Thermal Power Research Articles

Numerical simulation of single well geothermal system based on the artificial geyser concept considering phase change and multiphysics coupling

A geothermal system based on the artificial geyser concept can be free of high-pressure circulation pump. The core component of this system is a flash steam chamber located at the high-temperature well bottom, where periodic spray and vaporization of fine droplets occur, thus generating high pressure to drive the vapor to rise through the well- insulated inner tube of a coaxial heat exchanger (CHE). Though there was a semi-analytical model to evaluate this process, it failed to consider the heat transfer between ascending hot vapor and descending cold water in the CHE. Therefore, a new multi-physics coupled numerical model has been developed to assess the system operation mechanism, including the phase change of water. This model employs full coupling throughout its operation: during the downward flow of water in the well, it accounts for heat sources from both the hot formation and the ascending steam; during upward flow of vapor, it assesses the degree of steam condensation due to heat loss. The thermal behavior of descending water in the annulus is validated against existing research on a closed-loop borehole heat exchanger. Through the sensitivity analysis, it can be concluded that changes in the radius of production well and variation in the flow rate of injection well have a significant impact on the system's thermal power. For an engineering case with the same initial and boundary conditions, the outlet temperature of our system is around 50 °C higher than that of the hydrothermal system, and the total heat extraction reaches 380 kW, indicating that the artificial geyser system offers superior performance in terms of thermal energy utilization. After comprehensive optimization of the injection rate of water, the production well's radius, and the bottom pressure, the total heat extraction can reach 1 MW. In the actual project, one should monitor the pressure between the production well and the flash chamber to ensure the outlet vapor remains dry and has a high flow rate.

Improving Steam Turbine Plants Performance Through Advanced Testing and Simulation

The prolonged operation of thermal power plants inevitably leads to component aging and a gradual decline in performance. This deterioration increases the gross heat rate and reduces electrical output, resulting in higher fuel consumption and lower electricity production. Consequently, these issues can cause significant financial losses and threaten the plant’s competitiveness. This paper presents a comprehensive methodology for improving the performance of existing plants. The methodology consists of two crucial elements: steam turbine testing and numerical simulation of the process. The tests should be comprehensive to ensure accurate measurements and reliable conclusions. The developed method for process simulation enables the calculation of overall performance, like specific heat rate and thermal efficiency, as well as the performance of individual components under various operational conditions. Comparing numerical results with experimental data can effectively identify operational problems. Based on these findings, targeted overhauls and other corrective measures can substantially improve the plant’s thermal efficiency and financial performance. The system was demonstrated through a case study of a 120 MW coal-fired steam turbine. The test revealed that it consumes more than 10% additional heat compared to its original design specifications. The analysis identified operational issues and recommended improvement measures, focusing exclusively on the steam turbine set while excluding the boiler.

Epitaxial Growth of Triple-Layered Brownmillerite Cobalt Oxide Sr4Co3O9.

Layered perovskite oxides with the Ruddlesden-Popper (RP) structure exhibit diverse functionalities, yet the synthesis of cobalt-based RP oxides is hindered by competing phase formation. In this study, we successfully synthesized Sr4Co3O9, a triple-layered cobalt oxide with a layered brownmillerite structure, as an epitaxial thin film on a LaAlO3 substrate. Soft X-ray absorption spectra confirmed oxygen nonstoichiometry and a mixed-valence state of Co3.3+ while scanning transmission electron microscopy revealed the presence of a tetrahedral layer in the central perovskite block. The structural comparison indicates that unlike conventional brownmillerite A2B2O5, the triple-layered A4B3O9 phase features axially elongated octahedra with significant B-site off-centering, driven by Coulomb repulsion from the tetrahedral B cations. Density functional calculations suggest a charge-ordered antiferromagnetic state. The thermal power of Sr4Co3O9 is lower compared to other layered cobalt oxides, such as NaxCoO2. Our results demonstrate the impact of structural modulation in layered brownmillerite oxides, offering a perspective for designing functional materials.

