Power Industry In China Research Articles

Green Innovation and firm Performance: An Empirical Study of China's Power Industry

With China’s goal of achieving "carbon peak and neutrality”, green innovation has become an inevitable choice to accomplish the dual objective of ecological protection and economic growth. The objective of this study is to examine whether green innovation can contribute to enhancing firm performance. Specifically, this study empirically investigates the relationship between green innovation and firm performance by analyzing a sample of listed firms in China's A-share power industry from 2009 to 2022. By using panel fixed effect regression, this study found that green innovation markedly and positively enhances the firm's current performance. Furthermore, this paper tested the effect of green innovation on the firm's future performance, which is positive and greater than the effect on the current performance. Through data support spanning 14 years, this study verifies the theoretical hypothesis that green innovation can substantially enhance firm performance in the power industry. This not only deepens the understanding of how green innovation affects firm performance but also offers empirical evidence to support the further implementation and advancement of green innovation within the power industry. This study only uses a sample of a single industry, so the conclusions of this study do not have explanatory power for firms in other industries.

Digital technology adoption and radical and incremental innovations: evidence from the Chinese wind power industry

PurposeDigital technologies open up unprecedented opportunities for the Chinese wind power industry to make rapid and comprehensive decisions. However, the relationship between digital technology adoption and radical and incremental innovations has not been empirically assessed. In addition, reconfiguration capability is the ability of firms to transform and respond to changes. How such an organizational capability influences the effectiveness of digital technology adoption is a black box. In response, this study aims to assess the relationship between digital technology adoption and radical and incremental innovations in the Chinese wind power industry and elucidate the moderating role of reconfiguration capability.Design/methodology/approachBased on the data of listed companies in the Chinese wind power industry from 2006 to 2020, this study constructs regression models and validates the hypotheses.FindingsThe correlation between digital technology adoption and incremental innovation in the wind power industry in China is significantly positive, but the relationship between digital technology adoption and radical innovation is not significant. In addition, reconfiguration capability significantly enhances the incentive effect of digital technology adoption on incremental innovation.Originality/valueTo the best of the authors’ knowledge, this study is one of the earliest to explore the heterogeneous relationships between digital technology adoption and radical and incremental innovations in emerging economies, advancing the theoretical insights into how digital transformation can foster different categories of technological innovations. Moreover, this study embeds dynamic capability theory into digital transformation research by exploring the boundary conditions for the effectiveness of digital technology adoption from the perspective of organizational dynamic capability, thereby expanding the boundaries of existing knowledge.

Digitalization and productivity in the Chinese wind power industry: the serial mediating role of reconfiguration capability and technological innovation

PurposeWind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.Design/methodology/approachBased on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.FindingsThe empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.Originality/valueThis study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

Comparative Analysis of Carbon Tax and Carbon Emission Trading Policies in the Context of Carbon Emission Reduction: Based on the Perspective of the Power Industry

In this paper, we focus on China's power sector to investigate ways to improve emissions reductions in the context of global warming and rising carbon emissions. This paper reviews the current state of adapted carbon emission reduction policies in China's power industry and assesses the potential effectiveness of two mechanisms, carbon taxation, and carbon trading, in achieving substantial emissions reductions. China's power sector is a major contributor to global carbon emissions, and the paper explores the balance between short-term carbon tax policies and long-term carbon trading strategies aimed at promoting an early peak in carbon emissions as well as carbon neutrality within the country. This research finds that the carbon tax can have positive impacts in the short term, whereas carbon trading exhibits higher efficiency in the long term. The paper addresses this by proposing a combination of the two mechanisms to achieve effective emissions reductions in the power industry, supporting China's goal of achieving carbon neutrality by the time of 2060. Finally, we explore the feasibility and benefits of implementing a carbon tax, highlighting its suitability for near-term implementation in the power industry. We conclude that a combination of carbon taxes and carbon trading can make a significant contribution to China's carbon peak and carbon neutrality targets.

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.

