Chinese Power Plants Research Articles

A consensus reaching model for expert behavior-driven adjustment of expert weights based on picture fuzzy sets

This article proposes an expert-driven consensus and decision-making model that comprehensively considers expert behavior in Multi-criteria decision-making (MCDM) scenarios. Under the premise that experts are willing to adjust their viewpoints, the framework strives to reach group consensus to the utmost degree feasible. To tackle experts’ uncertainty during the evaluation process, this article employs the rejection degree in the picture fuzzy sets (PFS) to signify the level of ignorance while they deliver their evaluation opinions. Due to the diversity of expert views, reaching a group consensus is difficult in reality. Therefore, this article additionally presents a strategy for adjusting the weights of experts who did not reach consensus. This approach upholds data integrity and guarantees the precision of the ultimate decision. Finally, this article confirms the efficiency of the aforementioned model by means of a case study on selecting the optimal carbon reduction alternative for Chinese power plants.

Convolutional Deep Belief Network Based Expert System for Automated Fault Diagnosis in Hydro Electrical Power Systems

The paper developed an approach for fault diagnosis in Hydro-Electrical Power Systems (HEPS). Using a Renewable Energy System (RES), HEPS has performed a significant part in contributing to addressing the evolving energy demands of the present. Several electro-mechanical elements that collectively comprise the Hydro-Electric (HE) system are susceptible to corrosion from routine usage and unplanned occurrences. Administration and servicing systems that are successful in implementing and achieving these goals are those that regularly track and predict failures. Detect models applied in the past included those that were primarily reactive or reliant on human involvement to identify and analyse abnormalities. The significant multiple variables intricacies that impact successful fault detection are disregarded by these frameworks. The research presented here proposes a Convolutional Deep Belief Network (CDBN) driven Deep Learning (DL) model for successful fault and failure detection in such power systems that address these problems. Applying sample data collected from two Chinese power plants, the proposed framework has been assessed compared to other practical DL algorithms. Different metrics have been employed to determine the effectiveness of the simulations, namely Accuracy, Precision, Recall, and F1-score. These outcomes indicated that the CDBN is capable of predicting unexpected failures. Graphic representations demonstrating control used to measure turbine blade load, vibration level, and generator heat for assessing the replicas.

Analyzing the current state and future development of carbon capture, utilization and storage (CCUS) strategies and technologies in China

Carbon capture, utilization, and storage (hereafter as CCUS) encompass the procedures of capturing carbon dioxide before it is emitted into the atmosphere, transporting it via pipelines or vehicles and finally utilizing it or storing it in a secure manner. CCUS is vital in transitioning the world into more sustainable and low carbon energy production since it serves as a temporary “band-aid” in reducing the impacts of humanity’s high dependence on fossil fuels. The Chinese government has recently committed itself to reach carbon neutrality by 2060 and CCUS technologies will be a critical cornerstone in reaching this substantial goal. Up to 60% of China’s energy supply in 2019 derived from coal, thus an effective CCUS strategy integrated with the 1,110 operational Chinese coal power plants could be decisive in reaching their carbon neutrality goal. This research paper will analyze the most effective best available technologies (BATs) in terms of cost efficiency and practicality, providing a comprehensive report on the optimal steps for China to take in order to reach its carbon neutral goals through CCUS.

Quantitative Analysis of Coal Quality by a Portable Laser Induced Breakdown Spectroscopy and Three Chemometrics Methods

Laser-induced breakdown spectroscopy (LIBS) technology has the characteristics of small sample demand, simple sample preparation, simultaneous measurement of multiple elements and safety, which has great potential application in the rapid detection of coal quality. In this paper, 59 kinds of coal commonly used in Chinese power plants were tested by a lab-designed field-portable laser-induced breakdown spectrometer. The data set division methods and the quantitative analysis algorithm of ash content, volatile matter and calorific value of coal samples were carried out. The accuracy and prediction accuracy of three kinds of dataset partitioning methods, random selection (RS), Kennard–Stone (KS) and sample partitioning based on joint X-Y distances (SPXY), coupled with three quantitative algorithms, partial least squares regression (PLS), support vector machine regression (SVR) and random forest (RF), were compared and analyzed in this paper. The results show that the model featuring SPXY combined with RF has the best prediction performance. The R2 of ash content by the RF and SPXY method is 0.9843, the RMSEP of ash content is 1.3303 and the mean relative error (MRE) is 7.47%. The R2 of volatile matter is 0.9801, RMSEP is 0.7843 and MRE is 2.19%. The R2 of calorific value is 0.9844, RMSEP is 0.7324 and MRE is 2.27%. This study demonstrates that the field-portable LIBS device combining appropriate chemometrics algorithms has a wide application prospect in the rapid analysis of coal quality.

