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With the development of energy technology, hydrogen is gradually becoming widely used. China is also rapidly developing its own hydrogen energy industry in an effort to accomplish the "dual carbon target'. Hydrogen from methane is one of the mainstream sources, of which hydrogen from methane cracking is the decomposition of methane into hydrogen and solid carbon, with the solid carbon also having a high economic value. In particular, this technology does not emit carbon dioxide, which is very friendly to the environment, but it cannot avoid larger energy consumption. In contrast, hydrogen production from methane cracking driven by solar energy not only combines the characteristics of no CO 2 emission, but also greatly reduces the consumption of primary energy, which is the future development trend of hydrogen production from methane. This paper provides a brief overview of the various technological pathways for methane to hydrogen production in the context of China's actual development, focusing on the current status of the development and application of solar methane cracking to hydrogen production technologies at home and abroad. Among them, this paper mainly discusses the characteristics of solar reactors of different sizes and structures, and summarizes the results of related optimization studies. Meanwhile, the application of catalysts in solar reactors and the problem of carbon deposition are analyzed, and the practical application of solar methane cracking hydrogen production system is outlined. Finally, the future development of solar methane cracking hydrogen production technology is prospected from the national situation of China. [Display omitted] • Solar methane cracking for hydrogen can reduce emissions and energy consumption. • The current state of research on solar reactors is summarized. • Solar methane cracking requires higher performing catalysts. • Providing insights into the future development of solar methane cracking in China. [ABSTRACT FROM AUTHOR]

In recent decades, the role of green energy in realizing green transition and addressing environmental degradation needs to be brought into full play. To promote green energy development in China, this paper examines the relationship among green economic growth, green finance, and green energy (3G) between 2011 and 2019. The heterogeneous, asymmetric, and mediation impact relationship that exists in the 3G nexus is also explored in this study. Accordingly, the results suggest that: (1) Green economic growth and green finance are positively associated with green energy, and the impact is heterogeneous on different types of green energy and in different regions; (2) the impact of green economic growth on green energy are asymmetric, while that of green finance is consistent; and (3) green innovative technology is an effective mediator between green economic growth and green energy, while the investment effect is not significant. This paper contributes to formulating several reasonable policies for improving the green energy industry and achieving sustainable development. It is essential to give full play to the transformation of green achievements to enhance the role of green economic growth in promoting the green energy industry. • This study explores 3G nexus (green economic growth, finance, and energy (GRE)) in China. • The heterogeneity, asymmetry, and mediating mechanism are further analyzed. • Green economic growth and green finance can significantly promote GRE. • The impacts of green economic growth and green finance on GRE are heterogeneous. • Green technological innovation is an effective mediator in the 3G nexus. [ABSTRACT FROM AUTHOR]

Renewable energy is regarded as an effective method to alleviate environmental pollution and accelerate the green transition in China. This paper systematically investigates the impact of financial inclusion on renewable energy demand by using S-GMM model based on provincial data in the green finance era. This paper also analyzes the asymmetry, heterogeneity, and mediating mechanism in the nexus between financial inclusion and renewable energy demand, and highlights the following findings: (1) Improved financial inclusion can promote renewable energy development in China and present the characteristics of green finance; (2) the impact of financial inclusion on renewable energy demand is asymmetric and heterogeneous; specifically, this impact is much higher in northern China and the regions with higher renewable energy development; and (3) wind and photovoltaic power generation are effective mediators between financial inclusion and renewable energy industry, while the mediation effects of hydropower and nuclear power are not significant. New evidence in this study is presented for the achievement of green transition in China, as well as practical policy implications for improving financial inclusion and increasing renewable energy consumption. For instance, fiscal and tax incentives and green investment subsidies in the renewable energy sector need to be further improved. • This study explores the impact of financial inclusion (FI) on renewable energy demand (RED) in China. • Asymmetry, heterogeneity, and the mediating mechanism are further discussed. • Increased FI can promote RED , which presents the characteristics of green finance. • The impact of FI on RED is asymmetric and heterogeneous. • Wind and photovoltaic power are effective mediators between FI and RED. [ABSTRACT FROM AUTHOR]

