Power Plant System Research Articles

Development and validation of a liquid chromatography‐mass spectrometry method for quantification of octadecylamine in the secondary circuit of a nuclear power plant in the presence of other amines

AbstractOctadecylamine (ODA) is the most widely used film‐forming amine in the nuclear industry. Its function is to minimize corrosion. In this work, we developed and validated a liquid chromatography‐mass spectrometry method that allows the quantification of ODA in the presence of other amines in the secondary system of nuclear power plants operating under all‐volatile treatment chemistry. Sample stabilities greater than 95% were achieved after 1 week of being taken in acetonitrile 1:1. The method showed a high selectivity allowing the measurement of ODA in the presence of other amines. The calibration curve was linear in the range of 0.0025–0.1025 mg/L. The limit of detection and limit of quantification (LOQ) were 1.8 and 2.2 µg/L, respectively for an injection volume of 3 µL. Lower LOQs can be achieved by increasing the injection volume, making the method applicable even in the first hours and days of treatment. The bias of the method was less than 10% and the relative standard deviation of reproducibility was less than 15%. The sample stabilization was robust and the uncertainty associated with the method was acceptable. The method was applied to a real sample taken after a few years of treatment and a concentration of 0.15 mg/L was measured.

New Design of A Micro-Hydro Power Plant (MHPP) System In The 3T Region As Al-ternative Solution Unit Turbine Using Computational Fluid Dynamics (CFD) Simulation

New Design of A Micro-Hydro Power Plant (MHPP) System In The 3T Region As Al-ternative Solution Unit Turbine Using Computational Fluid Dynamics (CFD) Simulation

Use of an Air Heating System at the Inlet to the Gas-Turbine Compressor as an Element of the Heat-Recovery System in a Combined-Cycle Power Plant

Use of an Air Heating System at the Inlet to the Gas-Turbine Compressor as an Element of the Heat-Recovery System in a Combined-Cycle Power Plant

A Numerical Investigation of Mixed Thermal Elastohydrodynamic Lubrication in Tilting-Pad Journal Bearing

Abstract The tilting-pad journal bearing in the cooling system of the nuclear power plant is equipped below the ground and vertically positioned to accomplish its function for water transfer. Usually, the loading conditions are relatively stable since the required water volume almost remains the same level during the operation, but the loading direction cannot be known in advance. Furthermore, the bearing is designed with several separate pads, which allows the bearing to support the loading flexibly. The safety application of nuclear energy requires the bearing to have a reliable ability to maintain the rotating motion of gear sets. This study develops a numerical model to simulate the mixed thermo-elastohydrodynamic lubrication for the tilting-pad journal bearing in the nuclear plant. The elastic and thermal fields are properly determined, and the induced displacement is taken into account for an accurate description of film thickness. The asperity contact due to misaligned journal is well evaluated in the local area where the lubrication film cannot separate the surfaces. A parametric study is undertaken in detail to reveal the aspects that influence bearing lubrication. The conclusions potentially provide fundamentals for further lubrication optimization of the bearing system.

Energy/freshwater sustainability in urban areas through a novel solar-driven system with H2 production/liquefaction: Techno-economic evaluation and multi-objective optimization

The application of solar-based power plants systems in cities offers various advantages. These include reducing reliance on fossil fuels, declining carbon emissions, and supporting efforts to address climate change. Additionally, solar energy enhances energy resilience, promotes economic growth, and generates employment opportunities through investments in solar infrastructure. The primary goal of the current investigation is to meet the daily energy requirements of environmentally friendly urban areas. The setup includes the utilization of various processes such as LNG regasification, parabolic trough solar collectors, dual-loop power cycles, reverse osmosis, and a unit for liquefaction and hydrogen production. The analysis shows that the evaluated plant generates a net output electricity of 1994 kW and has a levelized cost of electricity (LCOE) of 5.1 Cent/kWh. Furthermore, the system effectively caters to the water demand of 32.21 kg/s and cooling requirement of 392 kW for residential purposes. In addition, it exhibits the capability to generate hydrogen at a rate of 9.49 kg/h, which is subsequently stored in a liquid state. The study findings indicate that adjusting the pressure of the compressor has a substantial influence on liquefaction work. Initially, the work increases with increasing pressure, reaches a peak, and subsequently declines. It is crucial to maintain the recommended pressure level of approximately 5 MPa for optimal performance. This pressure level leads to an efficiency of 17.01% and a coefficient of performance (COP) of 0.16. According to the multi-objective optimization, the optimized system demonstrates a shorter payback period of 3.38 years compared to the baseline system's 4.03 years, despite having higher initial costs. Over a 20-year lifespan, the optimized system is more profitable, surpassing the baseline system by approximately $2.4 million.

