Electric Power Industry In China Research Articles

A spatiotemporal analysis of personal casualty accidents in China's electric power industry

The electric power industry in China has experienced significant growth in recent years. Despite efforts to improve safety management in the industry, accidents still occur frequently. This study aimed to analyze the personal casualty accidents in the electric power industry from 2012 to 2021. Specific methods used include descriptive analysis, principal component analysis, and Theil index model. The results indicated that fall, electric shock, and collapse were the primary types of accidents, accounting for 59.65 % of all accidents. Accidents were higher in April and August, but lower in February. While the accident rate was relatively low on Mondays, the fatality rate was higher on Mondays, Thursdays, and Fridays. Taking into account accidents, workload, and labor, we found that Ningxia, Hainan, and Guangxi exhibited subpar levels of safety management within the electric power industry. The overall difference in the number of deaths in 31 provinces was significant in 2012 and 2016. It was significantly reduced in 2021. In terms of the proportion of intraregional and interregional differences, there were significant differences in the number of accidents and fatalities between provinces in the Central China and North China regions. This study provides valuable insights for enterprises to formulate accident prevention strategies and for the government to develop relevant policies.

Spatial spillover effect of environmental regulation on environmental efficiency of electric power industry in China

The electricity power (EP) industry, a primary source of emissions, significantly affects China's energy conservation and reduction efforts. The Chinese government has introduced various regulatory policies to limit the emissions and waste generated by the EP industry. This paper intends to assess the influence of environmental regulation (ER) on the environmental efficiency (EE) within China's EP sector, particularly concerning spatial spillover effects. The slack-based and the spatial Durbin models are applied to quantify EE and analyze the nonlinear connection between ER and EE. Some findings are summarized below. First, the EE of China's EP industry has significant regional heterogeneity and exhibits a positive spatial agglomeration effect of EE. Second, the influence of ER on EE in local provinces shows a U-shaped relationship, while it exhibits an inverted U-shaped effect in neighboring provinces. Third, ER can indirectly drive EE in the local province by affecting technological innovation. Finally, policy recommendations are offered to enhance the EE in China's EP industry.

Influence mechanism of technological innovation of electric power industry on carbon emission reduction in China

PurposeThis study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.Design/methodology/approachThis study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.FindingsPower technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.Research limitations/implicationsThis study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.Practical implicationsThis study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.Social implicationsRelevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.Originality/valueThis study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

Evaluation and Analysis of Electric Power in China Based on the ARMA Model

With the rapid development of China’s economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China’s electricity consumption, this paper analyzes the data characteristics of China’s electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China’s power demand from 2004 to 2019, the ARMA time series model is used to analyze China’s future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China’s electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China’s power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China’s power.

Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model

Operational efficiency analysis is the foundational work for the management policy adjustment of the electric power industry in China and many other countries, but it is difficult to conduct because of the system complexity. This research uses a network structure to simulate the operating process of this industry. Through introducing the dynamic slack-based measure algorithm into this structure, the operational efficiencies of the entire industry and each stage (power generation and transmission–distribution) in each period are evaluated. On this basis, extended methods are also designed to measure the factor efficiency and the technological gap of each group. The model is applied to China's electric power industry, and the following conclusions are drawn: (I) The operational efficiency levels of provinces and regions are relatively different. (II) Generally, the operational efficiency of the generation stage is significantly lower than that of the transmission–distribution stage. (III) Factors with efficiencies ranked from highest to lowest are capital, labor, and energy. (IV) Major policy implications include breaking down the barriers to prompt interprovincial electricity transmission, developing the energy storage industry, implementing the flexibility transformation of thermal power units, and reducing the cross subsidy to the residual electricity consumption.

Panel semiparametric quantile regression neural network for electricity consumption forecasting

Addressing the forecasting issues is one of the core objectives of developing and restructuring of electric power industry in China. However, there are not enough efforts that have been made to develop an accurate electricity consumption forecasting procedure. In this paper, a panel semiparametric quantile regression neural network (PSQRNN) is developed by combining an artificial neural network and semiparametric quantile regression for panel data. By embedding penalized quantile regression with least absolute shrinkage and selection operator (LASSO), ridge regression and backpropagation, PSQRNN keeps the flexibility of nonparametric models and the interpretability of parametric models simultaneously. The prediction accuracy is evaluated based on China's electricity consumption data set, and the results indicate that PSQRNN performs better compared with three benchmark methods including BP neural network (BP), Support Vector Machine (SVM) and Quantile Regression Neural Network (QRNN).

