Thermal Power Generation Research Articles

Boiler Combustion Adjustment and Economic Operation Affect Boiler Combustion Factors

Thermal power generation, as the most stable power output in China, plays a rather crucial role in the construction of China's economy. The most important power generation equipment of thermal power plant is the boiler, only good control of the boiler operation of the power plant, in order to better enable it to participate in the power generation work. Combined with the Linfen Thermal Power Co., Ltd. related boiler unit operation status, combustion adjustment optimisation content analysis, give the corresponding recommendations, so as to make the boiler operation more stable, safe, environmentally friendly, power plant power generation to make the corresponding contribution.

A Metastructure Based on Amorphous Carbon for High Efficiency and Selective Solar Absorption.

Efficient solar thermal conversion is crucial for renewable clean energy technologies such as solar thermal power generation, solar thermophotovoltaic and seawater desalination. To maximize solar energy conversion efficiency, a solar selective absorber with tailored absorption properties designed for solar applications is indispensable. In this study, we propose a broadband selective absorber based on amorphous carbon (a-C) metamaterials that achieves high absorption in the ultraviolet (UV), visible (Vis) and near-infrared (NIR) spectral ranges. Additionally, through metal doping, the optical properties of carbon matrix materials can be modulated. We introduce Ti@a-C thin film into the nanostructure to enhance light absorption across most of the solar spectrum, particularly in the NIR wavelength band, which is essential for improving energy utilization. The impressive solar absorptivity and photothermal conversion efficiency reach 97.8% and 95.6%, respectively. Notably, these superior performances are well-maintained even at large incident angles with different polarized states. These findings open new avenues for the application of a-C matrix materials, especially in fields related to solar energy harvesting.

Design of heliostat field based on ray tracing

In the tower solar thermal power generation system, the optical efficiency of mirror field is the primary factor that determines the power generation efficiency of the whole system. Given the size and installation height of heliostat, in order to meet the requirements of rated Power 60MW, the parameters of heliostat field are designed and the model of tower solar thermal power generation system is established. Considering the cosine loss, shadow occlusion loss and truncation efficiency, and knowing that these three points are closely related to the position of the Sun, a method of ray tracing is proposed to calculate the sunshine accurately, the optimum parameters of helioscope field were determined by simulation. The simulation results show that the average thermal power output per unit mirror area can be increased by reducing the shadow occlusion between the heliostats.

Prediction of Thermionic Energy Conversion Performance and Parametric Effects Using Genetic Algorithms to Fit Physics-Inspired Model Equations to Prototype Test Data

Abstract Thermionic converters have potential as an energy conversion technology for high-temperature space and terrestrial applications using concentrated solar, nuclear reaction, and combustion processes as the heat source. Recent studies have generated experimental performance data for narrow-gap thermionic energy conversion devices. This investigation explores the use of genetic algorithms to fit existing data with physics-inspired model equations. The resulting model equations can be used for performance prediction for system design optimization or to explore parametric effects on performance. The model equations incorporate Richardson’s law for current density, including both the saturated and Boltzmann regimes, with appropriate relations for power delivered to the external load. The transition regime is characterized using two separate models, each accounting for nonuniformity in emission surfaces and irregularities in the manufacturing process. The trained models enable performance prediction of small-gap thermionic energy conversion devices. In this study, data were fitted for two different prototype designs. The prototype test data and postulated values for the work functions and a transition regime parameter are substituted into physics-inspired model equations, yielding performance models with three adjustable constants. Optimized values of these constants are determined using a genetic algorithm to best fit the experimentally determined performance data for prototype thermionic conversion devices tested in earlier studies. This approach is demonstrated to fit the performance data to within 9%. This methodology also allows the user to back-infer the effective work function values, which were found in this study to be consistent with independent measurement.

