Power Plant Applications Research Articles

Effect of non-clustering element C and Mo on irradiation-induced clustering in reactor pressure vessel steels

Commercial reactor pressure vessel steels in nuclear power plant applications contain C and other minor non-clustering elements in addition to the clustering elements of Mn, Ni and Si. However, the effect of such non-clustering elements on irradiation-induced solute clustering in ferritic steels has seldom been addressed. Herein, we reveal that a commercial RPV steel and its Fe-Mn-Ni-Si model alloy with coarse/fine grains subjected to ion irradiation exhibits different irradiation-induced clustering, particularly in chemistry, mean size, and number density of irradiation-induced MnNiSi-clusters. The different chemical compositions of the clusters indicate different thermodynamics in driving solute clustering in RPV steel and its model alloy. The different number density and size evolutions of the clusters indicate different kinetics in governing irradiation-induced clustering. The presence of C and Mo, as non-clustering elements, is primarily responsible for the different clustering behaviors of Ni, Mn and Si in the two materials exposed to ion irradiation. The research finding is of significant implication for modelling and fundamental understanding irradiation-induced clustering in commercial RPV steels.

Hybrid power plant using synchronization controller system to save electricity cost

The application of hybrid energy power plants is one solution to save electricity cost in buildings of government agencies, industries, and universities. The problem with using hybrid power plants that use solar energy sources and paid electricity networks is that sunlight energy cannot produce energy consistently from sunrise to sunset. Maximum energy can only be obtained when the sun is vertically acceptable to the photovoltaic (PV). This results in electrical loads having to be disconnected or switched back to the grid. The application of an electrical power sharing system synchronization controller system (SCS) can automatically regulate the use of electrical energy to low PV energy. The results of research on the application of hybrid PV using the SCS system with a rooftop solar panel system at the Gorontalo State University Building can produce a total electrical power of 600,975 kWh. The need for electrical power from January to September 2022 amounted to 859,151 kWh. The SCS hybrid power plant can reduce the use of paid electrical energy and its costs by 83.60%. The investment, operational, and maintenance cost requirement is IDR 10,747,886,801. The return on investment (ROI) analysis results show that the return on investment can be achieved for up to 34 years.

Advancements and environmental considerations in portland cement-based radiation shielding concrete: Materials, properties, and applications in nuclear power plants– review

Radiation Shielding Concrete plays a critical role in safeguarding against ionizing radiation, in nuclear power plants, medical facilities, and other radiation-sensitive environments. This review paper presents a comprehensive examination of radiation shielding concrete development, highlighting a novel approach that incorporates a diverse range of natural and industrial materials. Traditional radiation shielding concrete formulations rely heavily on virgin materials, contributing to environmental degradation and resource depletion. In contrast, this paper explores the innovative use of natural materials, industrial by-products, and waste materials, emphasizing the environmental sustainability and resource efficiency of such approaches. By harnessing these alternative materials, the paper outlines how radiation shielding concrete production can significantly reduce its ecological footprint while maintaining or even enhancing its radiation shielding capabilities. The paper delves into the functional aspects, composition variations, and performance characteristics of radiation shielding concrete, providing a holistic perspective on the diverse materials employed. Additionally, it thoroughly examines the factors influencing the effectiveness of radiation shielding concrete in nuclear power plants. Furthermore, this review discusses recent developments and advancements in radiation shielding concrete, offering insights into the cutting-edge research and innovations that are shaping the future of radiation shielding. The integration of natural and industrial materials presents promising avenues for enhancing the versatility, cost-effectiveness, and sustainability of radiation shielding concrete.

Nonlinear Model Predictive Control for Doubly Fed Induction Generator with Uncertainties

Doubly fed induction generators (DFIG) find extensive application in variable-speed wind power plants, providing notable advantages such as cost-effectiveness, operational flexibility across varying speeds, and enhanced power quality. This research focuses on the control of DFIGs employed in variable-speed wind turbine configurations. A suitable mathematical model is chosen for representative systems following a comprehensive review of contemporary research. Subsequent analysis reveals the instability of the open-loop time response of the system. To address this instability, the initial approach involves the implementation of the conventional model predictive controller (MPC). However, the outcomes indicate that this controller falls short of delivering satisfactory performance despite the enhanced stability. In the subsequent phase, efforts are made to mitigate the impact of wind input variability by utilizing the Kalman filter, given its effectiveness in handling high variability. Following this, a novel methodology is introduced, which combines nonlinear MPC with the Lyapunov function. This method is based on the nonlinear model of the system. By using the Lyapunov function in the nonlinear MPC structure, the stability of the designed controller is guaranteed. To validate the proposed control approach, the results are compared with PID based controller in MATLAB/Simulink. The simulation results showed that the output variables of the modeled DFIG system achieve stability within a reasonable timeframe applying the input.