Energy efficiency in China: optimization and comparison between hydropower and thermal power

BackgroundThe energy generation efficiencies of thermal power and hydropower, which are the two main forces of electric power in China, are important factors affecting the energy conservation, emission reduction, and green development of the country’s whole power industry.MethodsConsidering regional differences and multiple efficient decision-making units (DMUs), this research uses the meta-Frontier super-efficiency slack-based measure (meta-SE-SBM) undesirable model to comprehensively evaluate the efficiencies of hydropower and thermal power generation in China. The CO2 emissions of thermal power generation are taken as the undesirable output.ResultsThe ranking of the average meta-efficiency of thermal power generation in China is Eastern China > Central China > Western China, and all regions show an upward trend. However, the ranking of the average meta-efficiency of hydropower generation is Western China > Central China > Eastern China, and all these regions present a downward trend. In 2017, the technology gap ratio (TGR) values for the thermal power generation efficiency of the eastern and western regions showed a rising trend, while that for the central region showed a declining trend. The TGR values of the hydropower generation efficiency of the western region continued to increase, while those of the central and eastern regions decreased. The development trends of the TGR values of the thermal power or hydropower generation efficiencies of the three regions were not consistent with each other, indicating that technological convergence has not been achieved. In the three regions, the technology gaps in hydropower have slightly expanded, but the technology gaps in thermal power have gradually narrowed. The undesirable output CO2 of the thermal power energy efficiency of the three regions is in a surplus, and the generation of hydropower in the eastern and central regions is insufficient.ConclusionsThe government and power industry managers should fully consider regional heterogeneity in the efficiency of hydropower and thermal power to reduce the technology gap in China. The thermal power industry is relatively mature, but its CO2 emissions should be controlled. The hydropower industry needs further policy support to promote an efficiency improvement in it under the condition of resource endowments.

Medium- And Long-term Power Curve Division Mechanism Based on Energy Block Segmentation

With the development of electric power system reform, it is very important to design the medium- and long-term curve division mechanism for electric power in China. The essence of power supply is "continuous" energy block supply. The two sides of supply and demand take the power block as the interactive unit agreement to deal with electricity. The model of medium- and long-term curve division based on energy block can reflect the abundance of electric power, be beneficial to the stable and reliable supply of electric power and effectively reduce the loss of auxiliary service. Based on the development of new power systems at home and abroad, this paper designs the power curve division mechanism based on energy blocks, and takes Qinghai Province as an example to study its medium - and long-term power curve division mechanism with high proportion of renewable energy.

Impacts of the coal resource tax on the electric power industry in China: A multi-regional comprehensive analysis

A coal resource tax is a common policy tool for promoting rational exploitation and utilization of resources. This study establishes a co-optimization model for both electricity and coal that not only depicts the power dispatched at the micro temporal scale but also considers the capacity expansion that occurs at the macro temporal scale and the spatial dispatch of coal. Based on this model, we investigate the impact of the coal resource tax on China’s electric power industry from four perspectives: economic efficiency, generation portfolio, inter-regional energy dispatch, and environmental benefits. The results show that the current tax rate has a relatively limited impact on the power system. Increasing the tax rate will inhibit the construction of supercritical and ultra-supercritical units and accelerate the diffusion of solar PV, small hydropower, and nuclear units. At the regional level, East China is most affected by the change in the resource tax, and other northern provinces are affected to varying degrees. The coal resource tax has little impact on inter-regional power grid investment, but it does affect the utilization efficiency of existing lines and reduces the volume of almost all coal transportation routes. Thus, it is necessary to consider the relationship between various policies and plans during decision-making.

Research on the Key Technologies of the Ubiquitous Electric Internet of Things

With the rapid development of social economy in China, the demand for electric power resources for all the industries is increasing, and it also puts forward higher requirements for the development and operation of electric power industry. In this context, the power industry is also constantly using new technologies for positive and efficient innovation. The Ubiquitous Electric Internet of Things is a new technology. In the practical application, the Ubiquitous Electric Internet of Things mainly relies on electronic information technology, uses the big clouds move wisdom and other network means to combine with the power system to ensure the power production and the user’s connection more closely and to implement the one-stop service and the management for the user and so on. The construction and application of the Ubiquitous Electric Internet of Things can speed up the development of electric power industry in China, and realize the far-reaching development of electric power industry, so it is of practical significance to study its key technologies.