The Impact of the Carbon Emission Trading Shadow Price on the Green Total Factor Productivity of the Power Industry in China

To mitigate the problem of global climate change, governments have taken measures to reduce greenhouse gas emissions. Carbon emission trading has gradually attracted attention as a market-oriented option. Power industry panel data from 30 provinces in China were used for an empirical analysis in this study. The super-efficiency Slack-Based Measure (SBM) model was used to calculate the shadow price of carbon trading and the green total factor productivity (GTFP), and the Ordinary Least Squares (OLS) regression model was used to quantitatively analyze the correlation between the shadow price of carbon trading and the GTFP of the power industry. The results showed that the shadow price of carbon trading had a significantly negative impact on the GTFP of the power industry; therefore, it needs to be improved and perfected. Through a further analysis using the heterogeneity test, it was found that there were problems in the current carbon trading price mechanism. In the face of the above problems, we offer suggestions for improvement from the perspectives of the government and companies. This study helps deepen the understanding of carbon trading prices and the GTFP in the power industry, and it provides a reference for formulating more effective carbon trading policies and corporate green management strategies.

Characteristics and mechanism analysis of the clean evolution of China's power generation structure

The power industry in China is the foremost emitter of carbon, necessitating a clean transition in its power generation segment for successful decarbonization. Identifying and quantitative analysis the critical factors that shape the transition and their operational mechanisms will help achieve a secure low-carbon transformation of the energy system. Nonetheless, the body of extensive research in this particular field remains notably limited. To bridge this gap, this paper initiates by developing a comprehensive mechanism framework (REEP) for the transition towards cleaner power generation including Resource endowment (abbreviated as R), Electricity market (abbreviated as E), Economic development (abbreviated as E) and Policy implementation (abbreviated as P) four fields. This framework is based on monthly power generation data derived from four categories of power generation sources at the provincial level in China, spanning the years 2014–2019. It dynamically and quantitative elucidates the multifaceted impacts of various influencing factors on the evolution of the power generation structure. Based on the REEP framework, we observe the power generation structure evolution trends. The study's findings underscore the significance of resource endowment as a paramount internal factor influencing the clean evolution of the power generation structure, while economic development emerges as a pivotal external driving force propelling its transformation. Despite wind and solar power generation accounting for a relatively small proportion at the end of the 14th Five Year Plan period, it is imperative for China to continue promoting the extensive development of renewable energy. While we should coordinate national power transmission and distribution on the foundation of incentivizing technological innovation in emission reduction and the development of energy storage technology. This approach is essential to comprehensively advance the low-carbon and stable development of the energy system, ultimately facilitating the realization of the dual-carbon goal.

RETRACTED: Elasticity of substitution between clean energy and non-clean energy: Evidence from the Chinese electricity industry

At present, China is in a stage of high-quality economic development. Rising demand for electricity has created a lot of CO2 emissions, which has put great pressure on the low-carbon development of China's power industry. Therefore, China attaches great importance to the potential of various clean power generation to replace thermal power generation. Given this, the study examines the potential for substitution of non-clean energy generation (thermal power generation) and clean energy generation (hydropower, nuclear power generation, and other energy generation) from 1993 to 2022 by using the translog production function and provides a scenario analysis of energy substitution for power generation. Firstly, the k-fold cross-validation method is used for ridge regression estimation in this paper, which avoids the subjective bias caused by the ridge trace diagram method used in most of the previous literatures. Secondly, compared with the previous research on the substitution elasticity of the power sector, this paper subdivides the types of clean power energy when estimating the substitution elasticity, which can better analyze the substitution relationship between thermal power and various clean power. Finally, the estimated substitution elasticity of thermal power and various clean energy sources is greater than 1, which indicates that clean energy generation can effectively replace non-clean energy generation. This provides an effective substitution elasticity parameter for the power sector to study low-carbon development. The scenario analysis show China's power sector can increase the proportion of clean power generation to reduce the carbon emission intensity while ensure power supply, which can help the Chinese government adjust the implementation of policies to promote the early peak of carbon emissions and keep carbon emission at a low level in the power sector.