Multilayer stackable grouped acoustic metamaterial with optional sound absorption performance

The control of noise pollution in the low-frequency domain with various spectrum ranges requires the development of a novel tunable sound absorbing material, and a multilayer stackable grouped acoustic metamaterial (MSG-AM) is proposed in this research to obtain the optimal noise reduction effect while minimizing the occupied space. The MSG-AM includes four layers with the eight Helmholtz resonators in each layer divided into three groups, and the total 32 resonators in different layers are connected in parallel. The sound absorption property of each layer is optimized by the joint simulation of finite element simulation and particle swarm optimization algorithm, and the average sound absorption coefficient (SAC) reaches 0.8609 for the first layer in the 535–650 Hz, 0.7126 for the second layer in the 782–937 Hz, 0.9285 for the third layer in the 650–782 Hz, and 0.7615 for the fourth layer in the 435–535 Hz, respectively. The four layers can be combined flexibly to gain the desired sound absorption property in the expected frequency range, and the sequence of multiple layers is a critical factor. The average SAC of the MSG-AM with four layers is improved from 0.3696 for 4 + 1 + 3 + 2 to 0.8726 for 2 + 3 + 1 + 4, and it is better to put behind the layer to obtain absorption in the low-frequency domain and put in front the layer to achieve absorption in the high-frequency domain. The sound absorption mechanism is revealed intuitively through the distributions of thermal power densities, which certify that there exists Helmholtz resonance and Fabry–Pérot resonance effects simultaneously. The proposed MSG-AM is conducive to guarantee the effective control of variable noise.

A new deep learning-based approach for predicting the geothermal heat pump’s thermal power of a real bioclimatic house

In recent years, growing concern about climate change and the need to reduce greenhouse gas emissions have highlighted the role of energy efficiency and sustainability on the global agenda. Energy policies are decisive in establishing regulatory frameworks and incentives to address these challenges, leading to an inclusive and more resilient energy transition. In this context, geothermal energy is an essential source of renewable, low-emission energy, capable of providing heat and electricity sustainably. The present research focuses on a bioclimatic house’s geothermal energy system based on a heating pump and a horizontal heat exchanger. The main aim is to predict the generated thermal power of the heat pump using historical data from several sensors. In particular, two approaches were proposed with both uni-variate and multi-variate scenarios. Several deep learning techniques were applied: LSTM, GRU, 1D-CNN, CNN-LSTM, and CNN-GRU, obtaining satisfactory results over the whole dataset, which comprised one year of data acquisition. Specifically, promising results have been achieved using hybrid methods combining recurrent-based and convolutional neural networks.

Thermal and Exergy Efficiency Analysis of Receiver for Solar Thermal Power Plant System

The purpose of this research is to analyses the thermal energy and the exergy efficiency of the focal point receiver in a solar power generation system. Heliostats are used as reflectors, directing sunlight towards the focal point receiver. The receiver transfers thermal energy to the first working medium, which is molten salt. Subsequently, the thermal energy from the molten salt is transferred to the second working medium, water. Once heated, the water boils and becomes steam, which can then drive a steam turbine to generate electricity. This research specifically analyses the thermal energy and assesses the exergy efficiency at the focal point receiver only, using the Engineering Equation Solver (EES) program to assist in calculations and to compare with past research. The thermal efficiency increases with higher Direct Normal Irradiation (DNI) values, where DNI ranges from 100 to 300 W/m2, showing a rapid increase in thermal efficiency. Then, the thermal efficiency gradually increases as the DNI ranges from 300 to 700 W/m2, and remains nearly constant at levels above 700 W/m2. The exergy efficiency also increases rapidly as DNI values range from 100 to 400 W/m2, then it gradually increases when DNI values range from 300 to 700 W/m2, and remains nearly constant at levels above 700 W/m2.

