Thermal Power Plants In China Research Articles

Carbon emission trading, carbon efficiency, and the Porter hypothesis: Plant-level evidence from China

Focusing on large thermal power plants in China, we examine the causal effect of carbon emission trading scheme (CETS) on their carbon emission efficiency. Using the staggered installation of CETS pilots as a natural experiment, we show that carbon emission trading significantly improves power plants’ carbon efficiency. Specifically, the CETS leads to a 6.9 % increase in carbon efficiency. The carbon efficiency growth effects are stronger for plants that are not state-owned, large in scale, or plants located in regions with high level of marketization. Moreover, the improvement in carbon efficiency mainly comes from the reduction in carbon emission, not the improvement in power generation level. The mechanism analysis indicates that the implementation of CETS increases the number of granted patents by as much as 23 %, which provides supporting evidence for the Porter hypothesis.

Calculation method of CO2 emission of thermal power plant in China

With the proposal of carbon dioxide peak in 2030 and carbon dioxide neutrality by 2060, more and more concern are shown in fossil fuel power plants. Since coal-fired power plant takes more than 90% in China of the power supplying side, discussion of how the CO2 trading quota is calculated and how to confirm the amount of CO2 seem emergency in CO2 neutrality area. This paper introduced the calculation method of CO2 trading quota and actual emission amount from the government document and present a calculation example with the operation data from a 300MW coal-fired power plant for reference.

Cost-benefits analysis of ultra-low emissions standard on air quality and health impact in thermal power plants in China

As China's largest energy infrastructure, thermal power plant consumed approximately half of China's coal over the past decade and threatened air quality, human health and socioeconomic development. Thus, a series of control policies have been implemented to alleviate those impacts in China. Particularly, China has witnessed unprecedented declines in air pollutant emissions from thermal power plants since the ultra-low emissions (ULE) standards were implemented. In contrast, the effect of the ULE policy on air quality, health and cost benefits remains poorly understood. Therefore, this study estimates the improved air quality and associated health and economic benefits under the ULE standards in the thermal power sector by using a measure-specific approach, combining a bottom-up emission inventory, an atmospheric model, a health assessment model and a cost analysis model. The results show that all the control measures lead to reduced air pollution, and renovating pre-existing units (RPU) is the most effective. Compared to without implementing the ULE policy, the population-weighted average PM2.5 and O3 concentrations decreased by 1.50 μg/m3 and 0.87 ppm, and 67,831 premature deaths could be avoided nationally. Furthermore, the results also show the net economic benefits of combining health benefits and costs due to control measures are 109.92 billion Yuan (in 2015 value) in China. The comprehensive results reveal that the health benefits outweigh the direct policy. Based on these empirical findings and the specific circumstances of China, we suggest that RPU should be further promoted to the entire of China, and if necessary, establish a long-term compensation mechanism for inter-provincial interests and institute and enforce comprehensive policies that carefully consider the health impacts of policies. This study provides strong arguments for China's policy-making and considering tightening emission standards for thermal power plants worldwide.

Low-carbon development pathways for provincial-level thermal power plants in China by mid-century

Phasing out thermal power plants is vital to combatting climate change. Less attention has been given to provincial-level thermal power plants, which are implementers of the policy of phasing out backward production capacity. To improve energy efficiency and reduce negative environmental impacts, this study proposes a bottom-up cost-optimal model to explore technology-oriented low-carbon development pathways for China's provincial-level thermal power plants. Taking 16 types of thermal power technologies into consideration, this study investigates the impacts of power demand, policy implementation, and technology maturity on energy consumption, pollutant emissions, and carbon emissions of power plants. The results show that an enhanced policy combined with a reduced thermal power demand would peak carbon emissions of the power industry at approximately 4.1 GtCO2 in 2023. Meanwhile, most of the inefficient coal-fired power technologies should be eliminated by 2030. Carbon capture and storage technology should be gradually promoted in Xinjiang, Inner Mongolia, Ningxia, and Jilin after 2025. Energy-saving upgrades on 600 MW and 1000 MW ultra-supercritical technologies should be emphatically carried out in Anhui, Guangdong, and Zhejiang. By 2050, all thermal power will come from ultra-supercritical and other advanced technologies.