Empirical analysis of Chinese overseas power plant investments: Likelihood of suspensions and associated environmental risks

Power sector investment is crucial to accelerate a sustainable energy transition, but not all investments are successful. We examine 1,393 Chinese overseas electric power projects across 78 countries over the past two decades. We identify 5% that have been canceled or delayed, with coal and hydro projects having much higher suspension rates than solar and wind projects. We find electric projects with higher environmental risks are more likely to be suspended. Specifically, coal projects located in more densely populated areas where more people are exposed to air pollutants, in countries with more fatalities from extreme weather events, and in places with a record of environmental protests, are more likely to be suspended. Additionally, hydro projects closer to protected areas have a higher suspension rate. Our results suggest that refraining from investing in environmentally risky projects helps mitigate environmental damages and prevents financial losses due to cancellation and postponement.

The joint impact of the carbon market on carbon emissions, energy mix, and copollutants

From a comprehensive standpoint, this paper investigates whether and to what extent the carbon market functions in the context of the developing world. Taking advantage of a unique seven-year-plant-level panel dataset (2010–2016) on Chinese power plants, we use a matched difference-in-differences strategy to identify the joint impact of China’s carbon emissions trading (CET) pilot policy on carbon emissions reduction (objective), energy mix improvement (mechanism), and air copollutant reduction (cobenefits). We find that China’s CET pilot policy effectively lowered carbon emissions by approximately 38.61%. Further analysis shows that plants reduce carbon emissions primarily by reducing coal consumption (approximately 30.79%). Most importantly, China’s CET pilot policy induces substantial air copollutant abatement benefits by reducing sulfur dioxide and nitrogen oxides by approximately 52.19% and 48.62%, respectively. State-owned plants are more affected by China’s CET pilot policy, and the policy effects show disproportionate environmental inequality. Furthermore, the effects are not affected by the rate-based allowance allocation structure that is adopted by China’s national carbon market.

Development of building materials based on a high content of fly ash and polycondensation products from Chinese heat and power plants

Abstract The addition of fly ash from thermal power plants (TPP) and chemical additives, such as polycondensation products of acetone and formaldehyde, is an effective and economical method for increasing the strength and durability of building materials, in particular concrete. Fly ash added to the concrete and mortars at 10%–15% does not reduce their technical properties, while polycondensation products of acetone and formaldehyde plasticize and accelerate the hardening process of concrete. The study aims to substantiate the possibility of obtaining concrete on dense aggregates with a high content of fly ash through the use of polycondensation products of acetone and formaldehyde as additives, which are highly soluble in water and polyfunctional. The strength indicators were determined using standard methods. The study has shown quantitative changes in the properties of the fly ash-concrete mixture, improvement of its physical and technical characteristics, and durability of the fly ash concrete with the addition of polycondensation products of acetone and formaldehyde. In the present study, the authors determine the effect of fly ash addition on the properties of a concrete mixture, as well as the maximum possible content of fly ash that can be added to concrete to maximize certain properties required of the mixture; additionally, the same action is conducted with the addition of polycondensation products of acetone and formaldehyde concomitant with the addition of fly ash.