SCADA implementation in microhydro power plant control and monitoring systems of screw turbine type

Screw turbine-type micro-hydro power plants are still controlled manually by humans when there is a change in the electrical load on the generator output. If there is a change in the electrical load, the generator output voltage will change, thus affecting the rotation of the turbine being used. In this case, humans are needed to manually regulate the flow of water entering the turbine to maintain the stability of the generator output voltage by controlling the sluice gate. The water discharge entering the screw turbine will rotate the generator through a belt/gearbox pulley transmission, thus producing an electrical voltage at the generator output. To maintain the stability of the generator output voltage, it is necessary to control the water discharge entering the screw turbine. The expected goal of this research is to design a control system for a screw turbine type microhydro power plant to stabilize the generator output voltage and monitor the output of a screw turbine type generator using a SCADA (Supervisory Control, and Data Aquisition) system. The method used is the research and development method, namely the system design stage based on secondary data that has been collected, where the system design includes hardware design and software design, followed by making hardware such as control panels and devices. Software, which includes display design and leader diagrams and testing, is carried out by testing the system on software, hardware, and overall system testing. From the results of the discussion and analysis, the screw turbine type microhydro power plant control design system was created, a load control system consisting of 6 groups and sluice gate opening control that uses an ultrasonic sensor to determine the water level. With the results of controlling the sluice gate at a door opening of 30 mm, the generator voltage is 18.42 Volts DC, DC current is 0.0 Ampere at a load of 0 watts, when the load is 30 watts the generator voltage decreases by 18.40 volts, current is 1.37 Ampere. Through the on-line monitoring system, electrical parameters are obtained which are displayed on the SCADA system by looking in real-time at the history of DC voltage and DC current, DC power, and DC energy generated by the screw turbine-type DC generator. The voltage read is 18. 57 volts, current 1.37 Amperes, DC electrical power is 25.4 watts with a DC light load of 30 watts.

Computational fluid dynamics numerical simulation of flue gas emission from stack and tower integration system of coal-fired power plant

ABSTRACT The method of Computational Fluid Dynamics (CFD) simulation has been extensively employed in the stack and tower integration technology (STIT) research; however, a significant number of studies overlooked the impact of thermal buoyancy on the external flow field of cooling tower. In light of this, an improved approach is proposed in this study. A model of a cooling tower and its surrounding flow field was established, and its reliability was confirmed too. Based on our model, the performance of three enhancement strategies under various crosswind speeds and ambient temperatures was simulated. The results indicate that all three enhancement strategies can effectively simulate the effects of thermal buoyancy. In the simulations, the elevation of the flue gases increased from 306 m to either 426 m or 476 m. In the present study, ambient conditions characterized by crosswind speeds below 4 m/s and temperatures below 297.15 K were deemed suitable for the dispersion of stack and tower integration (STI) flue gases. A power function distribution was identified between crosswind speed and the mean height of the plume, while a linear relationship was observed between ambient temperature and the mean height of the plume.