Innovative Soil Stabilization by using Fly Ash and Plastic Strips for Black Cotton Soil Improvement

In civil engineering construction, soil is essential, and inadequate soil characteristics can result in serious structural problems. The extremely expansive black cotton soil, which is primarily found in South India, presents significant difficulties since it shrinks in dry conditions and swells during the rainy season. Pavements, buildings, and foundations sustain significant damage as a result of these volume fluctuations. Stabilization methods are necessary to improve the black cotton soil's engineering qualities. This study investigates the use of fly ash and plastic strips to stabilize black cotton soil. Fly ash, an industrial by-product from thermal power plants, is incorporated at varying percentages of 5%, 10%, 15%, and 20% to determine the optimal dosage for improving soil strength. Once the optimal fly ash percentage is identified, plastic strips of 20mm × 20mm dimensions are added at 0.25%, 0.5%, 0.75%, and 1% by weight of the soil. The inclusion of plastic waste addresses its disposal challenges while enhancing soil properties. The stabilization process aims to improve soil strength, reduce its expansive nature, and mitigate infrastructure damage Fly ash and plastic strips work together to improve black cotton soil in an economical and environmentally responsible way, encouraging sustainability in building. This research contributes to more robust and long-lasting infrastructure by shedding light on the possible use of industrial waste for soil stabilization.

Modeling the Tripartite Coupling Dynamics of Electricity–Carbon–Renewable Certificate Markets: A System Dynamics Approach

To ensure a smooth transition towards peak carbon emissions and carbon neutrality, one key strategy is to promote a low-carbon transition in the energy sector by facilitating the coordinated development of the electricity market, carbon market, and other markets. Currently, China’s national carbon market primarily focuses on the power generation industry. High-energy-consuming industries such as the steel industry not only participate in the electricity market but also play a significant role in China’s future carbon market. Despite existing research on market mechanisms, there remains a significant research gap in understanding how steel enterprises adjust their trading behaviors to optimize costs in multi-market coupling contexts. This study employs a system dynamics approach to model the trading interconnection between electricity trading (ET), carbon emission trading (CET), and tradable green certificates (TGC). Within this multi-market system, thermal power enterprises and renewable generators serve as suppliers of carbon allowances and green certificates, respectively, while steel companies must meet both carbon emission constraints and renewable energy consumption obligations. The results show that companies can reduce future market transaction costs by increasing the proportion of medium to long-term electricity contracts and the purchase ratio of green electricity. Additionally, a lower proportion of free quotas leads to increased costs in the carbon market transactions in later stages. Therefore, it is beneficial for steel companies to conduct cost analyses of their participation in multivariate market transactions in the long run and adapt to market changes in advance and formulate rational market trading strategies.

The Optimal Low Carbon Economic Dispatch Scheme Based on GRU and C&CG Models in the Context of Smart City Development

The transition to low-carbon energy and energy system optimization are essential for addressing global carbon emissions. To improve the quality of low-carbon economic dispatching, a forward-day low-carbon economic dispatching model considering liquid-storage carbon capture system and electric-gas coupling equipment is proposed. In the process, gated cycle unit and column and constraint generation algorithm are used to solve the model. The upper limit and ramp rate of the gas turbine power are calculated, and multiple constraints are established for the model. The fusion algorithm is used to solve the model and iterate to obtain the optimal day-ahead low-carbon economic scheduling scheme. The experimental results showed that the output power of thermal power units in all four scenes demonstrated consistent variation patterns, achieving significant output power values within the 21600s-64800s. For the output power of the liquid storage carbon capture unit, Scene 4 was below Scene 3. For the output power of P2G devices, Scenes 1 and 3 were 0, and Scene 4 was below Scene 2. The optimal volumes for P2G device and storage type carbon capture solution device was 150 × 106 W and 800000 kg, respectively. The study highlights the feasibility of combining carbon capture and conversion technologies for sustainable energy systems. This integrated approach not only reduces carbon emissions, but also improves energy efficiency and economic efficiency. The research can provide some technical reference for urban environmental protection.