Erratum: “Potential of Integrating Solar Energy Into Systems of Thermal Power Generation, Cooling-Refrigeration, Hydrogen Production, and Carbon Capture” [ASME J. Energy Resour. Technol., 2023, 145(11), p. 110801; DOI: 10.1115/1.4062381

Erratum: “Potential of Integrating Solar Energy Into Systems of Thermal Power Generation, Cooling-Refrigeration, Hydrogen Production, and Carbon Capture” [ASME J. Energy Resour. Technol., 2023, <b>145</b>(11), p. 110801; DOI: 10.1115/1.4062381

Combined emission economic dispatch using quantum-inspired particle swarm optimization and its variants

The ever-increasing electricity demand, its dependency on fossil fuels, and the consequent environmental degradation are major concerns of this era. The worldwide domination of fossil fuels in bulk electricity generation is rapidly increasing the emissions of CO2 and other environmentally dangerous gases that are contributing to climate change. The economic and emission dispatch are two important problems in thermal power generation whose combination produces a complex highly constrained nonlinear optimization problem known as combined economic and emission dispatch. The optimization of combined economic and emission dispatch aims to allocate the generation of committed units to minimize fuel cost and emissions, simultaneously while honoring all equality and inequality constraints. Therefore, in this article, we investigate a solution of the combined economic and emission dispatch problem using quantum particle swarm optimization and its two modified versions, that is, enhanced quantum particle swarm optimization and quantum particle swarm optimization integrated with weighted mean personal best and adaptive local attractor. The enhanced quantum particle swarm optimization algorithm achieves particles’ diversification at early stages and shows good performance in local search at later stages. The quantum particle swarm optimization integrated with weighted mean personal best and adaptive local attractor boosts search performance of quantum particle swarm optimization and attains better global optimality. The suggested methods are employed to achieve solution for the combined economic and emission dispatch in four distinct systems, encompassing two scenarios with 6 units each, one with a 10-unit configuration, and another with an 11-unit setup. A comparative analysis with methodologies documented in existing literature reveals that the proposed approach outperforms others, demonstrating superior computational performance and robust efficiency.

The failure causes analysis of low-pressure heater pipes based on the porous medium model and local model

Low-pressure heaters are critical heat exchange equipment in thermal and nuclear power generation. The high-speed steam flow in the low-pressure heaters induces pipe vibration, causing pipe failure. The large size and complex flow make it hard to calculate directly. This paper employs a combined method of the porous medium and local models by substituting the boundary to calculate and prove steam flow trajectory and velocity are consistent with the actual situation. The analysis of the turbulent kinetic energy exhibits that the primary causes of pipe vibration are the periodic vortex shedding and the impact of the impingement plate on the pipes. The stress analysis indicates that the loosening of the pipes leads to a 368 times amplification of the shear stress by 0.1 MPa. The most crucial step in solving such a problem is to strengthen the fixation of the pipes, especially near the shell region.

Study on Multivariable Dynamic Matrix Control for a Novel Solar Hybrid STIGT System

To construct a clean and efficient energy system, advanced solar thermal power generation technology is developed, i.e., a solar hybrid STIGT (Steam Injected Gas Turbine) system with near zero water supply. Such a system is conducive to the efficient use of solar energy and water resources, and to improvement of the performance of the overall system. Given that the strong correlation between multiple-input and multiple-output of the new system, the MDMC (Multivariable Dynamic Matrix Control) method is proposed as an alternative to a PID (Proportional-Integral-Derivative) controller to meet requirements in achieving better control characteristics for a complex power system. First, based on MATLAB/Simulink, a dynamic model of the novel system is established. Then it is validated by both experimental and literature data, yielding an error no more than 5%. Subsequently, simulation results demonstrate that the overshoot of output power on MDMC is 1.2%, lower than the 3.4% observed with the PID controller. This improvement in stability, along with a reduction in settling time and peak time by over 50%, highlights the excellent potential of the MDMC in controlling overshoot and settling time in the novel system, while providing enhanced stability, rapidity, and accuracy in the regulation and control of distribution networks.

Enhancing grid-connected inverter performance under non-ideal grid conditions: a multi-functional multiplexing control strategy

Compared to the traditional thermal power generation, new energy sources, such as wind and photovoltaic systems, are more vulnerable to the effects of non-ideal power grids due to their limited capacity. This susceptibility can jeopardize the safe operation of power equipment, degrade power output quality, and lead to non-compliance with grid-connected specifications. The LCL-type grid-connected inverter is a typical nonlinear system that weakens the controllability of the grid-connected energy. To address these challenges, this study employs feedback linearization theory to transform the inverter into a standard linear system. Subsequently, it utilizes linear system methodologies to develop robust control laws, ultimately introducing a multi-functional multiplexing control strategy for grid-connected inverters based on feedback linearization and Hamilton-Jacobi-Issacs inequality. Simulation results demonstrate that this multi-functional strategy outperforms traditional grid-connected inverter control schemes, effectively mitigating issues related to low short-circuit ratios, voltage fluctuations, imbalances, harmonics, and other non-ideal grid conditions. Furthermore, it significantly expands the system’s adaptability to varying weak grid impedances.