Chaos-infused wind power integration in the grey wolf optimal paradigm for combine thermal-wind power plant systems

This research presents a novel methodology for tackling the combined thermal-wind economic load dispatch (ELD) issue in contemporary power system. The proposed approach involves hybridizing active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) into grey wolf optimization (GWO) algorithm, while effectively incorporating the intricacies associated with renewable energy sources (RES). A more accurate model is made possible by hybridization for complex systems with memory and hereditary characteristics. The GWO is used as a tool for global search while ASA, IPA and SQP methods are used for rapid local optimization mechanism. The performance evaluation of the design heuristics is carried out on 37 thermal and 3 wind power generating units and outcomes endorse the effectiveness of the proposed scheme over state-of-the-art counterparts. The worthy performance is further validated on statistical assessments in case of thermal-wind integrated ELD problem in terms of measure of central tendency and variation on cost and complexity indices.

Modified Evaporation Model for ATHLET System Code in a Passive Containment Cooling System for Nuclear Safety

The presented work deals with the improvement of the evaporation model of the ATHLET (Analysis of Thermal and Hydraulics of Leaks and Transients) system code to be applied to a passive containment cooling system of a nuclear power plant. For the model validation, INTRAVIT (Investigation of Passive Heat Transfer in a Variably Inclined Tube) test facility setup at the University of Luxembourg was used. The first part of the paper presents a review of the existing literature on evaporation models that revealed that those models significantly simplify the physical processes that occur. Next, a modified evaporation model is proposed that offers a realistic description of various evaporation processes and the start of bubble formation using a nucleation model, and a surface density calculation model is introduced that is necessary for evaporation simulation. The final part of this work explored five different system configurations to test the evaporation model: three condenser tube inclinations (5 deg, 60 deg, and 90 deg), two riser lengths (1 m and 2.5 m), and different thermal loads. They made it possible to simulate several experiments for stable and unstable natural circulation and to verify the proposed model.

An optimal standalone wind-photovoltaic power plant system for green hydrogen generation: Case study for hydrogen refueling station

Sustainability goals include the utilization of renewable energy resources to supply the energy needs in addition to wastewater treatment to satisfy the water demand. Moreover, hydrogen has become a promising energy carrier and green fuel to decarbonize the industrial and transportation sectors. In this context, this research investigates a wind-photovoltaic power plant to produce green hydrogen for hydrogen refueling station and to operate an electrocoagulation water treatment unit in Ostrava, Czech Republic's northeast region. The study conducts a techno-economic analysis through HOMER Pro® software for optimal sizing of the power station components and to investigate the economic indices of the plant. The power station employs photovoltaic panels and wind turbines to supply the required electricity for electrolyzers and electrocoagulation reactors. As an off-grid system, lead acid batteries are utilized to store the surplus electricity. Wind speed and solar irradiation are the key role site dependent parameters that determine the cost of hydrogen, electricity, and wastewater treatment. The simulated model considers the capital, operating, and replacement costs for system components. In the proposed system, 240 kg of hydrogen as well as 720 kWh electrical energy are daily required for the hydrogen refueling station and the electrocoagulation unit, respectively. Accordingly, the power station annually generates 6,997,990 kWh of electrical energy in addition to 85595 kg of green hydrogen. Based on the economic analysis, the project's NPC is determined to be €5.49 M and the levelized cost of Hydrogen (LCH) is 2.89 €/kg excluding compressor unit costs. This value proves the effectiveness of this power system, which encourages the utilization of green hydrogen for fuel-cell electric vehicles (FCVs). Furthermore, emerging electrocoagulation studies produce hydrogen through wastewater treatment, increasing hydrogen production and lowering LCH. Therefore, this study is able to provide practicable methodology support for optimal sizing of the power station components, which is beneficial for industrialization and economic development as well as transition toward sustainability and autonomous energy systems.