Heat Transfer Performance of Copper Powder-Copper Mesh Composite Wick Flat-Plate Micro Heat Pipe

Abstract Flat-plate micro heat pipe (FMHP) plays an important role in the field of heat dissipation of electronic devices through vapor–liquid two-phase flow. Improving the heat transfer performance of FMHP has become a hot topic. This article analyzes the heat transfer principle of the FMHP to discover that balancing the capillary pressure and permeability of the wick is crucial to the heat transfer performance of the FMHP. Therefore, we propose a kind of copper powder and three kinds of copper powder-copper mesh integrated sintered wicks, build an experimental device, and analyze and research their heat transfer performance. The results show that the wick sintered from two layers of copper mesh and copper powder can better balance the capillary pressure and permeability, and the prepared FMHP has the best heat transfer performance. The maximum thermal power is 30 W and the minimum thermal resistance is 0.27 °C/W at the optimum filling ratios.

Performance Evaluation of a 1500 MW Combined Cycle Power Plant using Energy and Exergy Analysis

The majority of electricity produced worldwide is produced by thermal power plants and these power plants have lower efficiency in comparison to other types of power plants, significant energy and exergy losses occur in thermal power plants, so it is important to reduce these losses, enhance plant performance, and protect the environment. The present study provides a thorough energy and exergy analysis of the Erbil Combined Cycle Power Plant (CCPP) using real operation data to give suggestions and recommendation points to enhance overall efficiency. The plant consists of 8 gas turbines, 8 heat recovery units, 2 steam turbines, and 2 condensers. The exergy study findings indicate that the Combustion Chamber (CC) exhibits the highest level of exergy destruction in comparison to the other components of the plant at 74% of the overall exergy losses while the condenser exhibits the highest level of energy losses compared to the other components of the plant at 1043 MW. The power plant efficiency has significantly enhanced with the transition from a gas turbine cycle to a combined cycle, with energy efficiency increasing by 30.2% to 46.1% and exergy efficiency rising by 28.7% to 43.7%. The gas turbine achieved the highest exergy efficiency in the plant, reaching a value of 95.9%. The plant components were negatively influenced by ambient temperature, when it was increased the exergy efficiency of the components decreased. The flue gas had an exergy of 43.2 MW, which is considerably high and may be used again.

The Multi-Point Cooperative Control Strategy for Electrode Boilers Supporting Grid Frequency Regulation

With the large-scale integration of wind power, photovoltaic, and other renewable energy sources into the power grid, their inherent randomness and variability present significant challenges to the frequency stability of power systems. Conventional thermal power units with limited frequency regulation capabilities face further strain, as frequent power fluctuations accelerate wear and tear, thereby shortening their operational lifespans. This makes it increasingly difficult to meet the demands for frequency regulation. Electrode boilers, as flexible electrical loads, can be retrofitted to enhance their flexibility and participate in grid frequency regulation alongside renewable energy units. This not only improves frequency stability but also reduces wear on generating units. However, the frequency regulation process involves balancing multiple objectives, such as maintaining system frequency stability, ensuring economic efficiency, and optimizing operational effectiveness. Traditional control strategies often struggle to address these competing objectives effectively. To address these challenges, this paper proposes a multi-objective collaborative optimization control decision model for electrode boilers to assist in grid frequency regulation. The model not only meets the frequency regulation requirements but also considers additional constraints, including the operational efficiency of electrode boilers, economic benefits, and equipment degradation. A genetic algorithm is employed to solve the model, and simulation analysis is conducted using the IEEE 14-node system. The results demonstrate that this strategy significantly enhances frequency stability, improves boiler operational efficiency, and boosts economic benefits, offering a viable solution for integrating electrode boilers into grid frequency regulation.

Modeling and Verification of Medium-Speed Coal Mill Based on Mechanism and Parameter Optimization Algorithm

Medium-speed coal mills are widely employed in thermal power plants. Developing an accurate mathematical model for these mills is essential for optimizing control systems. This paper presents a comprehensive mathematical model of a medium-speed coal mill, dividing it into four distinct regions based on its structural design. The model integrates the internal temperature distribution characteristics of the mill. To further enhance its accuracy, model parameters are optimized using the quantum particle swarm optimization (QPSO) algorithm, and the model is validated against field data. The results indicate that the model exhibits a high degree of accuracy, offering valuable support for fuel control system optimization and structural improvements in coal mill design.