Impact of PM10 Particles on the Measurement Error of SO2 Electrochemical Gas Sensor

To address the problems of poor measurement accuracy and long service life of SO2 electrochemical gas sensors when used in thermal power plant areas, fly ash emitted from a thermal power plant in China was used as the research object. Based on the analysis of the morphological characteristics of fly ash particles, theoretical calculations were used to obtain the settling speed of fly ash particles and the amount of fly ash deposited at different times, and then the impact of fly ash on the measurement error of a SO2 electrochemical gas sensor was investigated by experimental tests. The research results show that the particle size distribution of fly ash is 2–11 μm, the average settling speed of fly ash particles is 1.34 × 10−3 m/s, and the deposition amount of fly ash on the surface of the sensor inlet film is 0.95 mg per day. The deposition time of fly ash affects the sensor measurement error, and the longer the deposition time, the larger the sensor measurement error, which is due to the reduction of gas diffusion area S and diffusion coefficient K in the sensor caused by fly ash deposition. Fly ash deposition has a greater impact on the sensor when measuring low concentration gases. The higher the gas concentration, the lower the measurement error, because the higher the gas concentration, the faster the gas reaches the working electrode area and the higher the effective SO2 concentration detected in the limited response time. When using SO2 electrochemical sensors in environments with high concentrations of fly ash or dust, it is recommended to install dust-proof devices (such as air-permeable filter membranes with a pore size of less than 4 μm) and regularly clean the deposited fly ash, which can improve the accuracy of the sensor measurement and extend the service life.

Corrosion inhibition of hydrazine on carbon steel in water solutions with different pH adjusted by ammonia

Abstract The ammonia-hydrazine shutdown protection method is widely used in thermal power plants in China because of its good protective performance. However, the toxicity and safety of hydrazine have restricted its use in many power plants, and it is necessary to improve the shutdown protection techniques. In this paper, electrochemical impedance spectroscopy and potentiodynamic polarization curves were used to study the effect of hydrazine in water solutions of different pH values, adjusted with ammonia on the corrosion behavior of carbon steel. It was found that in the water solution without hydrazine, the corrosion resistance of a carbon steel electrode increased with raising the pH. When the pH value of water increased to 10.5, the impedance value of the carbon steel increased significantly, the corrosion current density decreased from 26.06 μA·cm−2 at pH 10.0 to 2.36 μA·cm−2, and the steel surface was passivated. Hydrazine had different effects on the electrochemical corrosion behavior of carbon steel in water solutions with various pH. When the pH of water was not higher than 10.0, hydrazine had a good corrosion inhibition effect on carbon steel. When the pH of water was not lower than 10.5, the addition of hydrazine inhibited the passivation of carbon steel and promoted the corrosion. The adsorption and substitutional oxidation of hydrazine in the anode region of carbon steel surface should be the reasons for the above phenomenon.

Measuring Environmental Performance of Provincial Thermal Power Plants in China: A Malmquist DEA Approach with Fixed-Sum Undesirable Outputs

Measuring Environmental Performance of Provincial Thermal Power Plants in China: A Malmquist DEA Approach with Fixed-Sum Undesirable Outputs

DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning

Optimizing the combustion efficiency of a thermal power generating unit (TPGU) is a highly challenging and critical task in the energy industry. We develop a new data-driven AI system, namely DeepThermal, to optimize the combustion control strategy for TPGUs. At its core, is a new model-based offline reinforcement learning (RL) framework, called MORE, which leverages historical operational data of a TGPU to solve a highly complex constrained Markov decision process problem via purely offline training. In DeepThermal, we first learn a data-driven combustion process simulator from the offline dataset. The RL agent of MORE is then trained by combining real historical data as well as carefully filtered and processed simulation data through a novel restrictive exploration scheme. DeepThermal has been successfully deployed in four large coal-fired thermal power plants in China. Real-world experiments show that DeepThermal effectively improves the combustion efficiency of TPGUs. We also report the superior performance of MORE by comparing with the state-of-the-art algorithms on the standard offline RL benchmarks.