Research on the Reasonability of Electricity Trading Data Based on Electricity Data Analysis

The rationality of power transaction data based on power data analysis can effectively promote the diversified development of China's power industry and meet the diverse electricity needs of the people in production and life. Professional technical personnel in the power field will integrate new technological means into the rationality of transaction data work, which will provide guidance for its sustainable development. Based on this, this article conducts a more targeted analysis from three levels: the advantages of electricity trading data rationality based on electricity data analysis, the classification of electricity trading data rationality based on electricity data analysis, and the exploration of electricity trading data rationality methods based on electricity data analysis, in order to provide reference for the effective promotion of Gini in related project engineering.

The allometric growth relationship between electricity consumption and economics in China.

Electric power is the basic industry of a modern country. The rapid development of the power industry has promoted economic development and social progress. With the establishment of the carbon neutrality target of carbon peak, China's power industry is also facing new situations and new challenges. This paper innovatively introduces the concept of allometric growth in biology, and uses the data of provincial electricity consumption and economic development from 1972 to 2017, to study the allometric growth relationship between electricity consumption and economics in China at multiple scales. Combined with the spatial autocorrelation analysis method, the temporal and spatial characteristics of allometric growth between electricity consumption and economic development were researched based on the analysis of spatial correlation of GDP electricity consumption intensity. The results show that: (1) The provincial GDP electricity consumption intensity shows an aggregate distribution, and the local aggregate pattern changed significantly from 1972 to 2017. (2) The High-High Cluster gradually disappeared, and the Low-Low Cluster moved southward, appearing in the middle and lower reaches of the Yangtze River. (3) The differential growth coefficient of electricity consumption and economic development increased initially and decreased from 1972 to 2017. (4) GDP would increase by 7.4%, 20.1%, and 15.6% in the simulation of electricity consumption, increasing 10% at the three stages of China's economic development. (5) The allometric growth coefficients of electricity consumption and economic development are very different in the three economic belts, eight economic zones, and provinces with different characteristics at the different stages of economic development. Formulating differentiated regulation policies for regional economic development and electricity consumption will be conducive to the coordinated development of electric power production and the national economy.

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.

Evaluation and spatial convergence of carbon emission reduction efficiency in China's power industry: Based on a three-stage DEA model with game cross-efficiency

Reducing carbon emissions is essential for achieving sustainable development in China. In this study, we developed a framework for measuring carbon emission reduction considering both thermal power and clean energy generation perspectives. Subsequently, we constructed a three-stage data envelopment analysis (DEA) model with game cross-efficiency to eliminate the influence of external environmental factors, random factors, and regional competition. Thereafter, we calculated the carbon emission reduction efficiencies (CEREs) of the power industries of 30 provinces in China from 2010 to 2020. Based on this, we conducted temporal and spatial analyses of the carbon emission reduction amount (CERA), evaluated CERE, compared different DEA models, and assessed spatial convergence effects. The evaluation results of CERE across 30 provinces, cities, and autonomous regions in China showed that: (1) although China's CERA increased, substantial regional differences exist in the carbon emission reduction structure. (2) The overall average CERE ranged from 0.485 to 0.737. Since 2016, the highest CERE values have been observed in southwest China, followed by the eastern coastal and central regions, while the northwestern region experienced notable fluctuations. (3) The three-stage DEA model with game cross-efficiency, which eliminates the influence of competition and external environmental factors, can be used to accurately measure CERE. (4) CERE has a spatial convergence effect on China's power industry and is promoted by energy structure, upgrading of industrial structure and government interventions. These findings provide important insights for optimizing the carbon emissions reduction structure and improving CERE.