With global climate change posing a major threat to human society, a growing number of countries have taken "carbon-neutral" as a national strategy and proposed a vision of carbon-free future. As an important supplement to traditional fossil energy, renewable energy is the main force to reduce the use of high-carbon energy and carbon dioxide emissions, which will become the trend of social development in the future. Finding the optimal renewable energy source is of particular significance for achieving the net zero emissions. However, the existing evaluation methods of renewable energy sources have obvious shortcomings. In terms of weight calculation methods, such as the randomness of the subjective method is strong and the index weights do not reflect the small changes of the evaluation matrix, which affect the reliability and accuracy of the evaluation result. The existing ranking methods can only achieve the complete ranking of the different objects, but cannot classify the renewable energy technical alternatives into different grades. Given this background, this paper proposes a novel evaluation method for renewable energy plans based on improved sparrow search algorithm and projection pursuit model. Firstly, this paper improves the traditional sparrow search algorithm from three aspects: population initialization, population update and population variation. Then, the projection pursuit model is constructed, and the improved sparrow search algorithm is applied to optimize the projection target to find the optimal projection direction, so as to determine the weight values of each evaluation index. Finally, the weighted rank-sum ratio method is used to select the best renewable energy technical plan, which can not only realize the complete ranking of different plans, but also classify the technical plans into different levels. Based on the actual renewable energy development data from a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some existing evaluation methods of renewable energy technical plans. [ABSTRACT FROM AUTHOR]

Rapid urbanization is affecting the harmonious development of the environment and economy. Governments are developing new urban planning policies to achieve sustainable urban development. Using the Chinese smart city pilot policy as a natural experimental group, we use a difference-differences model to explore the relationship between smart cities and clean energy development. There are three findings in this paper. First, we find that smart city pilots drive clean energy development. Second, we find that digital technologies can reinforce the positive impact of smart city pilots and that innovation and financial inclusion have a positive mediating role. Third, we find that the impact of smart city pilots has a heterogeneous impact. Namely, pilots in coastal, large, and resource-based cities have a more positive impact on clean energy development. Existing smart city pilots significantly impact energy security and sustainable development. Our study provides a new perspective on urban planning and clean energy development in emerging countries such as China. • A difference-differences model to explore the effect of smart city pilot. • Smart city pilot drives clean energy development. • Innovation and financial inclusion have positive mediating roles. • Digital technology has a positive moderating effect. • Clean energy development in smart cities is distinctly heterogeneous. [ABSTRACT FROM AUTHOR]

The development of information and communication technology (ICT), a subset of many functions such as visual communication, can positively affect renewable energy development in different countries. In this paper, focusing on China as the world's largest emitter of greenhouse gases, the relationship between visual communication and the deployment of renewable energy is investigated using the dynamic ARDL (autoregressive distributed lag) method and annual data from 1990 to 2021. Regarding the empirical estimations, a 1% increase in green finance market size leads to an improvement of sustainable energy deployment by 0.01%. In addition, the ICT development index has a significant and positive effect only in the long term. Furthermore, there is evidence of uni-directional causality from ICT to renewable energy deployment in the medium and long term. The recommended practical policies by the research are developing green financing tools, green economic growth policies, and creating virtual portals for financial interactions. • There is uni-directional causality from visual communication to renewable deployment. • ICT development index has a positive effect in the long term. • Effect of GDP on the development of renewable energy consumption is negative. [ABSTRACT FROM AUTHOR]

Renewable Portfolio Standards (RPS) is a mandatory institutional change to promote low-carbon energy transformation and renewable energy development. Its successful implementation requires the scientific design of relevant incentive mechanisms and rules. To make up for the defects in the current RPS mechanism design and the problems exposed in the Tradable Green Certificate (TGC) market, this paper takes China as an example and uses the system dynamics method to study the supply side incentives. The results show that: (1) Scientific setting the relevant system parameters of RPS (such as quota, benchmark price and penalty) and promoting the electricity market reform will effectively stimulate the power generation and investment on the supply side, and improve manufacturers' profit. (2) Higher quotas and lower benchmark prices can increase the manufacturers' power generation, profit and investment, and stimulate the supply side to conduct TGC transactions. However, when the penalty is set at different multiples of the benchmark price, the incentive effect on supply side power generation, investment and profit differ. (3) Marketed on-grid prices can significantly stimulate the supply side and promote renewable energy development. This paper can provide reference for the design of RPS incentive mechanism and institutional parameters. [ABSTRACT FROM AUTHOR]

The primary purpose of this paper is to evaluate the impacts of green finance on green energy deployment in China's tourism industry. To this end, the annual data over 1992–2021 through the ARDL (Autoregressive Distributed Lag) approach for the case of China are analyzed. The findings confirm that the issued green bonds positively impact the green efficiency of China's tourism industry in the long term. In contrast, the coefficient of issued green bonds is insignificant for the short-term approach. In addition, in the short and long term, the consumer price index also has a significant adverse effect on the green efficiency of China's tourism industry. The recommended practical policies are improving executive regulations and transparent market information, implementing green fiscal policies, green construction in hotels and tourist accommodations, green globalization, operational phases of innovation, adaptation, and stabilization (IAS), and eco-tourism regionalism. • Green bonds have a positive impact on the green efficiency of China's tourism. • Consumer price index has a negative effect on green efficiency of China's tourism. • Economic globalization index has a significant coefficient on green efficiency. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