Improving carbon emission performance of thermal power plants in China: An environmental benchmark selection approach

The power generation in China mainly relies on thermal power plants, which burn a lot of energy and then produce a lot of environmental pollutants including CO2. The thermal power plants put great pressures on environmental governance. Therefore, improving carbon emission performance of thermal power plants is of great importance for China to achieve the goals of carbon peaking and carbon neutrality. With this in mind, this study aims to explore the research question: How to improve the carbon emission performance of thermal power plants in China? To answer this question, an environmental benchmark selection approach is introduced. Then, an experiment is conducted with the production data of thermal power plants in 30 provinces in China in 2019. The result shows that 10 out of 30 provinces are efficient, and the overall carbon emission situation has been improved in 2019. However, the total carbon emission in China is still large, and many provinces need to decrease their energy consumption to improve carbon emission performance. Finally, some policy implications are given.

CO2 Reduction Potential from Efficiency Improvements in China’s Coal-Fired Thermal Power Generation: A Combined Approach of Metafrontier DEA and LMDI

Among the G20 countries, China is the only country to experience an increase in electricity generation from coal-fired thermal power plants from 2019 to 2020. This study aims to develop an analytical framework combining metafrontier data envelopment analysis with the logarithmic mean Divisia index for a detailed decomposition analysis of ‘mass-based’ energy-related CO2 reduction potential through efficiency improvements in coal-fired thermal power plants in China. The results show that inefficiency in power generation can be largely attributed to differences in the location of power plants and the production scale. Moreover, the impact of regional heterogeneity on the changes in power generation efficiency is more notable for the small–medium power plants in the northeast region than the large power plants in the western region in China. However, when focusing on the mass-based CO2 reduction potential associated with the regional heterogeneity, its positive effects in the western region for the large power plants are 6.2 times larger than that in the northeast region for the small–medium power plants. These results imply that an analysis that focuses only on the efficiency score would ignore the production scale of coal-fired thermal power plants and thus would fail to properly evaluate the environmental impacts associated with efficiency changes.

Anomaly detection and early warning via a novel multiblock-based method with applications to thermal power plants

The accurate and timely detection of anomalous conditions are essential for the safe and economical operation of complex thermal power plants (TPPs). However, the development of an excellent anomaly detection model without sufficient fault data is difficult in practice. In addition, global-based detection methods can submerge local anomalous behavior, causing serious delays in providing early warning of anomalous conditions. To solve this issue, a multiblock detection method based on the framework of evidence theory is proposed in this study. Measured variables collected from different units are automatically divided into several subblocks by using mutual information (MI)-based spectral clustering. Then, an evidential k-nearest neighbors algorithm (EKNN) is developed in each block, and local detection results are calculated. To provide an intuitionistic indication, the Dempster–Shafer rule is adopted to fuse the detection results of all the subblock EKNN models. The proposed approach can be applied to linear and nonlinear processes on the basis of MI and the nonparametric k-nearest neighbors procedure. To confirm its effectiveness, the proposed method is validated on samples collected from an ultra-supercritical TPP in China.

The use of fiber made from fly ash from power plants in China in road and airfield construction

The relevance of the study is due to the modern production being focused on the development of efficient materials that would provide for the minimum consumption of raw materials, a decrease in its cost and energy during the production and direct use of secondary resources. That is because recycling, disposal, neutralization and collection of industrial waste are one of the most pressing environmental problems. The aim of this work is to consider the feasibility of using fiber from fly ash from thermal power plants in China in the main types of asphalt concrete pavements. The results of the research have shown that the fiber from fly ash from thermal power plants is added to all purpose concrete mixtures for structural strength, impact toughness, reducing shrinkage and to prevent cracking, increase durability and resistance to abrasion. Concrete with the addition of fiber becomes water-resistant, frost-resistant (frost-resistance can increase up to 100 cycles), heat-resistant. The practical task is to solve environmental problems, such as assaving significant amounts of fuel in the production of building materials and energy; and conserving natural resources.

Refined modeling calculation of electromagnetic fields when lightning strikes thermal power plant and optimized layouts of sensitive devices

Lightning strikes thermal power plant will affect the normal operation of sensitive devices. However, due to the complex structure of thermal power plant, the calculation of electromagnetic field distribution is not accurate, and there is a lack of lightning protection specifications for low-voltage systems. Firstly, taking a thermal power plant in China as the object, an electromagnetic model of the low-voltage system including large irregular grounding grids, transformers, distribution lines, overhead cable trays, and external lightning protection systems is established, and a calculation method suitable for spatial electromagnetic fields of the complex model of thermal power plant is proposed. Secondly, the method is applied to the calculation of the maximum value of the magnetic fields at different layers, and the results show that the calculation accuracy is greatly improved. Finally, a method for optimizing the spatial layouts of sensitive devices in thermal power plant is proposed. This article provides data support for the design specifications and standards for lightning protection of low-voltage systems in thermal power plant. The spatial layouts of sensitive devices are optimized to achieve the purpose of rational use of building spatial and saving engineering costs.

Measuring environmental efficiency of thermal power plants in China: an improved Malmquist-Luenberger index with materials balance principle.

Improving environmental efficiency of thermal power plants is a crucial way to realize green and sustainable development. This paper investigates environmental efficiency of thermal power plants in China in 2011, 2013, and 2015 by conceptualizing a modified super-efficiency slacks-based measure with materials balance principle (MBP), which also eliminates the infeasibility in Malmquist-Luenberger index (MLI). An improved MLI is proposed based on the new efficiency measure. The results show that (1) the thermal power plants in most provinces have high environmental efficiency and productivity. (2) The improvement of productivity mainly originates from technical progress. This study provides a new perspective for environmental efficiency measurement on thermal power plants and advances related studies by (1) considering the first law of thermodynamics and introducing MBP in measuring environmental efficiency of thermal power plants and (2) defining a new MLI that captures the efficiency change and technical change in a super-efficiency framework. The thermal power plants in China can improve their environmental performance based on the results of current study.

Oxidation damage and interfacial failure of dissimilar metal welds containing ferritic heat resistant steels

The ex-service steam tubes containing dissimilar metal weld (DMW) between high Cr ferritic steel T91 and austenitic stainless steel TP347H and the ex-service steam tubes containing DMW between low Cr ferritic steel G102 and austenitic stainless steel TP347H were obtained from coal-fired thermal power plants in China, and their microstructures at the nickel-based weld metal (WM)/ferritic steel interfaces and oxidation characteristics were investigated. After operating for 15,000 h at steam temperature of 541 °C and steam pressure of 17.5 MPa, a G102/TP347H DMW failed along the WM/G102 steel interface, which was a dangerous premature failure mode without obvious plastic deformation. This interfacial failure was attributed to the interaction between oxidation and cracking along the interface, where fracture appeared to be related with the strain concentration at the interface. Oxide notch along the WM/G102 steel interface was the precursor of premature interfacial failure of DMW involving G102. For the DMW involving high Cr ferritic steel T91, ferritic steel side could form a Cr-rich passive film during service and thus would not be further oxidized after operating for 67,000 h at steam temperature of 541 °C and steam pressure of 3.5 MPa. It was concluded that oxidation played a more important role in failure of these DMWs, and retarding the development of oxidation and avoiding the interfacial oxide notch would dramatically improve the service performance of steam tubes containing DMWs.

Cost-benefit comparison of carbon capture, utilization, and storage retrofitted to different thermal power plants in China based on real options approach

A trinomial tree model based on a real options approach was developed to evaluate the investment decisions on carbon capture, utilization, and storage (CCUS) retrofitted to the three main types of thermal power plants in China under the same power generation and CO2 emissions levels. The plant types included pulverized coal (PC), integrated gasification combined cycle (IGCC), and natural gas combined cycle (NGCC) plants. We take into account a subsidy policy consistent with the 45Q tax credit of the U.S., as well as uncertainty factors, such as carbon price, technological progress, CO2 geological storage paths, oil price, and electricity price. The results showed that the investment benefit of ordinary NGCC power plants is 93.04 million USD. This provides greater economic advantages than the other two plant types as their investment benefit is negative if the captured CO2 was used for enhanced water recovery (EWR), even if 45Q subsidies are provided. Compared with NGCC + CCUS power plants, PC + CCUS and IGCC + CCUS power plants have more advantages in terms of economic benefits and emission reduction. The 45Q subsidy policy reduced the critical carbon price, which determines the decision to invest or not, by 30.14 USD t−1 for the PC and IGCC power plants and by 15.24 USD t−1 for the NGCC power plants. Nevertheless, only when the subsidy reaches at least 71.84 USD t−1 and the period limit is canceled can all three types of power plants be motivated to invest in CCUS and used the capture CO2 for EWR. Overall, the government should focus on the application of CCUS in coal-fired power plants (in addition to developing gas power generation), especially when CO2 is used for enhanced oil recovery (EOR). The government could introduce fiscal policies, such as 45Q or stronger, to stimulate CCUS technology development in China.