Study on stable multi-layer molten pool experiment with internal heat generation in ERVC-IVR strategy

Since oxide and metal materials are not miscible and Uranium extraction, the molten reactor core could turn into a multi-layer configuration molten pool in the Reactor Pressure Vessel (RPV). Three-layeR cOupled heat tranSfer molten pool Experiment (TROSE) is established with a three-dimension hemispheric test section. Two preliminary tests are carried out, and these tests use water to simulate both the top and middle layers and Cerrobend alloy to simulate the bottom layer. TROSE results demonstrate that upward heat transfer direction is found at the interface of the middle and bottom layers, and the power split ratio of the middle layer is about 1.0. The top and middle layers have an increasing trend of sideward heat flux; however, the bottom layer shows a different trend due to crust formation. Generally, the calculated results of Churchill-Chu, BALI, and COPRA correlations are close to the experimental sideward heat flux of the different layers in the multi-layer configuration. This three-dimension study provides additional experiment data for the three-layer configuration in IVR strategy for a new Chinese passive nuclear power plant.

Drivers of air pollution reduction paradox: Empirical evidence from directly measured unit-level data of Chinese power plants

This research investigates the drivers of the paradox that air pollutant emissions have fallen in the Chinese electric power sector as coal combustion continues to play a dominant role. With directly measured unit-level air pollution emissions data from Chinese power plants during 2014–17, this study quantifies the contributions of eight factors to reducing three key air pollutants (sulfur dioxide, nitrogen oxides, and particulate matter) using the Logarithmic Mean Divisia Index model. The main results are presented for aggregates of the 10 wealthiest and 20 less wealthy provinces. The dominant driver of the fall in air pollution is the emission intensity of fossil fuel use, cutting air pollution by 69%–86% in the wealthier region and 65%–72% in the poorer region. Electricity consumption per unit of gross domestic product, the second largest contributor to air pollution reduction, has reduced the three key air pollutants emissions from power plants by 7%–9% and 11%–12% in the wealthier and poorer regions. Results suggest some policy implications; implementing end-of-pipe techniques cuts air pollution by lowering the emission intensity of fossil fuel use. Meanwhile, measures such as renewable energy generation subsidies reduce the fossil fuel intensity of electricity use and indirectly cut air pollution from power plants.

Trade shocks, industrial growth, and electrification in early 20th-century China

How does demand from the industrial sector promote the diffusion of electricity? Using newly digitized data on Chinese power plants from 1912 to 1935, we examine the impact of a trade shock, which protected the domestic manufacturing sector from import competition, on the adoption of electricity. To establish a causal relationship, we exploit time variations in imported manufactured goods caused by China's unexpected recovery of tariff autonomy in 1929 and cross-sectional variations in local access to treaty ports. We find that the reduction in manufactured imports resulted from the tariff shock led to the expansion of the local electricity sector. Further analysis suggests that the booming domestic industrial sector rather than population agglomeration was the key channel for the effect.

Beneficiation of coal ash from ash silos of six Chinese power plants and its risk assessment of hazardous elements for land application

The tremendous amount of ash produced from coal-fired power plants must be disposed and utilized in an economically and environmentally sustainable manner. This paper conducted a study on the beneficiation of silo ashes and the risk assessment for land use. Silo ash samples were collected from six Chinese power plants and segregated into five size fractions by a combination of sieving and air classification. The concentration distributions of nine hazardous elements (i.e., As, Cd, Cr, Cu, Hg, Ni, Pb, Se, and Zn) were characterized. The results show that the particle size distributions of hazardous elements in the silo ashes do not exactly agree with the generally accepted models of their release and partitioning in the boiler. Environmental risks were assessed for agricultural and development land use of coal ash, according to related Chinese standards. The results suggest that all the bulk ashes meet the requirements for development land use. Beneficially, for some coal ashes, the coarse fraction (> 10 µm) can be applied to agricultural land while the remaining fraction (< 10 µm) still complies with the standard for development land use. This work demonstrates that a simple air classification is potentially an eco-friendly and value-added approach for the full utilization of coal ash.

Drivers of Air Pollution Reduction Paradox: Empirical Evidence from Directly Measured Unit-Level Data of Chinese Power Plants

Drivers of Air Pollution Reduction Paradox: Empirical Evidence from Directly Measured Unit-Level Data of Chinese Power Plants

Fast Screening of Coal Fly Ash with Potential for Rare Earth Element Recovery by Electron Paramagnetic Resonance Spectroscopy.