The rapid development of China's economy has driven the growth of energy consumption. However, the domination of the energy structure by fossil energy not only increases carbon emissions but is also an important source of fog and haze in China. This will cause global warming and increase people's lung diseases. To alleviate these problems, renewable energy (RE) development is crucial in reducing CO 2 emissions, promoting economic development, and reducing fog and haze in China. Industry accounts for the highest proportion of energy consumption, so an efficient adjustment of the industrial structure will greatly contribute to overall energy development, economic development, and environmental protection. By analyzing the sales output value of China's industrial subsectors, together with energy consumption and CO 2 emissions, this paper determines which industries should be encouraged and which industries should be restricted in China. Finally, RE strategies and industrial policies are proposed for Chinese government references. The contributions of the paper are three-fold: (1) propose a novel framework for the development of China in the aspects of energy, economy, and environmental policies; (2) provide valuable information for the Chinese government to enable it to understand which industries should be encouraged to improve its economic competitiveness; and (3) use hybrid methods (e.g., entropy method and weighted sum method) to rank the energy and CO 2 productivity, and the recommendations will provide strategic guidance for China's energy development. [Display omitted] ● China's Renewable Energy Strategy and Industrial Policy. ● Which industries should be encouraged or discouraged in China. ● Energy Productivity and CO 2 Productivity. [ABSTRACT FROM AUTHOR]

• The solar potential in different residential blocks is simulated. • The influences of block morphological parameters on solar potential are varified. • Four parameters that impact on the block solar potential more than 70% are verified. • The facade PV capacity in high-rise and hybrid residential blocks is more than 66%. • The average PV installation rate of roof, south and west facade is 96%, 32% and 39%. Block-scale application of photovoltaic technology in city is becoming a viable solution for renewable energy utilization. Rapid urbanization process has made urban buildings have huge development potential for solar energy in China, especially in residential areas that occupy large parts of the city. However, the residential blocks in China show differences in the morphological layout and parameters, which means they have diverse potential for solar energy development. This paper studies the effect of quantified morphological parameters on solar potential for residential blocks in Wuhan, China. The distribution characteristics of solar potential in different block environments are discussed. Various strategies are evaluated in terms of the installation position and height of PV modules. The results showed that floor area ratio, building density, average building height and building interval have significant impact on solar potential for residential block, and their correlation can reach 75%, 71%, 78% and 72% respectively. The average PV installation ratio of roof, south facade and west facade can reach 96%, 32% and 39% respectively. The results of this paper not only provide a reference to the block-scale application of PV technology in urban environment, but also stimulate the implementation of photovoltaic policies on various residential blocks in China. [ABSTRACT FROM AUTHOR]

• Bibliometrics overview of ZEB publications. • Draw of the collaboration networks from ZEB research publications. • Brought out thematic trend of the development ZEB over the time. • Discussions of the main challenges and solutions for ZEB studies. Zero Energy Building (ZEB) is gaining more attention as a solution to significantly mitigate the environment concerns. However, a bibliometric analysis of the topic, a very useful method to analyze the database of published publications and reviews, is lacking. Especially, to provide when and how this concept has been brought out, insights into the state-of-art technology, the findings of the collaboration networks and the challenges of ZEB. To address this gap, in this paper, ZEB studies have been reviewed using multiple perspectives and analytical tools, such as VOSviewer and Biblioshiny to analyze the collaboration networks and the thematic trends of ZEB publications. The original data was retrieved in Scopus, a total of 1051 documents including research articles and reviews published from 1976 to 2020. The analysis of the number of publications over the years shows that the development of Zero energy building research has gone through three stages: a slow development period from 1076 to 1999, followed by a development from 2000 to 2010 and finally a rapid development from 2011 to 2020. The study also reveals different rankings, including the most widely collaborated scholars, the most cited scholars, the most published countries, etc. Therein, the United State, United Kingdom and China have the most research on ZEB. Based on the analysis of co-occurrence network and evolution of thematic keywords, it is found that energy efficiency and life cycle assessment (LCA) are the main challenges for the achievement of ZEB target. Finally, these challenges have been discussed and solutions provided. [ABSTRACT FROM AUTHOR]

