated simulation model of the reaction environment variables, the cold-end system, and the thermal cycle. Taking the circulating water temperature and flow rate as variables, the errors of the separate condenser model and the coupled model in circulating water parameter changes were obtained under the condition of satisfying the thermal system operation, and the circulating water temperature and flow rate change ranges applied by the separate condenser model were analyzed in order to reduce the amount of calculations when the unit power error was 1%. The results show that the circulating water temperature is 4 °C, the applicable range of the circulating water flow rate is 42 m3/s to the rated flow rate, the applicable range of the circulating water temperature is 20 °C, the applicable range of the circulating water flow rate is 32.12 m3/s to the rated flow rate, the applicable range of the circulating water temperature is 26 °C, the applicable range of the circulating water flow rate is 38.63 m3/s to the rated flow rate, the applicable range of the circulating water temperature is 30 °C, and the applicable range of the circulating water flow rate is 45 m3/s to the rated flow rate. At a circulating water temperature of 26 °C, the applicable range of the circulating water flow is between 38.63 m3/s and the rated flow; at a circulating water temperature of 30 °C, the applicable range of the circulating water flow is between 45.64 m3/s and the rated flow.

A novel solar-driven waste heat recovery system in solar-fuel hybrid power plants

Solar-fuel hybrid power generation can effectively reduce pollutants in fuel power plants and facilitate the efficient utilisation of solar energy. This study proposes a novel solar-driven waste heat recovery system for solar–fuel hybrid power plants. New system is integrated with parabolic-trough solar collector to drive the heat pump and optimise air pre-heating, offering unique advantages: solar energy amplification and upgraded utilisation. For a 600 MW unit, solar energy in new system generates an electric power of 9.0 MWe with a 0.67 % increase in thermal efficiency, almost twice that of conventional system. With waste heat recovery, the new system exhibits a solar-to-electricity efficiency of 42.12 %. The new system can increase boiler exergy efficiency from 47.78 % to 48.35 %, and decrease exergy loss of air pre-heating to 7.6 MWe. The essential energy saving mechanism of the new system can be attributed to the optimisation of air preheating. Owing to high thermal performance, new system can yield a net benefit of 13.82 million CNY/y, which is 2.6 times that of conventional system. The findings of this study can help for better understanding of solar energy amplification and and upgraded utilisation, thus opening new avenues for solar conversion in solar-fuel hybrid power generation systems.

Analysis of Combustion Characteristics in Boilers Using Comparison of Coal Fuel Mixtures and Bark Biomass To Determine Optimal Combustion Conditions in a Steam Power Plant

Currently, several material production industries have used self-sustaining power generation systems. Where the most common steam power plant system is found as an option to be used as a source of electricity. The use of biomass as an additional material for fuel in power plant has been widely carried out. This method is more commonly known as cofiring. Analysis of the cofiring combustion system of biomass in the boiler needs to be carried out in order to determine the characteristics of the combustion system that occurs. By varying the composition of the fuel, an analysis of the energy produced from the combustion reaction will be calculated. In this study, the comparison of the use of coal and wood bark was varied at conditions 80:20, 70:30, 60:40, 50:50, 40:60, 30:70, 20:80. Assuming that the steam rate and temperature conditions to be achieved from the combustion products are constant. From the results of the analysis it was found that an increase in the amount of cofiring bark resulted in a decrease in the heating value of the combustion reaction and an increase in fuel capacity. Thus, it can be concluded that the use of bark cofiring in boilers with a coal design is less effective because it will require additional energy to increase the fuel consumption rate and reduce combustion efficiency due to not achieving optimal combustion energy because the initial design combustion chamber capacity is fixed.

Ecological interface design and evaluation for feedwater dearating system in NPPs

Abstract A good human-computer interface can improve the efficiency of operators in the main control room of a nuclear power plant (NPP) and reduce operational errors. It has been shown that ecological interface design (EID) can effectively reduce the cognitive load of users, improve the level of situation awareness, and help users to make decisions quickly and effectively. In this paper, we analyzed the feedwater deaeration system (ADG) of nuclear power plants, constructed the work domain analysis according to the abstraction hierarchy theory. The factors that affect the balance of the system are clarified, and the ecological interface is designed based on it, so that it can present the system status and present the future development trend more intuitively, and support the operator to predict the system situation. In this study, 10 volunteers with relevant knowledge background were selected for operational experiments, with subjective evaluation based on SART scale and grey theory, which verified that EID interface has significant advantages over the original interface in supporting both operator response time and accuracy.