GIS-AHP APPROACH FOR A COMPREHENSIVE FRAMEWORK TO DETERMINE THE SUITABLE REGIONS FOR GEOTHERMAL POWER PLANTS IN IZMIR, TÜRKİYE

Geothermal energy is gaining more reputation and importance around the world. Correspondingly, suitable location selection is a critical step and has become necessary for the successful installation and operation of geothermal power plants. This study investigated suitability of İzmir region, located in the Aegean part of Türkiye, in terms of geothermal power plants applications by using the combination of Geographical Information System and Analytic Hierarchy Process. Based on the request of power plants, thirteen important criteria were evaluated under three main categories named as physical (C1), environmental (C2) and technical (C3). Moreover, expert’s opinions were taken into consideration to calculate the importance of these criteria. Key results showed that İzmir was suitable for geothermal power plants. The final suitability map layer pointed out that %8.73 (1.037 km2) of total area were determined as highly suitable regions in terms of installation. In addition, the obtained suitability map layer was compared with actual geothermal power plants. Based on the comparison study, power plants in Seferihisar were moderately suitable for geothermal power plants while the location of Balçova power plant was highly suitable. Regarding the suitability assessment in the present study, the location of Dikili power plants had the least suitability score.

Pyrolysis characteristics and kinetics of waste photovoltaic module: A TG-MS-FTIR study

The emerging application of solar power plants has led to serious waste photovoltaic module disposal problems. To address the environmental concerns associated with waste photovoltaic module disposal, this study investigates pyrolysis as a promising treatment technology and a fundamental step for various thermal chemical processes. The kinetic characteristics and pyrolysis products of ethylene vinyl acetate (EVA), Tedlar-Polyethylene Terephalate-Tedlar (TPT), and silica gel were studied using TG-FTIR-MS. The weight loss stages of EVA, TPT, and silica gel were between 300 and 510 °C, 330–520 °C, and 100–830 °C, respectively, with a total weight loss rate of 99–100%, 73–76%, and 60–62%. The reactions they experienced were acetic acid production and long chain fracture, long chain fracture and fluorocarbon compound production, polymer methyl vibration, [(CH3)2SiO] cyclic compound production, Si–C bond fracture, and CO2 production, respectively. According to the results of the two kinetic models, their average activation energies were 278-281 kJ/mol, 330-336 kJ/mol, and 187-193 kJ/mol. The products released during the pyrolysis process of the three samples were different. Among them, olefins and aromatic hydrocarbons from EVA and TPT could be used to synthesize high-molecular-weight substances. Aldehydes, fats, and esters from TPT could be used to synthesize drugs and daily necessities; hydrofluoric acid and furan were harmful to human health and the environment. Hexamethylcyclotrisiloxane and octamethylcyclotetrasiloxane from silica gel could be used to synthesize silicone polymers. The content of volatile substances during pyrolysis was related to the heating rate. The findings are expected to contribute to the development of waste photovoltaic module disposal and resource recovery through pyrolysis.

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

In this study, response surface methodology (RSM) was employed to optimize the welding parameters’ effects on mechanical properties of dissimilar welds between Cr-Mo steel grade (P11) and austenitic stainless steel (AISI 316LN). To determine the best welding parameters, variance analysis (ANOVA), desirability function, and perturbation analysis were used to create regression models and identify the significant parameters influencing tensile strength and hardness gaps in the weld joints. The results indicated that welding speed is the most significant parameter affecting both the austenitic hardness gap and tensile strength, while gas flow has the most significant impact on the hardness gap of Cr-Mo steel. Furthermore, welding speed positively influences the mechanical properties of dissimilar weld, whereas welding current has a slight negative effect on tensile strength. The optimum welding parameters were found to be 130 A for welding current, 70 mm min−1 for welding speed, and 13 l min−1 for welding gas flow, resulting in hardness gap values of 18.10 HV (Stainless steel side), 27.38 HV (Cr-Mo steel side), and a tensile strength of 453.90 MPa. The optimum parameter effect is concentrated at the weld interfaces between the fusion zone and the heat-affected zone. This effect led to limitations in grain coarsening, a reduction in the martensite and delta ferrite phase percentages, a slight increase in the bainite ratio, and a decrease in carbide precipitations. As a result, a homogenization of strain distribution in the optimum weld was achieved, leading to ductile fracture in Cr-Mo steel.