Effectiveness of acupoint injection combined with specific electromagnetic spectrum irradiation and acupuncture on peripheral facial paralysis.

To investigate the clinical effectiveness of acupoint injection in the treatment of acute phase of peripheral facial paralysis (PFP). A total of 85 patients with PFP were randomly divided into the control group, which was treated by prednisone acetate; the thermal design power (TDP) group, which was treated with acupuncture plus specific electromagnetic spectrum irradiation; and the acupoint injection group, which was treated with acupuncture plus specific electromagnetic spectrum irradiation combined with vitamin B1 (Vit B1) and vitamin B12 (Vit B12) acupoint injection. The treatment effectiveness was evaluated by Portmann score of facial paralysis, House-Brackmann (H-B) facial nerve function grading, serum levels of IL-6, IL-1β, and TNF-α, the cure time, and total effective rate. The scores of Portmann and H-B in the TDP group were significantly higher than the control group, and the acupoint injection group was higher than the TDP group after each course of treatment (p < 0.05). The time to produce a significant effectiveness was shortened in the order of the acupoint injection group > the TDP group > the control group (p < 0.05). The cure rate was higher in the acupoint injection group (100%) than the TDP group (72.41%) and control group (67.86%) (p < 0.05). The serum levels of IL-6, IL-1β and TNF-α were obviously lower in the TDP group than the control group and in the acupoint injection group were lower than the TDP group (p < 0.05). Acupoint injection can significantly improve the curative effect, shorten the cure time, reduce the level of serum inflammatory factors, and promote the recovery of facial nerve function in the acute stage of PFP.

CO2 Emission Inventory in Türkiye and Estimation of CO2 Concentration over Türkiye by Using Dispersion Modelling

The density and composition of the atmosphere strongly influence the temperature of the Earth. The release of greenhouse gases has changed the radiative balance of the atmosphere and trapped some of the outgoing energy. The most important greenhouse gas (GHG) is carbon dioxide (CO2). CO2 concentration in the atmosphere is increasing continuously and will keep growing. The rise in the concentration of CO2 is due to the combustion of fossil fuels for energy generation. It is estimated that CO2 concentration is responsible for about 60% of the greenhouse effect. The main scope of this study is to assess the results of CO2 inventories and dispersion modelling for the period 1990 – 2003 in province and district bases. The collected data from households, transportation, industry, and thermal power plants were used to estimate district base emissions for CO2. However, after the year 2004, the collected data is not permitted to estimate ground-level CO2 concentrations due to the confidentiality of many data. Therefore, the projection of the concentration study has been done only for the year 2004. However, the emission inventory has been projected until the year 2010. After this year, the province and district base projections contain lots of errors and uncertainties. The economic conditions, industrial development, increasing number of thermal power plants, and changing number of households create many errors and uncertainties besides the collected activity data. In addition, the data including households, industrial activities, and thermal power plants is confidential and requires many agreements by governmental organizations. For that reason, the study period is limited to 1990 and 2003. However, the selected period is very important for the base year evaluation. Türkiye has no base year in the presence of the Convention and Protocol. The inventory for the years between 1990 and 2003 is also very important in terms of evaluating industrial development in Turkey. During this time, there was a very critical improvement in the emission of CO2 depending on the Turkish economy. The fluctuation of CO2 emission has shown a great variety, and this study has considered the fluctuations under the economic conditions of Türkiye during this period. Following the emission inventory, the dispersion of CO2 was studied by using the USEPA’s Industrial Source Complex Long Term Model, Version 3 ISCLT3. Based on the results of modeling calculations, the ground-level CO2 concentration maps were prepared and superimposed on the geographical map of Türkiye by using Geographic Information System (GIS) techniques. GIS techniques were used to map all the information. The results of the CO2 emission inventory conducted in this study between 1990 and 2003 showed that the CO2 emission in 1990 was 142.45 million tones/year and it is noteworthy that the year 2000 saw the highest recorded emissions, amounting to 207.97 million tones/year. The territorial distributions of CO2 emission have shown that the Marmara Region emits the highest regional CO2 emission throughout the years with a mean value of 54.76 million tones/year. It was also concluded that the Aegean and Marmara Regions are responsible for half of the CO2 emission of Türkiye. The highest ground-level CO2 concentrations were always obtained in the Marmara Region. This condition will still be maintained in 2024.