Sources of inefficient power generation by coal-fired thermal power plants in China: A metafrontier DEA decomposition approach

China is the world's largest CO2 emitting country, and coal-fired thermal power generation accounted for over 50% of the total electricity generation in China in 2015. This study reports the changes in the power generation efficiency of coal-fired thermal power plants in China from 2009 to 2011 and elucidates how the differences in the production scale of the power plants and regional heterogeneity affect the power generation efficiency. We propose a metafrontier data envelopment analysis (DEA) decomposition framework to investigate the sources of inefficiency in power generation. The results suggest that, on average, the power generation efficiency of large-scale power plants is 13% higher than that of small-scale power plants. Although operational inefficiency is the main source of inefficiency in eastern and central China, the technology gap - the differences in the quality of coal consumed for electricity production and in the equipment of the power plants among regions - is the main source of inefficiency in western China. This study uses the results of the framework to discuss the scrapping policies for coal-fired thermal power plants in China. For large-scale power plants in western China, the components of inefficiency vary and, thus, policymakers should consider scrapping thermal power plants based not only on the level of inefficiency but also on their components.

Utilization of coal fly ash in China: a mini-review on challenges and future directions.

The rapid economic development in China places a large demand for energy, and as a result, thermal power plants in China are producing an enormous amount of coal fly ash (CFA) which causes severe environmental pollution. This paper briefly describes the current production and utilization status of CFA in China and identifies the challenges confronting sustainable CFA utilization as the Chinese economy is being transformed. These issues include a regional imbalance in supply and demand, reducing demand in the real estate industry as well as stricter laws for environmental protection. Viable directions for future CFA utilization are proposed, for example, production of CFA-based ceramic tiles, recovery of elemental resources, agricultural melioration, treatment of wastewater and flue gas, and production of high-volume CFA concretes. This paper has some guiding significance for sustainable and cleaner utilization of CFA in China and even worldwide. Graphical abstract.

Using Sparse Representation to Detect Anomalies in Complex WSNs

In recent years, wireless sensor networks (WSNs) have become an active area of research for monitoring physical and environmental conditions. Due to the interdependence of sensors, a functional anomaly in one sensor can cause a functional anomaly in another sensor, which can further lead to the malfunctioning of the entire sensor network. Existing research work has analysed faulty sensor anomalies but fails to show the effectiveness throughout the entire interdependent network system. In this article, a dictionary learning algorithm based on a non-negative constraint is developed, and a sparse representation anomaly node detection method for sensor networks is proposed based on the dictionary learning. Through experiment on a specific thermal power plant in China, we verify the robustness of our proposed method in detecting abnormal nodes against four state of the art approaches and proved our method is more robust. Furthermore, the experiments are conducted on the obtained abnormal nodes to prove the interdependence of multi-layer sensor networks and reveal the conditions and causes of a system crash.

Efficiency evaluation of thermal power plants in China based on the weighted Russell directional distance method

China has the largest thermal power installed capacity worldwide, which has caused severe greenhouse gas emissions. To reduce the emissions and facilitate the development of energy savings and emission abatement, it is imperative to improve power-generating efficiency. In this paper, the nonparametric weighted Russell directional distance method (WRDDM) was used to evaluate the overall efficiency of thermal power plants in 30 provinces in China. The results show that the efficiency of East and North China is higher than that of Northeast and Southwest China. Furthermore, the correlations between scale, ownership and efficiency are discussed. The nonstate-owned plants with large generation capacity have a higher efficiency than the small and state-owned plants.