Integrated Systems of a Solar Thermal Energy Driven Power Plant

Integrated Systems of a Solar Thermal Energy Driven Power Plant

Thermal Energy-Kinetic Energy Conversion Efficiency Analysis Method Based on Grey Cluster Analysis

At this stage, although thermal power generation is still the main method of power generation in my country’s power plants, due to more and more energy consumption, the reserves of resources are gradually beginning to be stretched. Application in the power generation and production process of thermal power plants has become a road that more and more power plants must explore for development. In this paper, through the grey cluster analysis, the power plant can fully improve the power generation efficiency of the power plant in the process of utilizing the existing energy, so as to achieve the purpose of energy saving and environmental protection. Combined with the connotation of thermal energy-kinetic energy conversion, this paper establishes a theoretical framework for the analysis method of thermal energy-kinetic energy conversion efficiency based on grey cluster analysis. On the basis of theoretical research, using descriptive statistical tools, the main performance of thermal energy-kinetic energy conversion to promote economic growth is summarized. The realization method of gray cluster analysis theory is to identify and process the external features of gray information, capture effective information, and quantify the features (ie, whitening process), so as to complete the evaluation or decision-making, and verify the effect of these five mechanisms on economic growth. The final results of the study show that when K=1, 2, 3 and 4, the proportion of heat transfer is 41.63%, 42.19%, 49.63% and 52.13%, and the proportion of heat convection is 37.56% and 41.33%, respectively., 29.69% and 26.78%, the heat transfer and heat convection have the greatest influence on the thermal energy-kinetic energy conversion efficiency.

Research on optimal dispatching strategy of solar thermal-photovoltaic-wind combined power generation system

New energy photovoltaic generation of electricity and wind power have developed rapidly, and the installed capacity has been increasing, but their volatility and randomness have also caused a certain impact on the power grid. Considering that solar thermal power generation and photovoltaic power generation have natural complementary advantages, and solar thermal power generation and power output of wind power can complement each other in time., this paper proposes an optimal scheduling strategy for solar thermal-photovoltaic-wind alliance power generation system, which uses thermal storage device of the heat power station of solar energy to cope with the problem of wind and light abandonment of new energy power generation and promote the consumption level of renewable energy. The economic and stability deviations of the system before and in the launch the solar thermal power station are compared in depth and the simulation is verified in the IEEE30 node system. The results show that after the introduction of solar thermal power (CSP) station in the combined power generation system, the economy of the scientific is remarkable improvement, the wind turbine is also reduced, which realizes the full absorption of new energy.

Capacity optimization allocation method of photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system based on SAO algorithm

The capacity optimization allocation of hybrid micro-energy systems is an important link in micro-energy systems, which can effectively improve the reliability and economy of the power grid. In this paper, the capacity optimization allocation method of a photovoltaic-temperature difference-hydrogen-storage hybrid micro-energy system is studied. First, a capacity optimization configuration model based on photovoltaic, temperature difference, and hydrogen storage hybrid micro-energy system was established to maximize revenue. Then, the SAO algorithm is used to optimize its strategy. When the strategy does not change, it indicates that the income has been maximized. Finally, concerning the snow ablation mechanism, it can balance development and exploration well and can optimize the global optimal solution even in a more complex environment. The proposed method can ensure the reliability under premise of relatively low cost, and effectively improve the rationality of the power grid capacity allocation method in the photovoltaic thermal power generation scenario.

Повышение энергетической эффективности газопоршневой ТЭС за счет комплексного использования тепловых вторичных энергоресурсов