Thermal transport analysis in hydromagnetic fluid-particle suspension model under the effect of slip boundary conditions and electric field: Applications in solar power plant

Thermal transport analysis in hydromagnetic fluid-particle suspension model under the effect of slip boundary conditions and electric field: Applications in solar power plant

Feasibility Study on the Application of Boron Carbide for Long Term Reactivity Control in the LOTUS Small Fast Reactor

Abstract 200 MWth lead-cooled fast reactor (LOTUS) reactor core is a small modular lead-cooled fast reactor with designed power of 200 MWth under development at Vietnam National University (VNU) University of Science, Hanoi for a floating nuclear power plant application. For that purpose, advanced passive safety features and no refueling requirement are the priorities in the core design process. To endure the continuous operation over a long lifetime, the startup core exhibits excess reactivity to cover the reactivity loss due to burnup. The reactivity control system includes burnable poison and absorber rods and layers made of B4C which are employed in the reactor to minimize the excess reactivity of the core to about 1 $ to enhance the safety features of the core. The burnable poison is fixed inside the reactor while absorber rods/absorber layers are withdrawn or inserted in sequence to achieve the required excess reactivity of about 700 pcm. The reactivity control was arranged into ten steps to achieve the operating time of 15 effective full-power years without refueling. Good neutronic behavior of the core was observed with negative fuel temperature coefficient and coolant void reactivity and maximum radial power peaking factor of 1.32. However, a quite large residual absorption caused by fixed burnable poison inside fuel assemblies was revealed. In further study, to increase the neutron absorption efficiency of burnable poison in the fast spectrum as well as the reactor lifetime, a neutron moderator will be considered to add to the burnable poison rods.

Microstructure and Oxidation Behavior of C‐HRA‐5 Austenitic Heat‐Resistant Steel in Air at the Temperature Range of 650–750 °C

This study investigates the oxidation behavior and microstructure characterization of C‐HRA‐5 (i.e., a new austenitic heat‐resistant steel) in the air at temperatures ranging from 650 to 750 °C over a 1000‐hour duration. The oxidation behavior and mechanism are analyzed using gravimetric evaluation, thermodynamic analysis, microscopic morphology, and microstructure characterization. The results indicate that the oxidation behavior follows a parabolic law at each temperature. With increasing temperature, the oxide film gradually grows and transforms from small lump particles to strips and needles, eventually covering the entire substrate surface over time. Moreover, long‐term oxidation exposure promotes the formation of various phases, including M23C6, σ, MX, Z, nanosized Cu‐rich, and Laves phases, within the metallic substrate. Considering potential applications in new‐generation power plants, this study provides a solid foundation to disclose the possible oxidation of C‐HRA‐5 austenitic heat‐resistant steel at high temperatures.

Event diagnosis method for a nuclear power plant using meta-learning

Artificial intelligence (AI) techniques are now being considered in the nuclear field, but application faces with the lack of actual plant data. For this reason, most previous studies on AI applications in nuclear power plants (NPPs) have relied on simulators or thermal-hydraulic codes to mimic the plants. However, it remains uncertain whether an AI model trained using a simulator can properly work in an actual NPP. To address this issue, this study suggests the use of metadata, which can give information about parameter trends. Referred to here as robust AI, this concept started with the idea that although the absolute value of a plant parameter differs between a simulator and actual NPP, the parameter trend is identical under the same scenario. Based on the proposed robust AI, this study designs an event diagnosis algorithm to classify abnormal and emergency scenarios in NPPs using prototypical learning. The algorithm was trained using a simulator referencing a Westinghouse 990 MWe reactor and then tested in different environments in Advanced Power Reactor 1400 MWe simulators. The algorithm demonstrated robustness with 100 % diagnostic accuracy (117 out of 117 scenarios). This indicates the potential of the robust AI–based algorithm to be used in actual plants.

Constant Voltage Model of SCIG-Based Variable Speed Wind Power Plant for Load Flow Analysis

In recent years, the application of variable-speed wind power plants (WPPs) has become more and more popular and surpassed fixed-speed WPPs. This popularity is mainly because variable-speed WPPs are much more efficient in capturing or extracting wind energy than fixed-speed WPPs. Due to its relatively cheaper cost, the use of SCIG (Squirrel Cage Induction Generator)-based variable-speed WPP is currently increasing. This type of WPP is usually equipped with a power electronics converter to obtain a broader range of variable-speed operations. Modeling the power system components is undoubtedly necessary for performing the system analysis (including load flow analysis). This paper discusses the steady-state model of SCIG-based variable-speed WPP for load flow analysis of electric power distribution systems. The proposed model can be used for SCIG-based variable-speed WPP with voltage control operating mode. The model was developed based on formulas that calculate the turbine mechanical power input and the WPP electrical power output. This paper also presents a case study in which the proposed model is applied to a representative electric power distribution system.

Hollow microbeads modified with MoS2 for enhanced removal of mercury from coal-fired flue gas

Hollow microbeads, derived from fly ash emitted by power plants, are hollow microbeads composed of various compounds including SiO2 and Al2O3. These microspheres exhibit a high specific surface area and stable chemical properties. In this work, HM-MoS2 was synthesized through a two-step hydrothermal method to address the issues of low adsorption efficiency and high operational costs associated with the utilization of hollow microbeads in actual power plant applications. The experiments demonstrated that under simulated power plant flue gas conditions, the adsorption efficiency of HM-15 for elemental mercury (Hg0) exceeded 96%. Additionally, HM-15 displayed resistance to SO2 and NO gases, indicating its potential as a mercury adsorbent material with promising industrial applications.

PV System Installation Assessment Based on Power Measurement for Balcony Power Plant Applications

PV System Installation Assessment Based on Power Measurement for Balcony Power Plant Applications

A cascaded thermochemical energy storage system enabling performance enhancement of concentrated solar power plants

Calcium looping (CaL) thermochemical energy storage (TCES) exhibits promising potential for application in concentrated solar power (CSP) plants. However, the CSP-CaL integrating system encounters challenges related to elevated heat loss and diminished power generation efficiency. Herein, for the sake of a more rational heat management and enhanced energy utilization, we propose a cascaded energy storage and utilization strategy. Accordingly, a cascaded TCES system model consisting of Calcium looping and Magnesium looping (MgL)-MgCO3/MgO thermochemical cycle subsystem is developed. The energy analysis and exergy analysis results show that the solar power efficiency and exergy efficiency of the considered system are 41.7% of 44.7%, which are 2.6% and 2.8% higher than the single CaL energy storage CSP system, respectively, demonstrating the superiority of the proposed strategy and system for CSP application. Furthermore, the operation strategy of the system under off-design conditions is proposed by considering the real solar irradiation, and the yearly overall solar power efficiency is 39.2%. The economic analysis of the proposed system indicates that the levelized cost of electricity ranges from 179–156 $/MWh for different plant sizes and is superior in large-scale CSP plants. The cascaded energy storage and utilization strategy of thermochemical cycles with different working temperatures provides better dispatchability to meet the different thermal energy demands.

Assessing the effectiveness of a PV power plant and its subfields in Algeria: Case study Tamanrasset

In order to offer comprehensive and long-lasting answers to problems connected to the preservation of fossil fuel energy supplies and environmental challenges, Algeria has placed a focus on green energy sources. Her capacity for renewable energy sources is considerable. The installation of several PV power plants across the entire country's surface area shows that Algeria's national RE program is increasingly concentrating on solar energy, specifically photovoltaic applications. The aim of this work is to create a calculation code with a graphical interface called PVPA-1 which has the following objectives: quickly and easily analyze the performance of photovoltaic installations (the entire PV power plant and all these subfields) in accordance with IEC 61724 standards using data collected from these installations; to chart the yearly, monthly, and daily trends of performance parameters; and to compare the performance of these subfields to control and identify any irregularities in this system. This study presents a case study of a 15 MW photovoltaic power plant application (Tamanrasset, Algeria) for the year 2018. The results show that the PVPA-1 is a very powerful tool for analyzing PV power plant and these subfields performance. The reference, array and final yields were 6 h, 4.63 h and 4.58 h, respectively. Low system losses (0.052 h) are a result of the significant inverter efficiency (98.88 %). Similar to that seen in literature, the annual performance ratio is around 77.5 %. The PVP-1 allows users to compare the performance of all the subfields. As a result, the 9 th subfield displays peculiar behavior when compared to the other subfields, which has an impact on the overall PV power plant's performance.

Identifying fouling mechanism in a novel hybrid cooling tower's bundles: Application in concentrated solar power (CSP) plant

In this paper, structural, chemical, and thermos-physical characteristics of fouling and tube materials for hybrid cooling tower bundles in Concentrated Solar Power (CSP) facilities are addressed. Toward an in-depth understanding and a comparison of the fouling mechanism on galvanized steel and polymer tubes, results obtained from the characterization studies and the experimental test correlations were used to calculate the sticking probability (P) and deposit bond strength (ξ) based on the Kern-Seaton model. According to the data, the polymer tube had three times higher the adhering probability of the galvanized steel tube with a value of PPf = 3.15*102 Ns/m2, whereas the deposit bond strength was two times lower with a value of ξPf = 3.49*10−8. The results revealed that when it comes to polymer tubes, the ones with a finer surface structure tend to attract foulants from deluge water more readily. However, once foulants are attached to the heat transfer surface, it's simpler to be removed. The substantial increase in kaolinite and gypsum phases can explain this occurrence. On the other hand, galvanized tubes, exhibit the opposite behavior. It is anticipated that this constructive study will shed light on performance-enhancing fouling mechanisms and offer a scientific basis for thermal engineers.

A Numerical Algorithm for Calculating Critical Points and Its Application to Predictive Mixture Models and Binary CO_2 Mixtures

The use of supercritical fluids in technical applications requires an accurate knowledge of their critical points. For mixtures, these can deviate significantly and without a linear dependency from the critical points of its individual pure components. Since even small amounts of admixture can have noticeable effects, this not only concerns blends of targeted compositions, but also unintentional mixtures for example caused by impurities. Within this work, a method for the calculation of critical points is presented which focuses on numerical robustness promoting a fast and reliable generation of results. Implemented into the thermodynamic property software TREND, with its mixture modeling capabilities, the method allows a flexible combination of different equations of state and mixture models which also includes predictive approaches. Against the background of an increasing relevance of mixtures based on supercritical CO_2 (sCO_2) for energy applications, critical lines are calculated and compared against experimental results for selected sCO_2-based mixtures recently considered for power plant applications. Herein, several combinations of equations of state (EoS) and mixture models are compared. Critical lines are calculated for the first time in this work with the combination of the multi-fluid mixture model with excess Gibbs energy (g^text {E}) models. It was found that the critical lines calculated with the combination of the multi-fluid mixture model with the g^text {E}-model COSMO-SAC yields good predictive results for the investigated CO_2 mixtures.

Investigation of heat transfer performance of double-walled pipes of heat exchanger for power plant applications

Heat transfer between contacting surfaces, is a key factor affecting the thermal performance of heat exchangers in power plants and other applications. Double-walled pipes, used in the heat exchangers, can significantly improve the safety factor of the system. In this research work, the thermal contact conductions (TCC) at the interfaces of double-walled stainless steel 316 L pipes under various contact pressures were investigated. These pipes were manufactured with the shrink-fitting method using servo-hydraulic universal testing machine. A numerical model, verified by X-ray diffraction analysis, was developed to investigate the contact pressure variation at the interfaces according to loading conditions. The contact pressure between the inner and outer walls was controlled in the range of 22.78 MPa to 25.70 MPa, by varying the tensile loading conditions. A phase-sensitive transient thermal method was developed to measure the thermal conductivity (TC) and TCC of double-walled pipes. TC was observed to be in the range of 15.13 W/mK to 15.84W/mK while TCC at the interface was observed to increase sharply with the contact pressure, reaching 17 × 103W/m2K under 25.70 MPa contact pressure.

Unsupervised Causal Deep Learning-Based Anomaly Detection in Nuclear Power Plant Applications

Nuclear power generation will be key to meeting carbon free energy transition goals. However, nuclear power must provide agility and flexibility to fluctuating power demands when other sources of carbon-free energy like solar and wind may not be as flexible. This has led to small modular reactor (SMR) development where nuclear power will be generated from a distributed fleet of smaller reactors where units can be brought online or offline as needed. Due to its high operational and maintenance (O&M) costs as it is, a distributed fleet will put additional cost burden if remote monitoring and crew sharing is not enabled. This requires prognostics and health management (PHM) capabilities such as early warning, diagnostics, and prognostics to enable predictive maintenance with high accuracy. Typically, monitoring solutions are developed on component and subsystem levels targeting specific failure modes. However, it is argued that a systemwide monitoring, in addition to specific targeted analytics, would be of key importance. This paper presents a deep-causal unsupervised anomaly detector that has been successfully applied in various aerospace and renewable energy applications. In this paper we share our experience applying this method on a nuclear power plant (NPP) application. Specifically, we share how we dealt with practical challenges of data quality, ground truth labeling, performance evaluation and field validation in an unknown-unknown setting where prior knowledge of failures and failure modes were not available to begin with.