Performance Assessment of an Interconnected Photovoltaic‐Thermal System and Solar Thermal Collector: Parametric Study and Optimization

ABSTRACTIn the present study, an interconnected photovoltaic‐thermal system and solar thermal collector with half‐tubes are presented as a new generation of solar systems to produce maximum thermal and electrical power. Performance comparison of the photovoltaic module, photovoltaic‐thermal system, solar thermal collector, and proposed system shows that the maximum power of 1336.27 W is generated by the proposed system. Also, the outlet fluid temperature increases by 28.03% and 20.88% compared to the photovoltaic‐thermal systems and solar thermal collectors, respectively, which indicates higher quality of the generated thermal power. To improve the system performance, fins with different heights are used inside the half‐tubes. The results indicated that the overall generated power increases using the fin by up to 2.93%. A parametric analysis using response surface method showed that among four parameters including flow rate, incident solar radiation, wind speed, and ambient temperature, the solar radiation and ambient temperature have the most and least impact on the system output, respectively. Also, using the response surface method, two models are provided to predict the electrical and thermal power generation of the system. Single‐objective and multi‐objective optimization of the system is also investigated using these models.

Turbine Generator with Increased Rotation Speed for Small-Capacity Thermal and Nuclear Power Plants

Turbine Generator with Increased Rotation Speed for Small-Capacity Thermal and Nuclear Power Plants

Interpretable machine learning model for temperature prediction in coal pulverizer of thermal power plants

Interpretable machine learning model for temperature prediction in coal pulverizer of thermal power plants

A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer

Precise pressure control in shell-and-tube steam condensers is crucial for ensuring efficiency in thermal power plants. However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. These challenges lead to slow response, high overshoot, and poor steady-state performance. To address these limitations, this study proposes a cascaded PI-PDN control strategy optimized using the electric eel foraging optimizer (EEFO). EEFO, inspired by the prey-seeking behavior of electric eels, efficiently tunes controller parameters, ensuring improved stability and precision. A comparative analysis against recent metaheuristic algorithms (SMA, GEO, KMA, QIO) demonstrates superior performance of EEFO in regulating condenser pressure. Additionally, validation against documented studies (CSA-based FOPID, RIME-based FOPID, GWO-based PI, GA-based PI) highlights its advantages over existing methods. Simulation results confirm that EEFO reduces settling time by 22.7%, overshoot by 78.7%, steady-state error by three orders of magnitude, and ITAE by 81.2% compared to metaheuristic based methods. The EEFO-based controller achieves faster convergence, enhanced robustness to disturbances, and precise tracking, making it a highly effective solution for real-world applications. These findings contribute to optimization-based control strategies in thermal power plants and open pathways for further bio-inspired control innovations.

Thermal shock resistance of additive manufactured Inconel 718 by concentrated solar energy

Concentrated Solar Power (CSP) is a powerful tool for simulating the extreme high-temperature conditions that metallic materials encounter. Using a vertical parabolic solar furnace, it was possible to perform heating and cooling cycles between 250 and 950 °C in approximately 250 s per cycle. This capability is particularly relevant for the development of solar receivers used in solar thermal plants. Additive Manufacturing (AM) offers the potential to create new compositions and geometries that can enhance the efficiency of these solar receivers. In this study, Ni-base superalloys—identified as suitable materials for high-temperature solar receivers—were produced using AM and tested in two conditions: as-built and after thermal treatment. These were compared with a forged reference alloy. The results revealed the formation of a protective oxide layer on the surface in all cases. However, the oxide layer on the samples fabricated by additive manufacturing appeared to be more compact and adherent compared to that formed on the reference alloy.