Recently, the advantages and prospects to use piston gas internal combustion engines for the combined generation of electrical and thermal energy have become increasingly obvious. The range of single capacities of gas piston units (GPU) ranges from 0,1 MW to tens of MW, which makes them more attractive when designing various power facilities. Most brands of gas piston units can operate in co-generation mode, that is, as a combined heat and power plant that simultaneously generates electrical and thermal energy. The purpose of this study is to substantiate the possibility of integrated use of heat of the cooling systems of the gas piston engine of a thermal power plant (TPP). The studies conducted are carried out using well-known methods of thermodynamic calculation of the internal combustion engine cycle, of determination of the components of its thermal balance and thermal calculation of the equipment for utilization of secondary thermal energy resources. The results of the analysis of the heat losses of the GPU drive engine have showed that the total losses during its operation are about 11544,5 kW. Average potential heat losses with flue gases are 45,87 %, and low-potential heat losses with water in cooling systems and oil in lubrication systems are 53,14 %. A schematic diagram is proposed for the integrated utilization of thermal renewable energy resources (RES) at a gas piston thermal power plant. The main difference between the proposed scheme and the existing technical solutions is the utilization of the heat of the low-temperature charge air cooling system after the second section of the compressor and the heat of the engine lubrication system. An analysis of the expenditure part of the energy balance of the drive engine in case of the integrated use of thermal RES in the GPU cycle, has showed that the implementation of energy-saving measures will make it possible to usefully use up to 93,05 % of the supplied energy in the generation of electrical and thermal power.

Performance analysis and multi-objective optimization of the offshore renewable energy powered integrated energy supply system

Offshore renewable energy technologies offer a promising prospect for energy supply on offshore islands. However, traditional wind and solar energy sources exhibit strong variability and cannot fully meet the energy demands of users. At the same time, the energy demand of users also has great volatility, so the supply side and demand side of energy cannot match well. Existing renewable energy systems often utilize thermal power generation as a stabilizer for the system, however, this approach is difficult to apply in offshore conditions. This study introduces an innovative multi-energy complementary system that integrates seawater freezing desalination, refrigeration and power-hydrogen-ammonia co-generation, driven by ocean thermal energy, wind energy, and solar energy. The system incorporates the use of a new developed small temperature difference ejector refrigeration cycle to stabilize the entire system and produce low-temperature refrigeration. By utilizing the seawater freezing desalination process to minimize energy conversion losses and balancing fluctuations in multiple energy inputs and user demands through ammonia-hydrogen co-production, this approach effectively minimizes energy waste, enhances energy utilization efficiency, and reduces excess power handling. The purpose is to optimize the configuration of the energy conversion subsystem within the multi-energy complementary multi-effect co-generation system, thus improving the economic feasibility and reliability of the system in providing energy and freshwater supply, ultimately achieving the goals of reducing energy waste, achieving high conversion efficiency, and minimizing equipment investment. This study conducts an economic analysis and optimization of a multi-energy complementary system, utilizing a 2 MW-level OTEC subsystem as a stabilizer. Both equipment investment and operating costs are considered in the economy analysis. The carbon emission reduction performance of this system is evaluated. The performance optimization results show that the system achieves an energy storage efficiency of 65.96 %, and the curtailment rate of this system is only 3.99 %, significantly lower than the 10 % curtailment rate in traditional system. The proposed system can meet the annual electricity demand of 33.09 million kWh, as well as a cooling demand of 546.81 million kWh. Under typical conditions, the ocean thermal energy conversion cycle exhibits a power efficiency of 0.85 % and a refrigeration efficiency of 29.10 %. Meanwhile, it annually reduces CO2 emissions by 2.54 million tons, demonstrating significant environmental benefits. This proposed system is mainly applicable to tropical waters with high surface water temperatures and depths of no less than 600 m worldwide. This study offers a practical and economically beneficial solution for energy and freshwater supply on offshore islands.

Research on Key Technologies for Optimization of Water Systems and Efficient Utilization of Regenerated Water in Thermal Power Plants

Water is the source of life, an essential element in production, and the foundation of ecosystems. In the natural hydrological cycle, water that can be utilized by humans is referred to as water resources. Water resources form the basis for human survival and development, intimately connected to daily life, and concurrently represent a controlling factor in the ecological environment. It is well-known that the thermal power generation industry has consistently been a major consumer of water in the industrial sector, with substantial demands for water resources. Throughout the process of thermal power generation, water resources are extensively utilized for cooling, steam generation, waste heat discharge, and other processes. This large-scale utilization of water resources not only imposes pressure on local water resources but also leads to pollution of water environments and disruption of ecosystems.To address the challenges posed by the limited availability of water resources and environmental pollution, this paper explores the key technologies for optimizing water systems in thermal power plants. Through in-depth analyses of 3S water source optimization technology, ABFT biological treatment processes, recycled water utilization technology in the circulating cooling system, reclaimed water reuse technology, and the coal-fired "flue gas desulfurization" process, coupled with empirical studies of typical cases, the aim is to propose viable optimization solutions for water systems.