The impact of removing cross subsidies in electric power industry in China: Welfare, economy, and CO2 emission

There are cross subsidies in China's power industry and there is a gap between supply cost and the sales price of electricity to residents and enterprises. Enterprises pay for part of residents' electricity bills. As cross subsidies always have been criticized, this paper simulates counterfactual scenarios of removing cross subsidy by applying a dynamic recursive computable general equilibrium model. Based on the scenario analysis, the elimination of cross subsidy will have positive impact on economic performance, but negative on CO2 mitigation, industrial structure, and social welfare. Eliminating cross subsidies can reduce commodity prices, improve the competitiveness of enterprises, especially power-intensive enterprises. However, China is somehow an export-oriented country. Only a part of the benefits of the decrease in the product price is obtained by domestic households. Maybe removing cross subsidies is not a good policy in this kind of countries. However, under the background of power system reform, cross subsidy may not last long, and the price will not be regulated. With the marketization of electricity trading, appropriate imposed environmental tax or carbon tax will be more conducive to China's low-carbon development.

The rapid development of the photovoltaic industry in China and related carbon dioxide abatement costs

There is a consensus within the international community that replacing traditional fossil energy with renewable energy, such as photovoltaic energy, will help mitigate climate change. However, the literature addressing the rapid development issues of the photovoltaic industry and related carbon dioxide abatement costs is limited. China is currently the largest photovoltaic producer and consumer in the world, hence suitable as our research object. In this paper, a fixed effect panel model with provincial panel data during the period 2012–2016 is applied to study the factors that influence China’s photovoltaic industry. The empirical results indicate that carbon dioxide emission mitigation requirements, government subsidies, technological progress, energy substitution, economic growth, and illumination resources promote the development of the photovoltaic industry. We further adapt the cost estimation model to estimate the average carbon dioxide abatement cost of photovoltaic electric power in China at 679.72 yuan/ton in 2015 and 681.88 yuan/ton in 2016. Compared with wind power and biomass energy, photovoltaic electric power is currently less economical for carbon dioxide emission reduction. Moreover, the future carbon dioxide abatement cost is predicted using a scenario analysis at 118.94–259.42 yuan/ton in 2025 and 42.63–171.95 yuan/ton in 2030. Since the carbon dioxide abatement cost in 2030 is in line with the future price level of the carbon trading market, it will be both economical and feasible to use photovoltaic electric power to decrease carbon dioxide emissions in the future.

A Power Metering Pipeline Fault Warning Method Based on Deep Learning

With the continuous deepening of the informationization and intelligentization of the electric power industry in China, the fault early warning and diagnosis system of the electric power verification system in China reflects the current situation of insufficient intelligentization. Traditional fault diagnosis system collects operation data of verification system through sensor network, acquisition network and log message technology, and then carries out manual or semi-manual fault detection and processing. There is a small amount of data collected, and the traditional data mining methods such as expert judgment method, decision tree method and SDG model have low efficiency and poor diagnosis effect. In view of this situation, this paper introduces deep learning technology into the verification system of automated pipeline, realizes the integration of fault early warning and diagnosis, builds a fault classification model for automated pipeline based on deep learning neural network, and tests and verifies the effect of model early warning with actual system operation data. The validation of the algorithm gives the result of fault early warning in the form of probability, fully considers the factors affecting the interaction between the pipeline and equipment, has a better effect of fault early warning provides more accurate reference for fault detection and prevention of automated pipeline.

Detecting and Understanding Synergies and Co-Benefits of Low Carbon Development in the Electric Power Industry in China

China’s electric power industry contributes a significant amount of carbon emissions as well as air pollutants such as SO2, NOx, and fine particles. In order to detect co-benefits of carbon reduction and air pollution control, this study analyzed the emission reduction, emission reduction factors, and synergistic effect factors of technical and structural emission reduction measures in the electric power industry in the Jiangsu, Zhejiang, and Yunnan provinces and Shanghai City. The main findings are: (1) the structural emission reduction measures in all four regions had positive co-control effects. Therefore, promoting renewables can achieve remarkable co-benefits; (2) the result demonstrated that the direct removal ability of pollutants by technical emission reduction measures was better than the structural emission reduction measures in all four case studies. However, there were no or few carbon reduction co-benefits associated with their utilization; (3) in all cases, CO2 had the highest emission factor value, which means that there is still room for synergistic carbon reduction; (4) air pollutants and CO2 emission intensity from the Yunnan power plants were much higher than that of the other three regions. In order to achieve the overall co-benefits, co-control measures should be promoted and strengthened in western areas such as Yunnan.

Environmental efficiency of electric power industry, market segmentation and technological innovation: Empirical evidence from China

Environmental efficiency of electric power industry (EEE) is crucial to sustainable development. Among all the factors affecting the efficiency, there lacks enough knowledge of the role of governments and institutions in it. The purpose of this study is to explore the effect of market segmentation (ME) on environmental efficiency of electric power industry and its influencing mechanism from the perspective of technological innovation. The empirical results generated by the system generalized method of moments (GMM) approach indicate that market segmentation has significantly negative effect on environmental efficiency of electric power industry. As evidence we find shows, market segmentation hinders technological innovation, which is an important factor affecting environmental efficiency of electric power industry. Additionally, the inhibiting effect of market segmentation on environmental efficiency of electric power industry is more significant in provinces with weak institutional quality. The conclusions share insights in how to improve environmental efficiency of electric power industry in China by weakening market segmentation.