Physics-informed deep learning and linear programming for efficient optimization of combined cycle power plants

Efficient operation of combined cycle power plants (CCPP) involves solving mixed-integer nonlinear optimization problems, constrained by thermodynamic differential equations, thermal constraints, and temporal dependencies between variables. The optimization problem aims to maximize profit for day-ahead operation by minimizing short-term and long-term costs, and accounting for volatility in ambient conditions and energy price. In operational terms, the challenge lies in developing an efficient and robust optimization algorithm capable of determining optimal values for thousands of temporal variables. It must also have the capacity to evaluate a multitude of scenarios encompassing various weather and market conditions. To address this challenge, this paper proposes a hybrid optimizer that utilizes deep learning models trained on historical operational data of a real CCPP, along with a surrogate physics-driven piecewise-linear model of CCPP, to determine the optimal values of thousands of control setpoints, with strong temporal co-dependencies, within a two-minute runtime required by industry constraints. A multi-resolution architecture is proposed to efficiently implement this optimizer. The algorithm sequentially solves the problem in coarse and fine resolutions to accelerate convergence. Final results are checked for feasibility using pre-trained deep learning models, ensuring accuracy and validity. The study shows that the proposed model provides comparable results to the exact solution while reducing computational costs, up to 95%. This research has practical implications for power plant system operators, as well as traders and dispatchers, enabling them to make optimal decisions for day-ahead contracting purposes and CCPP operation in a reasonable time, ultimately leading to more efficient and cost-effective power plant management. Furthermore, the methodology introduced in this work could potentially be extended to other industrial applications that require large-scale, complex optimizations, where the precise governing principles of a process can be approximated by piecewise-linear functions.

Multi-unit PSA based risk evaluation framework for utilizing cross-tie systems for nuclear power plants

The Fukushima accident showed that the safety of multiple nuclear power plants (NPPs) at the same site could be jeopardized simultaneously. Since then, many studies have focused on developing strategies to prevent the spread of multi-unit accidents, with numerous countries establishing strategies to use mobile equipment. However, mobile equipment strategies are inherently accompanied by a high degree of uncertainty regarding operation success and duration because multiple organizations and personnel interact in various ways during multi-unit accident situations. Furthermore, supplementing current fixed equipment with additional mobile equipment requires extra resources. Therefore, cross-tie strategies that use currently installed fixed equipment can provide additional means to manage site risk with relatively few additional costs. This study proposes a multi-unit probabilistic safety assessment–based risk evaluation framework for utilizing cross-tie systems in NPPs and a modeling methodology to quantify the effectiveness of the cross-tie strategies. A case study was conducted to evaluate the risk reduction from using cross-tie strategies for emergency diesel generators and alternate AC diesel generators, which are power systems utilized in multi-unit loss of offsite power initiating events. It is expected that the developed framework and methodology can be utilized for other types of cross-tie strategies as well.

A Fault Diagnosis Method for Rectifier-Filter Circuit Integrating EEMD Algorithm and Transformer Network

Rectifier-filter circuit, as a critical component of the drive circuit in instrumentation and control systems of nuclear power plants, can convert the 50 Hz AC into the smooth DC. Thus, it plays a vital role in the power control of reactors. However, the weak waveform anomalies of soft faults in the rectifier-filter circuit make fault feature extraction difficult. Therefore, in this article, an ensemble empirical modal decomposition (EEMD) algorithm is employed to decompose the signal mode components in the monitor data of the rectifier-filter circuit. The weak waveform anomalies are indirectly enhanced by the IMF and residual components. Subsequently, the Transformer network is utilized to construct the feature extractor. With the advantage of multi-head attention (MHA) mechanism in the Transformer network, the multi-directional, multi-scale, and highly sensitive long-range time-dependent features in the EEMD feature data are extracted. Then, a deep Softmax classifier is adopted to reduce the dimensionality and diagnose the soft faults of the rectifier-filter circuit. Finally, a fault simulation model of the rectifier-filter circuit is constructed and the condition monitor data are collected. The effectiveness and diagnosis accuracy of the proposed method are verified by a real case experiment and some comparative methods.