Fractional-Order Load Frequency Control of an Interconnected Power System with a Hydrogen Energy-Storage Unit

Modern power systems are confronted with widespread concern on the frequency stability issue due to the widespread integration of randomly fluctuating renewable resources. To address the above concern, this work introduces a load-frequency-control (LFC) scheme based on a parameter tuning strategy for fractional-order proportional–integral–derivative (FOPID) controller. Firstly, a two-area interconnected power system (IPS) model, including thermal, hydro, solar, wind, and gas power generator and a hydrogen-based energy-storage unit, is established. Then, a FOPID controller is designed for this IPS model, and an improved gradient-based optimizer (IGBO) is developed to adaptively regulate the parameters of the FOPID controllers. Finally, the effectiveness of the offered LFC scheme is tested through load disturbance and renewable energy fluctuations test scenarios and provides a comparison and robustness analysis among different schemes. The test results validated that the offered LFC scheme can effectively suppress the frequency fluctuations of the IPS and has excellent robustness.

Optimal stochastic power flow using enhanced multi-objective mayfly algorithm

For the classical multi-objective optimal power flow (MOOPF) problem, only traditional thermal power generators are used in power systems. However, there is an increasing interest in renewable energy sources and the MOOPF problem using wind and solar energy has been raised to replace part of the thermal generators in the system with wind turbines and solar photovoltaics (PV) generators. The optimization objectives of MOOPF with renewable energy sources vary with the study case. They are mainly a combination of 2–4 objectives from fuel cost, emissions, power loss and voltage deviation (VD). In addition, reasonable prediction of renewable power is a major difficulty due to the discontinuous, disordered and unstable nature of renewable energy. In this paper, the Weibull probability distribution function (PDF) and lognormal PDF are applied to evaluate the available wind and available solar power, respectively. In this paper, an enhanced multi-objective mayfly algorithm (NSMA-SF) based on non-dominated sorting and the superiority of feasible solutions is implemented to tackle the MOOPF problem with wind and solar energy. The algorithm NSMA-SF is applied to the modified IEEE-30 and standard IEEE-57 bus test systems. The simulation results are analyzed and compared with the recently reported MOOPF results.

Pollution Source Apportionment of Heavy Metals in Cultivated Soil Around a Red Mud Yard Based on APCS-MLR and PMF Models

In order to explore the characteristics and sources of heavy metal pollution in cultivated soil around a red mud yard in Chongqing， the content and spatial distribution characteristics of eight heavy metal elements （Cd， Cr， Hg， Ni， Pb， As， Cu， and Zn） in the soil were analyzed， and the single factor pollution index method and Nemerow comprehensive pollution index method were used to evaluate the characteristics of heavy metal pollution in soil. On the basis of correlation analysis， the APCS-MLR and PMF models were used to quantitatively analyze the sources of heavy metals. The results showed that the average contents of the other seven heavy metal elements were higher than the background values of Chongqing soil， except for that of Cr. The heavy metals Cd， Hg， and As were moderately polluted， and Pb， Cu， Ni， and Zn were mildly polluted. The spatial distribution pattern of Cr， Ni， Pb， Cu， and Zn in the soil was similar， and there was a very significant positive correlation between them （P &lt; 0.01）. The spatial distribution characteristics of Cd， Hg， and As were significantly different， and there was no significant correlation between them （P &gt; 0.05）. The source apportionment showed that the sources of heavy metals in the soil in the study area were relatively complex， and the APCS-MLR and PMF models could identify the same four pollution sources， namely red mud yard percolation emission and natural sources， thermal power generation emission sources， agricultural activities and natural sources， and non-ferrous metal smelting emission sources. There was little difference in the results of source apportionment between the two models. The contribution rates of the four pollution sources in the APCS-MLR model were 51.8%， 18.0%， 15.9%， and 14.3%， respectively， whereas those in the PMF model were 45.9%， 12.8%， 21.5%， and 19.8%， respectively.

Analysis of the Operating Characteristics of a Photothermal Storage Coupled Power Station Based on the Life-Cycle-Extending Renovation of Retired Thermal Power Units

Analysis of the Operating Characteristics of a Photothermal Storage Coupled Power Station Based on the Life-Cycle-Extending Renovation of Retired Thermal Power Units