P2P trading mode for real-time coupled electricity and carbon markets based on a new indicator green energy

The carbon trading market has introduced new opportunities for the low-carbon transformation of China's power industry. To realize real-time coupling of the electric–carbon market at the mechanism level, this study constructs a P2P trading mode that improves economic and environmental benefits through innovative mechanisms. First, we propose a novel indicator, Green Energy, which has multidimensional composite attributes and accurately characterizes the supply of clean and low-carbon energy. Green Energy is used as a matchmaking indicator in the P2P electricity market to increase the rate of renewable energy consumption and encourage emission reduction of fossil energy suppliers. Second, the carbon price is dynamically adjusted according to real-time electricity consumption information and it is transmitted to the electricity market through Green Energy. Third, blockchain cross-chain interoperability technology is introduced to establish a real-time data-sharing network for electricity and carbon co-trading. Moreover, a case study is conducted, and the simulation results show that the proposed method improves social welfare by over 18% compared to the traditional trading mode. And it can improve renewable energy utilization efficiency by 26.78% and reduce carbon emissions by more than 17%. This study provides a reference for the real-time coupled electricity and carbon markets.

Has the evolution of renewable energy policies facilitated the construction of a new power system for China? A system dynamics analysis

Renewable energy (RE) support policies play a significant role in promoting RE development. Both the feed-in-tariff (FIT) and renewable portfolio standards (RPS) policies have been implemented in China's power industry, but the market response is far from satisfactory. Additionally, a rush to promote electric power generation from RE sources poses operational hazards to the power system due to its intermittent nature. Therefore, this paper focuses on various forms of mainstream RE policies and develops system dynamics (SD)-based simulation models to examine their different incentive effects and evaluate the impacts on constructing a new power system for China. The simulation results show that the demand-side RPS (DRPS) outperforms the supply-side RPS (SRPS) policy at minimizing the costs of market participants, promoting RE consumption, constraining the damage for thermal power generation, and providing long-term incentives for RE industry investment, but lacks incentives for promoting the liquidity of Tradable green certificates (TGC) market. The combined FIT&RPS policy provides a transitional instrument to neutralize large volatility. When promoting energy transition, different RE policy forms should be enacted in stages and it is necessary to consider the construction of power grid systems and appropriately plan RE development to achieve balanced development.

Support carbon neutrality target — Which flexible power source is the best option for China?

China has set a goal of carbon neutrality by 2060 and is determined to increase wind and solar power to 1200 GW by 2030, even though it already has the world's largest installed capacity of renewables. However, the lack of flexibility in the power system will limit the development of a higher proportion of renewable energy. This paper evaluates the applicability of different types of flexible power sources in China for the first time. Above all, it describes the current situation of China's power industry and the necessity of increasing flexible power sources, establishes an evaluation system from the perspectives of benefit, opportunity, cost & risk, then determines 19 evaluation criteria. The BOCR-ANP-TOPSIS method was used to evaluate the system, where the ANP method determines the weights and the TOPSIS method ranks the alternatives. The result shows that pumped storage hydropower has the highest overall ranking, followed by the flexibility transformation of coal-fired power. Coupled with sensitivity and comparative analysis, valuable findings that will help future energy policymakers are reported.

Quantity or quality? Policy effects on innovations in the wind power industry in China

AbstractThis study evaluates the effects of policy on the quantity and quality of innovations based on microdata collected from Chinese enterprises from 2006 to 2020 and then identifies the moderating effect of technological opportunity. The results indicate that while policy significantly increases the quantity of innovation, it inhibits its quality, and when technological opportunities are added to this mix, it does not significantly moderate the impact of policy on innovation quantity but does weaken its negative effect on innovation quality.

Has the Wind Power Price Policy Promoted the High-Quality Development of China’s Wind Power Industry?—Analysis Based on Total Factor Productivity

The wind power price policy has promoted the rapid development of the wind power industry in China. However, China’s wind power industry is facing high-quality development problems such as wind curtailment and blind investment. Exploring the relationship between the change in wind power price policy and China’s high-quality development of wind power is of great significance for the energy system to achieve carbon neutrality. This paper constructs an SBM-GML global covariance model, calculates the total factor productivity of wind power in 30 provinces in China from 2015 to 2019 and conducts index decomposition, and selects provincial panel data from 2015 to 2019 to empirically test the impact of the wind power price policy on the total factor productivity of wind power in China. The results show that the wind power price policy can significantly improve the total factor productivity of wind power, and the results of the endogenous test and robustness test show the effectiveness of the model. The wind power price policy is helpful to promote the technological progress of wind power, affect the reduction of the price difference between wind power benchmark price and coal power benchmark price, and then promote the improvement of wind power total factor productivity so as to meet the policy requirements of wind power full grid parity. In addition, the impact of wind power price policy on the total factor productivity of wind power has obvious regional heterogeneity. Future price policy formulation should clarify industry development expectations, consider regional differences, and establish a sound, market-oriented electricity pricing mechanism.