Influence of circuit on power generation performance of wave energy power generation device using oscillating water column technology

In order to study the influence of the load circuit on the system efficiency and power oscillation of the oscillating water column device, a unified modeling model of the oscillating water column device is built for simulation. According to the coupling relationship in various fields of the oscillating water column device, the differential equation of motion of the turbine generator set is established. The power plant components and systems are modeled by Modelica language. Based on this system, the system-level simulation is carried out and the load circuit is optimized. In addition, experimental tests of the traditional load circuit and the modified load circuit are carried out. Results indicate that the modified load circuit can increase the speed of the turbine to better follow the airflow and balance the system damping, thereby improving the system efficiency. Increasing resistance can reduce the fluctuation of output electric power. Different battery, resistance and generator parameters can cause differences in system efficiency. The research results provide a reference to improve the performance of oscillating water column device.

Techno-economic evaluation of energy storage systems for concentrated solar power plants using the Monte Carlo method

This paper aims to perform a techno-economic evaluation for the sensible heat, latent heat, and combined sensible-latent heat storage systems applied in concentrated solar power (CSP) plants. An analytical model that integrates the uncertainty of input variables is developed to observe the probability distribution of the levelized cost of electricity (LCOE) for various energy storage systems using a combination of Monte Carlo methods and economic indicators. Uncertainty quantification reveals that the combined sensible-latent heat storage system has the least uncertainty. The sensible-latent heat storage system has certainty equivalents of 0.1852 $/kWh and 0.1321 $/kWh for both the Blue Map and Roadmap scenarios, which is approximately 29% less than the two-tank molten salt energy storage system. Under emission trading, the environmental and social benefits of carbon reduction in energy storage systems can reduce the LCOE for CSP plants. This study can provide decision makers with more comprehensive information in determining the economic viability of different energy storage systems.

Thermodynamic analysis and operation strategy optimization of coupled molten salt energy storage system for coal-fired power plant

The growing use of renewable energy requires greater flexibility than existing thermal power units. A steam-extraction system was developed to adjust the power output during a low-load period. The incorporation of molten-salt energy storage enables the decoupling of the boiler from the turbine, thus enabling the regulation of the output power during low-load operation. And the impact of key parameters on the performance of coal-fired units is analyzed to find the suitable operation parameters for the existing coal-fired power plant. The performance parameters of the system are optimized by a multi-objective grey wolf optimization algorithm, which conducts trade-off optimization between roundtrip efficiency and exergy efficiency to identify the Pareto Front for a certain range of extracted steam mass flow rates, hot-tank temperatures, and split ratios. The typical operating conditions of the combined system were analyzed, and a peak capacity of 64.1 MW and a power change factor of 17.33 % were achieved. The discharging process reduced the heat consumption of the unit, while the peak capacity and heat consumption of the combined system were used as objective functions to optimize the charging process. The peak capacity, power enhancement rate, and net profits of the system improved 1.12, 1.42, and 1.27 times after optimization. Heat consumption and efficiency were reduced by 2.61 % and 3.96 %. The molten-salt thermal storage system achieved a synergistic improvement in the operational flexibility and thermal efficiency of the thermal power system.

The Effect of Wind Direction on the Cooling Capacity of Short Dry Natural Draft Cooling Towers Operating in Close Proximity

Abstract The layout of multiple natural draft dry cooling towers could have a significant influence on the performance of the cooling system in concentrated solar power (CSP) plants; however, this has never been quantified. Hence, this work used computational fluid dynamics (CFD) modeling to analyze the cooling capacity of two short natural draft dry cooling towers (NDDCTs) on a common site for a range of tower spacings, wind-speeds, and wind incidence angles. The results show that the cooling performance of the towers is a strong function of tower spacing and their orientation with respect to the wind direction. It was found that when the wind came at a 90-deg wind incidence angle (i.e., normal to a line drawn between the two towers), their cooling capacity was improved at tower spacings of less than 1.8 tower diameters (1.8D), though for the other tower spacings, there was no interaction between the towers. However, with the wind at 45 deg to the towers, the flow around the towers resulted in a decrease in their cooling capacity at tower spacings of 1.8D and 2.6D. Most interestingly, it was found that orienting the towers in line with the prevailing wind direction delivered improvements in the cooling capacity of up to 30%. This is due to the windward tower acting as a passive windbreak. Hence, as CSP plant capacity is increased, and additional cooling towers are required, these should be placed close to any existing tower and oriented along the line of the prevailing winds.