Water, energy and environment nexus: Quantitative assessment for integrated power plants with renewable energy

The population increase and the demand for water and energy, accompanied by the implications of environment pollution for natural and human resources, indicate the critical necessity for a coherent movement towards nexus between water, energy, and environment. Due to the fact that power generation industry is responsible for a significant proportion of water and fuel consumption and Carbon dioxide emissions within the world, in this research, the application of the hybrid renewable system in a thermal power plant has been assessed based on the approach of analyzing the link between energy, water and environment. The design of the solar system and the assessment of carbon balance during the power plant lifetime have been conducted in PVsyst application in 2022. Moreover, ReCipe environmental model has been used for assessing the effect of decrease in carbon emission on the ecosystem. The findings of the research indicate that the replacement of at least 2 % of the nominal capacity of the fossil fuel power plant with the renewable one, prevents the emission of 1431.28 tons of carbon dioxide yearly. This amount equals to 380.34 cubic meters of reserve in fossil fuel consumption and 391.73 tons of crude oil. The results also showed that in addition to preserving natural resources, the hybrid cycle design leads to significant water demand reduction which equals to 3842 cubic meters with the capacity to supply underground water sources. Due to the interests of preserving water and energy resources and decreasing carbon emission in power plant industry, within the framework of nexus approach, management of energy supply by replacing resources and using water and heat recovery technologies and application of energy demand management policies based on energy efficiency and environmental implications is recommended.

Power plant systems performance assessment with applications of combined pinch and exergy analysis

Steam power plants forms an effective share of global electricity production. Thus, improving such plants performance is crucial to minimize its environmental effects and to enhance operational economy. Al-Mosyab thermal power station in Iraq is considered as a case study of this paper, with an objective of achieving best system performance. A combined pinch & exergy analysis (CPEA) is conducted under actual operating conditions. Further analytical attempt is varying pressure (165, 175, 185) bar, and temperature (450, 550, 620) °C at selected cycle location. Examining thereby the impact of each variable on the system power output, exergy destruction and 2nd low efficiency. The Engineering Equation Solving program (EES) is used for the simulation of each system components under these various operating conditions. The yielded results showed that the maximum mechanical & thermal output are (36.75 & 94.88) % of fuel energy respectively, while, turbine, boiler and condenser irreversibility and 2nd law efficiency are (157.76, 1086.18, 303.19) kJ/kg) and (88.36, 68.97, 28.68) % respectively. The analytical part of the analysis however showed that the high-pressure turbine network output increases by about (1%) with pressure variation, while such increase rise up to (70%) with temperature variation. Final concluded results predicted that best performance could be obtained at maximum pressure and temperature of (175) bar and (620) °C respectively.

Analysis of virtual power plants participating in the optimization operation of the electricity-carbon joint market based on the EEMD–IBA–Markov chain

To enhance the utilization of clean energy sources, such as wind power and photovoltaic within virtual power plants, and mitigate carbon emissions, this paper proposes a virtual power plant participation in the electricity carbon joint market optimization operation model based on ensemble empirical mode decomposition–improved bat algorithm (IBA)–Markov chain new energy output prediction. First, complementary set empirical mode decomposition is performed on historical data to construct a Markov chain based wind power and photovoltaic prediction model optimized by IBA. Second, this prediction model is used to predict the daily generation power of wind power and photovoltaic power. Finally, with the optimization goals of maximizing the benefits and minimizing the carbon costs of virtual power plants, a virtual power plant system participating in the electricity carbon joint market model based on wind power and photovoltaic output prediction results is constructed. At the same time, demand response factors are introduced and solved using the NSGA-II algorithm. Taking a certain park as an example for simulation analysis, the research results show that the combined effect of carbon market and demand response can achieve 99.82% of new energy consumption in virtual power plants without significantly reducing profits, basically achieving complete new energy consumption, demonstrating the effectiveness of the proposed model in this paper.

An abrupt regime shift of bacterioplankton community from weak to strong thermal pollution in a subtropical bay.