Government intervention and technological innovation in the wind power industry in China: The role of industrial environmental turbulence

Wind power is accelerating the transformation of China’s energy market from a primary to a renewable energy-dominated market. The Chinese government has engaged in many supportive and regulatory interventions to guide and stimulate wind power enterprises to simultaneously improve existing technologies and develop new solutions. However, the effectiveness of policies and the potential interactions among them have not been empirically assessed. Firms in emerging economies typically survive and develop in turbulent environments. How such an environment affects the effectiveness of government intervention remains a black box. This study aimed to investigate the impact of wind power policies and their mix on exploitative and exploratory innovations in China, along with the moderating role of environmental turbulence. Using data on listed companies in the Chinese wind power industry from 2006 to 2020 and two-way fixed effects regressions, this study assesses and compares the impacts of different policy categories and their mix on exploitative and exploratory innovations. We also distinguish between market and technological turbulence, and clarify the moderating effect of environmental turbulence. In addition, this study ensures the robustness of the empirical results by altering the dependent variables and eliminating the interference of endogeneity using the IV-2SLS method. The results indicate that supportive and regulatory policies and their mix facilitate exploitative and exploratory innovations. Market turbulence enhances the relationship between policies and their mix and exploitative innovation, whereas technological turbulence enhances the relationship between policies and their mix and exploratory innovation. This is one of the first studies to evaluate the impacts of policies and their mix on the exploitative and exploratory innovations of renewable energy sectors in emerging economies, advancing the understanding of innovation growth in emerging economies and enriching research on renewable energy policies. Additionally, this study links environmental turbulence to government intervention, and thus contributes to the identification of policy effectiveness boundaries.

A study on the spatial and temporal evolution of carbon emission efficiency in China's provincial power industry

Promoting the low carbon development of the power industry is an essential path for China to achieve the “3060” dual carbon goal. This paper uses the SBM model and the Moran index to construct a carbon emission efficiency assessment system that meets the requirements of a high proportion of renewable energy access in China. The spatial and temporal evolution and correlation of the carbon emission efficiency of the power industry in 29 provinces in China were analyzed. The results show that the carbon efficiency of China's power industry has been increasing year by year since the 13th Five-Year Plan, and the overall pattern is that the periphery has led to the gradual development of the center, while the Yangtze River Delta and Northeast China show a clear spatial correlation, with prominent policy and technology spillovers. The results may provide scientific guidance for efficiency improvements in each region.

The impact of carbon emissions trading policy on carbon emission of China's power industry: mechanism and spatial spillover effect.

Carbon emission trading policy (CETP) is an important tool for energy savings and emission reduction. However, the effect of CETP on carbon emission reduction in power industry is still unknown. This paper uses the difference-in-differences (DID) model and the intermediary effect model to test the impact and mechanism of CETP on power industry carbon emissions. In addition, a spatial difference-in-differences (SDID) model is established to analyze the spatial spillover effect. The results show that CETP has a significant inhibitory effect on power industry carbon emissions and the results are still valid after endogenous and robust tests. The improvement of technology level and power conversion efficiency plays an intermediary role for CETP to reduce power industry carbon emissions. The optimization of power generation structure is likely to become another important way for CETP to play its role in the future. The spatial spillover effect test shows that CETP not only has a significant inhibitory effect on power industry carbon emissions in the pilot areas but also has a negative spatial spillover effect on power industry carbon emissions in the surrounding non-pilot areas. The heterogeneity tests show that CETP has the most significant reduction effect in the central region of China and the strongest spatial spillover inhibiting effect in the eastern region. The purpose of this study is to provide decision-making references for government to achieve China's dual-carbon goal.