Evaluation of the Marine Impacts Resulting from the Using of Different Chemical Biocides in Cooling Water System of New Nuclear Power Plant

Evaluation of the Marine Impacts Resulting from the Using of Different Chemical Biocides in Cooling Water System of New Nuclear Power Plant

Evaluation of the Marine Impacts Resulting from the Using of Different Chemical Biocides in Cooling Water System of New Nuclear Power Plant

Evaluation of the Marine Impacts Resulting from the Using of Different Chemical Biocides in Cooling Water System of New Nuclear Power Plant

Design and Verification of Key Components of a New Selective Catalytic Reduction System in a Petrochemical Captive Power Plant

A new selective catalytic reduction (SCR) system for captive power plants in the petrochemical industry was analyzed. The key components suitable for the target SCR system were obtained using computational fluid dynamics (CFD) numerical simulation combined with a cold physical model. The structural characteristics of the SCR system were studied, and corresponding design schemes were obtained for the key components, such as the guide plate, the ammonia injection grid (AIG), the static mixer, and the rectifier grille. The distributions of the flue gas velocity and the NH3 concentration within the flue cross-section in front of the first layer catalyst were studied in detail. Synchronously, the pressure loss and the temperature reduction characteristics in the SCR system were also considered. CFD results showed that the average standard deviation of the flue gas velocity was about 11.61%, and the average standard deviation of the NH3 concentration distribution could reach about 3.79% under the five operating conditions. It could be concluded that the uniformity of the flue gas velocity and the NH3 concentration distribution within the above flue cross-section was guaranteed by comparing to the design standard of 15% and 5%, respectively. It was further found that the maximum pressure loss between the inlet and the first layer catalyst was about 106.64 Pa, and the temperature reduction characteristic of the entire SCR system could be maintained within ±0.01 °C, which indicated that no extreme adverse effect arose due to the introduce of the key components. The cold physical model experiment was accordingly conducted to verify the reliability of the above CFD results. The cold physical model experiment results showed that the average standard deviation of flue gas velocity was about 8.82%, and the average standard deviation of NH3 concentration distribution could reach about 4.21%. The maximum biases for the standard deviations of the flue gas velocity and the NH3 concentration distribution were approximately 4.83% and 1.18% under the five operating conditions. Based on the good agreement of the research results via the two different methods, the designed key components of a new SCR system could be confirmed to be feasible, which would benefit the deNOx performance of the SCR system.

Predicting pneumatic conveyability and flowability of fly ash using bulk property characterization

Pneumatic fly ash conveying systems in thermal power plants are often not able to transport ash as per their expected duty due to either variability of ash characteristics and/or inadequate system sizing resulting in generation loss and reduced ash utilization. This paper results from an ongoing investigation into the relationship between the physical characteristics of ash to some of the important design criteria, such as ash conveyability and flowability. Based on a comprehensive test program including the pneumatic conveying (in a pilot plant) and flow property testing of 23 ash samples obtained from five different power stations, predictions for conveyability and flowability have been made using bulk property characterization. Of all the different particle and bulk parameters investigated, the angle of repose has been found to be the most significant parameter linking conveyability and flowability. A newly developed design tool based on the angle of repose is expected to assist designers and operational engineers to predict the flow condition and appropriately size equipment/system with suitable operating parameters.

Reliability Analysis of Nuclear Power Plant Electrical System Considering Common Cause Failure Based on GO-FLOW

The reliability of nuclear power plant electrical systems is an important guarantee of nuclear safety, and the common fault failure problem arising from redundant design and intelligent control may greatly affect reliability assessment results. Combined with the features of repairability, multi-state characteristics, and common fault failure of nuclear power plant electrical systems, a reliability analysis method of nuclear power plant electrical systems based on the GO-FLOW method considering common fault failure is proposed. This study firstly constructs the algorithmic model of combining operators of repairable components and the equivalent model of reliability parameters of multi-mode repairable components, then establishes a probability calculation model of common fault failure for repairable systems by considering the quantitative computation of the common signaling system model, and finally, quantitatively calculates the reliability of nuclear power plant electrical systems and their influencing factors. The example simulation calculates the reliability of the external power supply system and the electrical system of the nuclear power plant, analyzes the influence of the common signal processing and the common fault failure factors on the reliability of the electrical system of the nuclear power plant, and verifies the validity of the proposed method. The results show that the common fault failure factors have a large impact on the system reliability analysis; the common fault failure of the standby diesel generator set will seriously reduce the reliability of the electrical system, which can be improved by installing additional standby diesel generators.