Thermal pollution from the cooling system of the nuclear power plants greatly changes the environmental and the ecological conditions of the receiving marine water body, but we know little about their impact on the steady-state transition of marine bacterioplankton communities. In this study, we used high-throughput sequencing based on the 16S rRNA gene to investigate the impact of the thermal pollution on the bacterioplankton communities in a subtropical bay (the Daya Bay). We observed that thermal pollution from the cooling system of the nuclear power plant caused a pronounced thermal gradient ranging from 19.6°C to 24.12°C over the whole Daya Bay. A temperature difference of 4.5°C between the northern and southern parts of the bay led to a regime shift in the bacterioplankton community structure. In the three typical scenarios of regime shifts, the steady-state transition of bacterioplankton community structure in response to temperature increasing was more likely consistent with an abrupt regime shift rather than a smooth regime or a discontinuous regime model. Water temperature was a decisive factor on the regime shift of bacterioplankton community structure. High temperature significantly decreased bacterioplankton diversity and shifted its community compositions. Cyanobium and Synechococcus of Cyanobacteria, NS5 marine group of Bacteroidota, and Vibrio of Gammaproteobacteria were found that favored high temperature environments. Furthermore, the increased water temperature significantly altered the community assembly of bacterioplankton in Daya Bay, with a substantial decrease in the proportion of drift and others, and a marked increase in the proportion of homogeneous selection. In summary, we proposed that seawater temperature increasing induced by the thermal pollution resulted in an abrupt regime shift of bacterioplankton community in winter subtropical bay. Our research might broad our understanding of marine microbial ecology under future conditions of global warming.

Solar Power Generation System at Household Scale

Solar power plants are renewable energy systems that utilize sunlight as a power source to generate electricity. The conversion of light energy into electrical energy is achieved through the photovoltaic effect. The process of converting solar energy into electrical energy is made possible by photovoltaic solar panels, which convert solar light energy into electricity. This technology began to be widely known and began to be widely used. Its use is widespread, ranging from large factories, office buildings, commercial buildings, shopping centers, hospitals, hotels, and households The purpose of this study is to know and analyze household-scale solar power generation systems. The method used in this study is a literature review, data used in the form of articles in electronic databases such as Google Scholar, in the period 2006 to 2023. The results showed that solar power plants (PLTS) are the right choice to overcome the energy crisis in Indonesia. Solar Power Plant Energy (PLTS) is abundant sunlight. Solar Power Plant System (PLTS) at the household level using Solar Home System (SHS) which is increasingly adopted in Indonesia (especially in households). The implication in this study is to provide a deeper understanding of household-scale solar systems, including the associated advantages and challenges. This can help individuals, institutions, and governments make better decisions regarding the use of renewable energy.

Fourier series-based modelling of the effects of thermal coupling on the transient dynamics of component loops in a coupled natural circulation loop

Energy efficiency in process industry and passive safety systems in nuclear power plants necessitate the use of buoyancy driven heat exchangers. The current study presents a 1-D numerical model of the buoyancy driven fluid system in a Coupled Natural Circulation Loop (CNCL) comprising water as the working fluid. In this study water at different temperatures is considered as the operating fluid in each of the loops. The study employs a 1-D model derived using a semi-analytical Fourier series. A validation study was carried out using the relevant literature to verify the mathematical model. A detailed parametric study on individual NCLs and their coupled system was conducted by varying the cross-sectional area keeping the other parameters constant to gain insights into the effect of thermal coupling on the long-term transient dynamics of each of the individual loops of the CNCL system, for stable, unstable – periodic, and unstable – chaotic conditions. The dynamics were analysed using the difference between transient buoyancy and viscous forces, and it was found that the overall heat transfer coefficient influences the coupling behaviour and the dynamics of the component loops in a CNCL. At lower values of the overall heat transfer coefficient, the component loops in the CNCL nearly retain their independent behaviour, i.e., the component loops hardly influence each other. It was also found that the temperature dependent fluid properties influence the stability of the CNCL system in some cases.

Numerical Investigation of Butterfly Valve Performance in Variable Valve Sizes, Positions and Flow Regimes

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario.