Power Plant System Research Articles

Optimal control of a doubly fed induction generator of a wind turbine in cooperation with weak and rigid grids

In this article a control method for a rotor side converter (RSC) of a doubly fed induction generator of a wind turbine is developed. The doubly-fed induction generator (DFIG) system of a wind energy power plant that improves grid symmetrization was applied. The issue of optimal control was treated as an extended linear quadratic regulator (ELQR) having an extra set of exogenous inputs, which are source voltages of the electric grid. No additional knowledge of equations modelling the exogenous inputs was assumed. The proposed method is much more efficient than the currently available linear quadratic control methods. The control objective for a weak grid was to maintain the given value of the voltage module on load terminals and the given value of active power transferred from the stator’s winding. First harmonic components of relevant waveforms were used for this purpose. This task also required the DFIG system to provide reactive power to the grid. In the case of a rigid grid, this reactive power would be too high. Therefore, in this case, it was assumed that the system would supply only part of the required active and reactive power, based on its capabilities. It was required that the voltage and current ratings of the system, mainly the DFIG, were not exceeded. Therefore, the parameters of the network in these difficult failure cases were corrected only partially. The behaviour of the grid in the conditions of failure, as well as the return to the steady state after failure disappearance, were studied.

The effects of geometric factors on power generation performance in solar chimney power plants

This research aims to create an admissible source for specifying the relation between the plant's output power and specified geometrical parameters unique to each simulated chimney dimension. In the current study, the solar chimney output power has been studied considering 49 solar chimneys, including different collector diameters, chimney heights, and chimney diameters. The study employs the Ansys-CFX to simulate the numerical model for the unsteady k-ε turbulent flow for a vast number of geometries. The obtained results indicate that the velocity as the main factor in generating the output power has significantly improved by elevating the collector radius. The output power increased up to 50 % by elevating the collector radius and around 30 % by enhancing the chimney heights which cause an increase in airflow, temperature differentials. Moreover, increasing the chimney height has generally ascended the power plant system. Among all geometrical parameters, chimney radius had the least impact on solar chimney performance. The results indicate that the best ratio between collector radius and chimney height is 6 %–10 % to achieve the optimized output power. Our findings were verified with the available experimental setups.

Investigating different scenarios of integrating solar-assisted carbon capture with combined cycle power plant and water desalination system

In this work, an optimal algorithm-based integration of solar thermal energy with carbon capture and desalination processes were proposed. The stripper columns, identified as the most energy-consuming equipment, were designed with constant capacities to ensure practicality and applicability. Results show that, without affecting the power plant's efficiency, using a solvent tank as an energy storage system (scenario-2) increases total CO2 capture from 45 % to 98 % compared to a part-time solar power system (scenario-1). Utilizing two solvent tanks reduces waste energy from 87 % to 67 % (scenario-3), while achieving 100 % CO2 capture. Using three different stripper columns (scenario-4) lowers the levelized cost of energy by 20 %. Incorporating an additional multiple effect distillation system (scenario-5) reduces levelized cost of energy and energy loss by 26 % and 74 %, respectively. Approximately 28 % of the total solar energy collected (4.64 × 106 MWh) was used to capture 1.57 × 106 ton.year−1 of CO2. The remaining energy was used in desalination to produce 9.4 × 106 m³.year−1 of fresh water, increasing overall energy efficiency from 28 % to 81 %, and reducing waste energy to 0.88 × 106 MWh, just 26 % of previous scenarios' waste.