Rare earth elements (REYs) are in increasing global demand, but their mining is costly and environmentally destructive. Coal fly ash (CFA) is a promising alternative source of REYs, but it is necessary to identify CFA with sufficiently high REY concentrations. This study proposes the use of electron paramagnetic resonance (EPR) spectroscopy as part of a simple method to identify CFAs with adequate REY concentrations. The EPR spectra of CFA samples taken from 186 Chinese commercial coal-fired power plants were analyzed. The results suggest that CFAs without evident 6-fold resonances are worth recycling (REY concentrations of 416 ± 108 mg/kg), while those with conspicuous 6-fold resonances are not worth recycling (REY concentrations of 55 ± 26 mg/kg). This is probably due to isomorphic substitution of Ca(II) for Mn(II) and REY(III), resulting in low concentrations of Mn(II) and REY(III) in Ca-rich CFAs. This EPR evaluation method does not require specialized sample preparation, professional skills, or secondary data analysis and has potential global significance in the fast screening of CFAs with REY-recycling potential.

Dynamic Reliability Evaluation of Diesel Generator System of One Chinese 1000MWe NPP Considering Temporal Failure Effects

Loss of power supply from the diesel generator system (DGS) after loss of offsite power (LOOP) will pose great threat to the safety of GEN-II pressurized water reactors (PWR). Therefore, it is very desirable to evaluate the DGS’s reliability. The traditional analyzing tools are limited to static approaches neglecting the dynamic sequence failure behaviors, such as reliability block diagram (RBD), static fault tree (SFT). Static reliability modeling techniques are not capable of capturing the dynamic sequence-dependent failure behaviors typically existing in NPP safety systems such as DGS, and thus often overestimate the unreliability of systems. In this paper, motivated to study the effects of sequence failure behaviors, dynamic fault tree (DFT) is applied to evaluate the reliability of the DGS of one Chinese 1000MWe Nuclear Power Plant (NPP), and an integrated two-phased Markov Chain model is also developed, which can be considered as a contribution of this article. Comparative study of DGS reliability between DFT and SFT is carried out. The results indicate that compared with the result derived from the DFT model, the unreliability of DGS calculated by SFT is greatly overestimated by about one to two orders of magnitude. Therefore, DFT has a potential to improve the economy of NPP by relaxing the overestimated unreliability of nuclear power systems.

The Enemy Within? Green Industrial Policy and Stranded Assets in China’s Power Sector

AbstractThis article examines potential interest group opposition to green industrial policies through the lens of state investment in China’s coal power sector. Using a novel data set on financial investments in Chinese coal power plants, we show that state actors have controlling stakes in the majority of nominally private coal plants. Importantly, the majority of such plants have investments from multiple levels of government. Green industrial policies could therefore face resistance from economic coalitions within the state, as state-owned coal plants and government agencies object to policies that harm their financial interests. Theoretically, this implies the need for a conceptualization of state capacity that allows for the ability to overcome internal opposition. Empirically, we highlight a predicament for the Chinese state: it has set ambitious goals to decarbonize but also has a vested interest in ensuring the profitability of the world’s largest coal-fired power generation fleet.

Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

Option to survive or surrender: Carbon asset management and optimization in thermal power enterprises from China

Carbon emission right allowance is a double-edged sword, one edge is to reduce emission as its original design intention, another edge has in practice slain many less developed coal-consuming enterprises, especially for those in thermal power industry. Partially governed on the hilt in hands of the authority, body of this sword is the prices of carbon emission right. How should the thermal power plants dance on the blade motivates this research. Considering the impact of price fluctuations of carbon emission right allowance, we investigate the operation of Chinese thermal power plant by modeling the decision-making with optimal stopping problem, which is established on the stochastic environment with carbon emission allowance price process simulated by geometric Brownian motion. Under the overall goal of maximizing the ultimate profitability, the optimal stopping indicates the timing of suspend or halt of production, hence the optimal stopping boundary curve implies the edge of life and death with regard to this enterprise. Applying this methodology, real cases of failure and survival of several Chinese representative thermal power plants were analyzed to explore the industry ecotope, which leads to the findings that: 1) The survival environment of existed thermal power plants becomes severer when facing more pressure from the newborn carbon-finance market. 2) Boundaries of survival environment is mainly drawn by the technical improvements for rising the utilization rate of carbon emission. Based on the same optimal stopping model, outlook of this industry is drawn with a demarcation surface defining the vivosphere of thermal power plants with different levels of profitability. This finding provides benchmarks for those enterprises struggling for survival and policy makers scheming better supervision and necessary intervene, and the methodology developed in this paper provides a research paradigm for enterprise survival analysis.