State intervention in East Asia’s varieties of capitalism: A case study of the electric power industry in China and Japan, 1882–1951

This article studies the history of state intervention in East Asia’s varieties of capitalism through a case study of the electric power industry. The reasons for state intervention in China and Japan, their similarities and differences, and their relative importance are described and analysed. The origin and evolution of the different national models of state–business relations in the two countries are influenced by domestic factors such as national defence and internal unification, as well as external circumstances such as colonialism, occupation, and war.

Regulatory mechanism design of GHG emissions in the electric power industry in China

As one of the key industries of CO2 emissions, the electric power industry plays an important role in China's response to climate change. Recently, the electric power industry has achieved a certain amount of emission reductions through optimizing power structure and enhancing energy efficiency. However, the efforts to address climate change still lack of orderly management and supervision. In order to fulfill the goals of ‘Notice of the 13th Five-Year Work Plan for Controlling GHG emissions’ in China, that by the end of 2020 CO2 emissions per unit of GDP should decrease by 18% compared with that in 2015, there is an urgent need to establish and innovate regulatory mechanisms for Greenhouse gases (GHG) emissions in the electric power industry. This study discusses the status quo and existing problems of GHG emissions regulation of the electric power industry in China from the perspectives of regulatory agencies, measures and accounting methods. Then based on the regulatory experiences from developed countries and combined the real-life characteristics in China, a new GHG emissions regulatory index system and supervision scheme for the electric power industry is established. Finally, some recommendations are proposed for further regulatory mechanism innovation of the electric power industry in China.

Research and Empirical Study on the Healthy Development dynamic model of electric power system Based on China’s Resource Endowment

Based on the macro data of China’s power development in recent years, the paper constructs a dynamic model structure for balanced development of energy generation systems. By modifying, optimizing and verifying it, the optimal dynamic model based on the China’s energy endowment system is derived. And using it, the paper makes a comprehensive in-depth analysis of the long and short-term dynamic variation process and affecting factors of electric power in China, makes a rational study on the trend of complementary multi-source fusion and development as well as the optimal ratio of solution in China’s future power industry. Through an empirical analysis, the simulation degree and reliability of provided decision is proved to be relatively good. While China’s energy has been developing rapidly, there are still some universal problems such as deficient power generation absorption, less reasonable power structure, power transmission channel and so on. Therefore, the paper also puts forward suggestions and solutions on how to strengthen the whole process management of energy development and utilization, formulate all –dimensional policy system etc. in order to promote the development of electric power in China.

Simulating wind power plants for relay protection problems

Wind turbines with a capacity of several kilowatts and megawatts are actively used by the electric power industry in China, Europe, the USA and other countries. The wind has an intermittent nature, depending on the territory, can change its speed from 2 to 25 m / s during day. It’s necessary to study the dynamic impact of the wind farm and to adequately model their operation under different wind loads, taking into account that wind energy constitutes a significant part of the structure of electricity production in many countries, which is reflected in the transients in the power system, Changing or disturbance of the wind flow is reflected on the change of the real power output of each wind turbine. To study the operation modes of wind turbines under different conditions with different methods of specifying wind energy, short-circuit tests were conducted on the 690V wind turbines. The study of the operation of wind turbines in the network with various wind models clearly showed differences in the oscillograms of the current in time, that in order to assess the influence of the work of the wind turbine on the network, the dynamics changes in the wind turbine in faults.

Should China support the development of biomass power generation?

Compared with wind and solar power, biomass power has grown relatively slowly in China. With abundant biomass resources, the development of biomass electric power in China has potential advantages. This paper analyzed the environmental impact of biomass power in the construction and operation stages in comparison with wind and solar power. The results showed that biomass power produced relatively less emissions in the system construction stage at around 1700 ton CO2-e/MW. In the operation stage, biomass power projects achieved an average of 131462 ton CO2-e per year, which is greater than wind and solar power of equal installed capacity. Biomass power plants could achieve net emission reductions in a shorter time (0.39 year) after operation. The life cycle GHG emissions of biomass power projects are between 42 and 85 g CO2-e/kWh. The evidence pointed out that biomass power is worth supporting in China, from the perspective of environmental performance. Local governments should promote the sustainable supply of biomass materials and the development of renewable energy industry should depend on local conditions.