Use of logical-graphic methods of analysis of risks in the water supply systems of thermal power plants

Today's urgent issues in the water supply of thermal power plants are increasing the efficiency of production processes, reducing energy costs, introducing innovative technologies, as well as ensuring environmental safety and sustainable development. The analysis of the causes of industrial accidents and damages shows that the occurrence and development of accidents, as a rule, is characterized by a combination of random local events that occur with different frequency at different stages of the accident. Logical-graphic methods of fault trees and events are used to identify cause-and-effect relationships between these events. In order to investigate the identification and analysis of cause-and-effect relationships that contribute to the occurrence of failures in the water treatment system using a fault tree for the further development of effective measures to minimize risks and increase the reliability and safety of the water supply systems of thermal power plants, it is proposed to use logical-graphic methods on the previous stage of identification and assessment of technogenic risks. The analysis of the obtained results showed that: 1) the fault tree is an instantaneous display of the system at a certain moment in time t and is a graphical representation of the cause-and-effect relationships obtained as a result of identifying dangerous situations in the system in a forward and reverse order in order to find possible causes of their occurrence; 2) a complex final event should be determined using the so-called «tree top». The top of the tree consists of the final event and additional undesirable events, including potential accidents and dangerous conditions that are direct causes of the final event. The final event and additional events must be carefully defined and all the most important causes of the final event identified. Therefore, the first five heuristic rules must be used when building a rejection tree; 3) construction of a fault tree using heuristic rules can be used when considering any element of the system, however, to simplify cumbersome constructions, it is more appropriate to build trees only for the main elements that cause emergency situations and have a negative impact on people's lives and health, as well as on environment; 4) when building a fault trees for the technological scheme of water treatment, it is possible to specify and quantify events, to find events with a very high probability and a very low probability, to limit the further development of the fault trees and to establish the causes of failures at each stage of the water treatment process; 5) the rejection tree can be used for quantitative assessments using Markov models.

Design challenges and response plans for intelligent decision support systems for Korean nuclear power plants under normal and abnormal conditions

In nuclear power plants (NPPs), an intelligent decision support system (IDSS) aids the decision-making process of main control room operators. It achieves this by monitoring and diagnosing conditions, predicting progress, and providing preventive advice during both normal and abnormal operations. Despite ongoing research in Korea, few IDSS for NPPs have been effectively applied and verified. Furthermore, established designs and validation guidelines for IDSSs for Korean NPPs remain lacking. To address this gap, this study systematically identifies problems and corresponding countermeasures for applying artificial intelligence-based design and validation technologies, while complying with licensing regulatory standards. The aim is to develop a practical and effective IDSS. This study identifies design challenges in the practical application of fundamental IDSS technology, outlining necessary design and validation technologies. Additionally, it suggests technology-specific response plans for the identified design challenges.

Evaluating Methods of Software Bill of Materials Generation to Enhance Nuclear Power Plant Cybersecurity

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) are potential targets of cyberattacks and can prove deleterious for the safety of the NPPs. A Software Bill of Materials (SBOM) provides a detailed list of the various components and their dependencies in software, which helps in vulnerability and risk assessment for cyber hygiene and situational awareness. For an NPP, the process of generating an accurate SBOM report can be complex due to the legacy systems and firmware binaries involved. While most current SBOM tools are focused more on modern internet technology software, this research provides insights and guidelines for an NPP to generate an accurate and efficient SBOM. The paper proposes a new methodology to help NPPs categorize software and use appropriate tools to generate SBOMs for their digital I&C systems.

Explainable, Deep Reinforcement Learning–Based Decision Making for Operations and Maintenance

This paper presents research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance aimed at reducing lifetime maintenance and repair costs. Additionally, a focal point of this research is to make the decisions explainable to operators, improving the trustworthiness of the decisions from what can be considered a black box model. In this work, we develop and evaluate an explainable, online asset management methodology to help reduce lifetime maintenance and repair costs. Using the latest advancements in condition monitoring, inventory management, deep reinforcement learning, and explainable artificial intelligence methods, we create a predictive maintenance methodology that can optimize the maintenance and spare part management of a repairable nuclear power plant system. To demonstrate these methods, preliminary studies were conducted on a representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Using deep reinforcement learning, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies for the chosen system. A key component of our methodology is the integration of Shapley values to quantify the contribution of various factors to the decision-making process. This addition enhances the explainability and trustworthiness of our decisions, providing operators with transparent and understandable insights into the rationale behind maintenance strategies. The robustness and resiliency of our decision policy against observation noise were also thoroughly evaluated, demonstrating its effectiveness in uncertain operational environments.

Investigation of Factors Affecting Corrosion Mechanisms in Latent Heat Thermal Energy Storage Systems

Concentrated Solar Power (CSP) plants integrated with Latent Heat Thermal Energy Storage (LHTES) systems offer a promising solution for dispatchability, reliability, and economic concerns generally associated with renewable energy technologies. These systems, however, require an operational life of up to 30 years to compete with power plant systems operating on fossil fuels. This is a significant challenge due to the high temperatures and corrosive eutectic salts utilised in LHTES systems. Additionally, these systems and its subcomponents are expected to be under varying degrees of stress due to the diurnal cyclic temperature variations inherent in the plant’s operational cycle. Hence, it is crucial to understand the various factors that can affect the operational life of materials used in such applications and conduct thorough material compatibility studies to assess the combined impact of these operating conditions on corrosion mechanisms. This study presents a novel static immersion test approach using modified Compact Tension (CT) specimens manufactured from 316L to investigate the effects of Na2CO3:NaCl (59.45:40.55 wt.%) salt, elevated temperatures (700 ℃ for up to 1000 hours), and stress on corrosion induced in the alloy. The post-exposure results are characterised with Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) shows that corrosion mechanisms are significantly affected by factors such as high operating temperatures leading to changes in both corrosion morphology and rate, high stresses causing localised preferential corrosion, as well as corrosive salt and oxygen availability affecting the type of corrosion induced.

USE OF IIoT TECHNOLOGIES IN ENGINE MONITORING AND CONTROL SYSTEMS

Determining the operating parameters of engine systems is very important to ensure its long-term reliability. Modern power plants use a large number of modern electronic components (sensors, controllers, etc.). All systems generate a huge volume of data that must be tracked, processed and analyzed, which in turn creates calls to gateways and servers. However, the current state of development of microcontrollers and their power allow the use of fog computing, which can lead to more efficient use of both the power plant and data transmission systems. Also, the use of modern microcontrollers and fog computing allows modernizing old power plants with minimal effort and creating new information nodes for monitoring the state of nodes and engine systems and easily combining them with systems already existing on the engine. The selection of a microcontroller and justification of its type for the modernization of the fuel system of a diesel engine are considered. Rapid processes occur in the high-pressure fuel system of diesel engines, which can be determined by changes in fuel pressure. For detailed measurement of processes in the fuel system, measurements should be made with a frequency of at least 24 kHz, i.e.: if the crankshaft rotation frequency is 4000 min-1, then 24,000 measurements should be made every second (when registering data after 1 degree of crankshaft rotation). Another indicator that imposes its requirements is the bit rate of the analog-to-digital converter (ADC), which depends on the range of recorded values. For example, an ADC with a resolution of 8 bits is capable of outputting 256 discrete values (0…255). That is, the higher the bit rate, the more sensitive the converter is to signal changes, and 8 bits may not be enough. Thus, even a small number of sensors can generate a huge amount of data. Transmitting large amounts of data is irrational and can lead to data loss and "clogging" of transmission channels, which challenges the computational performance of the microprocessor.

Experimental investigation of material properties of GFRP pipe for numerical simulation of novel nuclear power plant cooling water intake system

The cooling systems of nuclear power plants are typically made of reinforced concrete water intake structures and special steel pipes, making them large, important structures that necessitate very expensive special productions. In the scope of this research, an innovative design for 4-meter diameter GFRP composite pipes used in nuclear power plant cooling systems was developed using the circular wrapping method. The composite GFRP pipe used in the study has a substantial embedment depth. For this reason, an innovative design was created using unique stiffening rings, and the impact of these rings on the overall behavior was investigated. The nonlinear numerical analysis model of the nuclear power station cooling system, which consists of three pipes with a diameter of 4 m, was then created with ANSYS finite element software using the determined material models, and the results were interpreted. As a result of the study, a composite GFRP pipe design that can be used as a cooling system in significant structures like nuclear power plants has been developed.

Design and optimization of power conversion system for a steady state CFETR power plant

A promising magnetic fusion steady state reactor is Chinese Fusion Engineering Testing Reactor (CFETR) and a different power conversion system is required than tokamak reactor. The control and utilization of high outlet temperature and thermal power generated by the fusion reactor efficiently are the main challenges in the field of thermo-fusion technology. An efficient and optimized power conversion system is an urge for the thermo-fusion energy system with a candidate working fluid under high temperature and pressure. Five cycle topologies based on the Brayton cycle have been designed such as multi stage expansion and recompression cycle with intercooling, recompression cycle with intercooling, partial expansion with multistage compression, partial expansion and partial recompression with cooling across range of turbine and compressor inlet temperatures. Brayton cycle with different system configurations have been simulated with He-gas and supercritical Carbon Dioxide (CO2) to conceive high outlet temperature of CFETR about 500 °C and thermal power of 200 MWth for better thermal performance by using REFPROP, EES and analytical model has been developed with MATLAB. The supercritical CO2 has better thermal performance about 36.18 % as compared to He-gas has 29.81 % under same thermal conditions. The Schematic-I with addition of preheat and recompression enhance the thermal performance about 2 % and has been proposed for CFETR. The effect of change in pressure of the system, effect of the working fluid, isentropic efficiency, heat rate and back to work ratio on the thermal performance and network output have been analyzed and optimized based on analytical model with the MATLAB. The system net power is increased from 69.20 MW to 79.71 MW, heat rejected by the system is decreased from 134.46 MW to 127.06 MW and thermal performance is increased about 34.62 %–39.85 % with pressure from 24 MPa to 28 MPa. Using multi stage expansion and recompression cycle with intercooling instead of other topologies can improve the thermal performance up to 6.1 % depends upon the operation conditions and working fluid. The heat rate of the system decreased while back work ratio increased with the pressure and it reveal that calculations are correct.

Reversible solid oxide cells-based hydrogen energy storage system for renewable solar power plants

The power-H2-power system based on reversible solid oxide cell is a promising pathway for large-scale renewable energy storage but not well understood due to the absence of comprehensive system analyses. In this study, a reversible solid oxide cell-based H2 energy storage system for a 100 % renewable solar power plant is proposed and analyzed through detailed modeling approach and optimization framework. The detailed parametric analyses and economic evaluations are performed in electrolysis (12:00 pm, sufficient solar energy) and power generation (6:30 am, insufficient solar energy) conditions. Notably, it is found that larger stack capacity (Ncell) and higher operating temperature (TReSOC) of the cell enhances system net H2 production and system economics despite additional investment cost. Afterwards, the optimal system performance is obtained (VH2,produce = 498.40 Nm3·h−1, Z=263.59 $·h−1 for electrolysis, and VH2,consume = 380.33 Nm3·h−1 for power generation) through multi-objective optimization by fully considering cell internal operating characteristics and system energy-exergy-economic factors. Besides, it is also found that the performance of power-H2-power system is still limited by remarkable fuel (H2) costs for nighttime power generation (daytime H2 production is smaller than nighttime H2 consumption when Wtot = 1 MW). Therefore, the critical power capacity (Pcritical) is obtained, offering a convenient approach to determine the maximum output capacity (Pcritical = 880 kW) to make the power-H2-power system profitable at specific solar energy input. This study provides valuable insights between system capacity, economics, and cell operating features in solar power plants, which are useful for the design and optimization of practical power-H2-power systems for renewable energy storage.

Optical study of combustion stability in dual fuel approach using ammonia and high reactivity fuel

Ammonia, as a zero-carbon fuel, is considered to be an ideal alternative fuel for a reduction of carbon dioxide emissions. Owing to low laminar flame speed and high ignition energy, the utilization of pure ammonia in powerplant system still presents severe challenges. To solve these issues, the dual fuel combustion of high reactivity fuel and ammonia is a promising solution. However, the dual fuel combustion stability of ammonia and high reactivity fuel has not been clearly understood. In present study, the misfire reasons are investigated using various optical diagnostic methods. Results demonstrate that the misfire reasons are divided into two aspects. One is that the addition of ammonia increases the temperature and pressure required for direction injection fuel auto-ignition, which makes it difficult to generate auto-ignition site, resulting in misfire. The other is that the low flame development speed and degradation of the in-cylinder temperature and pressure causes the difficulty in the further flame development, which results in misfire. A collaborative regulation approach of engine operating condition and direction injection fuel reactivity is proposed to improve combustion stability, which achieves 93% ammonia energy ratio. At 93% ammonia energy ratio, increasing direction injection pressure from 600 bar to 1000 bar decrease combustion stability. The local equivalence ratio of direction injection fuel that can ignite ammonia stably is mainly concentrated between 0.56 and 0.86 in the conditions of 93% ammonia energy ratio and 22 bar in-cylinder pressure. Compared with the in-cylinder temperature, the main factor in determining combustion stability is local equivalence ratio of direction injection fuel. The addition of ammonia prolongs the low temperature reaction and constrains the high temperature reaction of direction injection fuel. In brief, the combustion stability and ammonia energy ratio can be improved simultaneously using the collaborative regulation.

Study of a Novel Updraft Tower Power Plant Combined with Wind and Solar Energy

This study presents a novel solar updraft tower power plant (SUTPP) system, which has been designed to achieve the simultaneous utilization of solar and wind energy resources in desert regions, in response to the pressing demand for sustainable and efficient renewable energy solutions. The aim of this research was to develop an integrated system that is capable of harnessing and converting these abundant energy sources into electrical power, thereby enhancing the renewable energy portfolio in arid environments. The methodology of this study involved the design and construction of a prototype SUTPP, comprising a 53 m high tower, a 6170 m2 collector, five horizontal-axis wind turbines, and a thermal energy storage layer made up of pebbles and sand. The experimental setup was meticulously detailed, and experiments were conducted to collect data on the system’s performance under various environmental conditions. Subsequently, three-dimensional numerical simulations were performed to explore the effects of ambient wind speed and solar radiation on the output power of the SUTPP. The results indicate that the output power of the system increases with the increase in ambient wind speed and solar radiation. The impact of solar irradiation on output power was observed to diminish as ambient wind speeds increased. Notably, as the inlet wind speed rose from 4 m/s to 12 m/s, the output power showed a substantial increase of 727%. The numerical simulations revealed that ambient wind speed has a more pronounced effect on power output compared to solar radiation. Furthermore, it was found that the influence of solar radiation is significant at low wind speeds, with its impact decreasing as wind speed increases. This research provides essential guidance for the design and engineering of highly efficient solar thermal energy utilization projects, representing a significant advancement in the field of renewable energy technology deployment in desert environments.

Reliability enhancement through optimal placement of photovoltaic power plant and battery energy storage in distribution system

Integration of distributed generation (DG) units could reduce the duration of power outage for a certain number of consumers in distribution networks after a network failure. Prerequisites are that i) the DG unit has the technical characteristics that enable its islanded operation, the degree of automation of the distribution network allows it and ii) it is in accordance with the current technical regulations of the country. The extent to which integration of distributed sources can improve reliability depends on the DG size, type, and the point of common coupling. Besides, an energy storage system could be installed along with DG unit, so that energy supply availability during fault periods can be secured. This paper proposes an algorithm based on mixed-integer linear programming (MILP) approach for optimal placement of photovoltaic power plant (PVPP) and battery energy storage system (BESS). The optimal location is determined so that expected non supplied energy is minimized. The uncertainties in the estimation of production of PVPP, load and BESS state of charge (SoC) were taken into account by Monte Carlo simulations (MCS).

Gear detection and research for hydraulic couplers based on AC electromagnetic field techniques

Abstract To address the issue of fatigue cracks of hydraulic coupler gears in nuclear power plants, we construct an alternating current (AC) electromagnetic field detection system based on stress analysis of gear models. In this model, we design a probe suitable for gear detection in the main feedwater system of nuclear power plants. Moreover, artificial defects are machined into the gears to verify the feasibility of the AC electromagnetic techniques. Results indicate that the AC electromagnetic field techniques can detect the near-surface defects in the test piece with a greater detection depth and better detection effectiveness.

Investigation on the thermal characteristics of electronic system and prediction of chip temperature by machine learning

In this work, the thermal characteristics and steady-state temperatures (SST) of CPU and FPGA of electronic system in nuclear power plant are explored. Finite element analysis is performed to simulate the test process. Furthermore, three machine learning algorithms are used to predict chips temperatures at different operating conditions. It is found that when the ambient temperature is 20 °C and all the fans are power-off, the SST of the CPU and FPGA reaches 75 °C and 72 °C, respectively. While when the fans are power-on, the SST of the CPU and FPGA drops to 37.5 °C and 33 °C. When the ambient temperature increases to 55 °C and all the fans are power-on, the SST of the CPU and FPGA is 72.3 °C and 68.2 °C, respectively. The finite element model is verified and used to generate test data. Three machine learning models are verified by predicting the SST of CPU and FPGA under different operating conditions. It is found that M-SVR has better prediction ability than DT and ANN. The findings can be used for chip reliability evaluation of other electronic system devices, and provide a new method for predicting the possible steady-state temperature of chips under different service conditions.

Coupling of the best-estimate system code and containment analysis code and its application to TMLB’ accident

With the development of advanced pressurized water reactor technology, the thermal-hydraulic coupling effect between the containment and the primary system becomes increasingly tight. In order to meet the demand for integrated safety analysis between the containment and the primary system, this paper investigates a direct coupling method between the best-estimate system code Advanced Reactor Safety Analysis Code and the containment analysis program ATHROC (Analysis of Thermal Hydraulic Response Of Containment). The feasibility of this direct coupling method and the applicability of the coupled program for overall safety analysis are demonstrated using Marviken two-phase flow release experiments. The ATHROC/ARSAC coupled program is employed to analyze the impact of the pressure relief function of the CPR1000 nuclear power plant pressurizer on the behavior of the primary system and containment during the TMLB’ accident. The calculation results indicate that these measures can reduce the pressure of the primary system to the level acceptable by the low-pressure injection system, but at the same time, they cause the pressure in the containment to rise to nearly 0.4 MPa. Therefore, to ensure the structural integrity of the containment, it is necessary for the non-passive hydrogen recombiner to effectively reduce the hydrogen concentration, thereby avoiding additional pressure increase in the containment due to hydrogen deflagration, which could lead to overpressure failure. The findings of this study are of significant reference value for improving the safety performance of thermal-hydraulic systems in operational Gen-II and advanced Gen-III pressurized water reactor nuclear power plants.

Profitability on Solar Power Plant Systems for Households Electricity in Indonesia

Profitability on Solar Power Plant Systems for Households Electricity in Indonesia

Integrating reliability analysis into MBSE for FPGA-based safety critical I&C system design in nuclear power plants

Abstract With the widespread application of Field Programmable Gate Array (FPGA) technology in the instrumentation and control (I&C) systems of nuclear power plants (NPPs), its design reliability has become the key to ensuring the subsequent safe operation of NPPs. However, the traditional document-based design method is no longer sufficient to meet the current design needs of complex systems, and there is a lack of research related to the reliability and security analysis of FPGA-based systems. Therefore, the overall goal of this study is to integrate reliability analysis into the model-based systems engineering (MBSE)-based design of FPGA-based I&C systems. Based on the typical application characteristics of the FPGA, a digital design framework for FPGA-based systems is proposed to realize a traceable design process from requirements to implementation. Subsequently, a model-based forward comprehensive reliability analysis method is proposed, which uses a SysML-based mapping mechanism to integrate Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) methods into the design process, so as to comprehensively identify and analyze failure modes from systems to components and optimize and improve system design. Finally, the proposed method is applied to the analog output design of FPGA-based systems. The proposed method can provide guidance for improving the reliability of FPGA-based DI&C systems and provide theoretical basis for the further engineering application.