The sources of regulated productivity in Chinese power plants: An estimation of the restricted cost function combined with DEA approach

China's fossil fuel electric power industry, a traditionally energy- intensive industry, is the focus of recent environmental regulation. In this paper, we propose a framework to measure the effect of environmental regulation on power plants. First, we use the non-parametric distance function to construct the regulatory stringency index with DEA for specific fossil fuel electric power plants. Second, we incorporate the proposed regulatory stringency index into the restricted cost function, to estimate the environmental regulation effect on power plants, including the effect on productivity and elasticities of substitution. This approach allows us to overcome the problem of the data unavailability. Results indicate that there is an approximate U-shaped effect of environmental regulation on productivity growth. Productivity growth is mainly driven by technological progress. The substitution possibility between capital and energy is a good sign for Porter hypothesis in China. These findings provide policy implications for power plants to carry out environmental regulation and improve production performance.

Is solar power renewable and carbon-neutral: Evidence from a pilot solar tower plant in China under a systems view

Solar power has been widely treated as renewable and carbon-neutral for being free of fossil resource inputs and causing no carbon emissions. Recent studies, however, qualitatively challenged the traditional thinking derived under a local-realism-based perspective. In response to the recent concerns, this study as a continuation of a previous work offers a systems view into comprehending the ‘renewable’ and ‘carbon-neutral’ characters of solar power by the case of a Chinese pilot solar power plant. Under the systems view, a solar power plant is positioned as an organic system fed by ‘nutrients’ from the macro economy that relies on exogenous non-renewable energy resources as environmental support. A quantitative framework for evaluating the renewability and carbon-neutrality of solar power systems is proposed. A package of indicators is also devised, together with a retrospect of the history of methodological development. The non-renewable energy cost is revealed to be in magnitude 1.6 times as much as the electricity produced and the carbon emissions induced are also shown to be remarkable, implying that solar power is not as renewable and carbon-neutral as generally perceived. In contrast to coal-based power, however, solar power still appears as a promising alternative: the non-renewable energy cost and carbon emission for per unit of electricity delivered are revealed as 55% and 64% of that by the reference coal-fired power generation system in China, respectively. The outcome of this work provides a well-adapted assessment framework and adds insights into the intuitive understanding of renewable-based electricity.

Utilization of Boiler Slag from Pulverized-Coal-Combustion Power Plants in China for Manufacturing Acoustic Materials

The potential utilization of boiler slag generated in large amounts from pulverized-coal-combustion (PCC) power plants has recently drawn much attention due to the serious problems caused to ecosystems. In order to make maximal use of the boiler slag and reduce the environmental risk it poses, this study focused on manufacturing acoustic materials using boiler slag from Chinese PCC power plants. Three promising acoustic materials were successfully manufactured from up to 80% boiler slag with different grain sizes, with the addition of 20% Portland cement. The density and compressive strength of the products were inversely proportional and the sound absorption coefficient was positively proportional to the grain size of the boiler slag. The best sound absorption coefficient was obtained in products made from the coarsest fraction of the boiler slag (MS-C). Nonetheless, all the boiler-slag-based acoustic products still demonstrated compressive strength and densities comparable to those of other acoustic materials made of Spanish bottom ash or other conventional/recycled materials. The acoustic products made from the coarsest fraction (MS-C) and medium fraction (MS-M) of the boiler slag presented good noise absorption characteristics, like those of the commercial coarse porous cement that is traditionally used as an acoustic product. Furthermore, the acoustic products were characterized by very low leach ability of potentially hazardous elements. Consequently, the manufacture of acoustic materials is a very promising application for boiler slag. On the one hand, it consumes huge amounts of boiler slag that is generated in large amounts in China. On the other hand, the acoustic products can be used extensively to produce road acoustic barriers with a high sound absorption efficiency, no significant physical or mechanical limitations and no environmental implication.