Security measurement of instrumentation systems: A case study of NPP

Current instrumentation systems are distributed in nature and hence consist of different processing nodes that are interconnected with each other to exchange the data. The input data is processed into a meaningful data and output to other processing nodes. The output of the nodes depends on the input data and hence the validity of the input data needs to be ensured for the correct functioning of the overall system. Many of the instrumentation systems are safety critical in nature and contains confidential data and hence it must be secure from outside access. Due to the security significance of these systems, there is a need to assure the secrecy of systems at an early stage. In order to improve the security of instrumentation systems, this paper introduces a threat-driven modelling framework to measure the security threats using Petri Net. The technique has been validated on 21 instrumentation systems of Nuclear Power Plant and illustrated on a case study in this paper.

ECOC-based integrated learning method for fault diagnosis in nuclear power plants

Abstract The fault diagnosis system of nuclear power plants plays an important role in ensuring the safety and economy of nuclear power plant operations. This paper first analyzes typical faults of nuclear power plants and their phenomena, and fault samples are obtained. A comprehensive study of the structure of the nuclear power plant system, its working mode and the association between each subsystem is carried out to analyze the monitoring parameters and fault characteristics and establish the fault data set. Secondly, an IFWA (Improved Fireworks Algorithm - Integrated Learning) algorithm is proposed to assess the severity of faults in the first circuit of a nuclear power plant. Finally, the fault diagnosis module is divided into three units according to the functional logic, i.e., condition monitoring unit, fault identification unit, and fault severity assessment unit. The results show that the diagnostic accuracy of the IFWA algorithm is 94.25% for SGTR in the single-fault diagnosis experiment and 96.25% for SGTR-LOCA in the multiple-fault diagnosis experiment. It shows that the IFWA algorithm proposed in this paper has the optimal performance capability when applied to nuclear power plant fault diagnosis and effectively assists managers in diagnosing faults and giving maintenance recommendations.

Exploring energetic, exergetic, economic and environmental (4E) performance of waste heat power generation in nuclear power plant systems: A perspective of pattern recognition

Combined cogeneration systems are employed to recover waste heat from the sCO2 cycle in nuclear power generation systems. However, dealing with their multidimensional and nonlinear design and optimization spaces is a complex challenge for designers. In this study, the combined cogeneration system is parameterized and modeled: 4E models including energetic, exergetic, economic and environmental are established for sCO2 combined Organic Rankine Cycle (sCO2/ORC) and trans-critical CO2 Cycle (sCO2/tCO2) respectively. Several decision variables and five performance indicators are selected. To gain a deeper understanding of the mechanisms and optimize the combined cogeneration system, pattern recognition methods including the Self-Organizing Map (SOM), an unsupervised competitive learning approach, and Statistical Sobol Global Sensitivity Analysis methods are proposed. These techniques help identify key parameters and system patterns within the design space. Then, the Non-Dominated Sorting Whale Optimization Algorithm (NSWOA) is adopted to build a Pareto-optimal decision space, and the SOM and PCPs are proposed to visualize and mining based on pattern recognition and graph visualization interaction. The design parameters of the top cycle, P2, PRc, and x, have been confirmed as having a substantial impact on the system's performance. The multiple attributes, criterions and objectives problems in the combined cogeneration system are ultimately simplified to “Economy-Environment”, double objectives problem, and three trade-offs’ solutions are discussed: prioritizing economics, prioritizing the environment, and finding a balanced economic-environmental compromise. Pattern recognition method provides decision-makers with a fresh perspective for gaining a deeper understanding of the multi-criteria objectives space and potential trade-offs. The integration of pattern recognition into the thermodynamic, economic, and environmental models outlined in this paper represents a substantial and valuable advancement in the analysis and optimization of combined cogeneration cycles.