• Long-term evolution trend of wind and waves in China's offshore was investigated. • A novel approach was proposed to evaluate wind-wave joint exploitation potential. • Joint utilization guarantee rate of wind and waves in China's offshore was 67 %–87 %. • AO, AMO and Niño 3.4 affected WS and H s from high to low latitudes, respectively. • Impact of ENSO on WS and H s in SCS could reach 3.92 m/s and 1.15 m, respectively. Assessing wind and waves resources and analyzing their evolution are crucial for the exploitation of wind and wave energy. This paper utilized ERA5 reanalysis data to investigate the distribution characteristics, long-term evolution, and influencing factors of wind speed (WS) and significant wave height (H s) in China's offshore regions. It showed that over the past 60 years, the Bohai Sea experienced a significant downward trend in WS (−0.632 cm/s/yr) and H s (−0.135 cm/yr). The Yellow Sea exhibited a downward trend in WS, but no change trend was observed in H s (p > 0.05). The H s in the East China Sea (ECS) and South China Sea (SCS) showed upward trends, increasing by 0.191 cm/yr and 0.262 cm/yr, respectively. The concept of energy utilization guarantee rate (EUGR) was introduced to evaluate the complementarity and synergy between wind and wave resources. The ECS and SCS were found to possess ample wind resources, with an EUGR of approximately 80 %. The combined EUGR of wind and wave energy in the Bohai Sea, Yellow Sea, ECS, and SCS amounted to 67.41 %, 72.29 %, 86.86 %, and 84.10 %, respectively. The southeastern coastal waters of China exhibited significant complementary and synergistic effects between wind and waves, making them suitable for the joint utilization of wind and wave energy. The distribution and evolution of wind and waves in China's offshore varied due to diverse climate conditions prevailing in different regions. From high to low latitudes, the Bohai Sea was mainly controlled by AO, while the Yellow Sea was jointly affected by AO and AMO; The ECS and SCS were mainly affected by AMO and Niño 3.4, respectively. During El Niño/La Niña years, the SCS exhibited a decrease/increase in WS and H s , with a lag of ∼3 months in response to ENSO. The variation amplitude of WS and H s could reach 3.92 m/s and 1.15 m, respectively. [ABSTRACT FROM AUTHOR]

Prefabricated buildings (PB) are assembled using prefabricated components, known for their cost-effectiveness and high efficiency. They are seen as an effective means to achieving sustainable development goals and mitigating climate change. This paper examines the impact of prefabricated buildings on urban green total factor energy efficiency (GTFEE) using panel data from 278 cities in China. The analysis is conducted through the application of a super-efficiency slack-based measure (SBM) model and a difference-in-differences model. The results of the study indicate that the promotion of PB can significantly improve urban GTFEE; there is heterogeneity in the improvement of urban GTFEE by PB; the innovation effect, industrial effect and marketization effect of PB are the main ways to improve urban GTFEE. Specifically, PB exerts an innovation effect by promoting technological innovation. It influences consumer and investor demand, leading to increased activity in the secondary industry, thereby creating an industrial effect. Moreover, PB facilitates the marketization effect by phasing out outdated industries, encouraging autonomous enterprise innovation, and fostering the growth of new advanced enterprises. This study reveals the critical role of PB in urban GTFEE improvement. It clarifies its mechanism of action, which provides a reference for urban sustainable development strategies and energy efficiency. • Prefabricated buildings can improve green total-factor energy efficiency. • Urban green total-factor energy efficiency has been measured. • PB improves GTFEE through innovation, industry and marketization effect. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

As the world's largest energy consuming country, it is important to study the mechanisms of improving renewable energy and energy efficiency to achieve green economic growth in China and globally. Therefore, this study investigates the impact of environmental regulations on green economic growth and renewable energy development in China, respectively. First, this study measures the level of green economic growth in Chinese cities by the Metafrontier-Global-SBM super-efficient data envelopment analysis (DEA) model from the perspective of energy efficiency. And the environmental regulation intensity was measured using an improved fuzzy comprehensive evaluation method. Second, a spatial econometric model based on longitudinal data was constructed to examine the non-linear effects of environmental regulations on green economic growth and its spatial spillover and feedback effects. The results indicated a U-shaped non-linear effect of energy efficiency-related environmental regulation on green economic growth as well as a spatial spillover effect and spatial feedback effect. Finally, the impact of environmental regulation on renewable energy development was investigated. The results show that renewable energy development, an important component of green economic growth, is equally dependent on the implementation of environmental regulation policies and that environmental regulation makes a significant contribution to renewable energy development. The findings of this paper provide a basis for the realization of green economic growth and the formulation of renewable energy policies in China. • Impact of environmental regulation on renewable energy development was investigated. • A spatial econometric model of 286 Chinese cities from 2003 to 2018 was constructed. • Environmental regulation has a significant U-shaped effect on green economic growth. • Non-linear effects include spatial spillover and spatial feedback effects. • Environmental regulation promotes green growth earlier in resource-based cities. [ABSTRACT FROM AUTHOR]

The exploration and promotion of new energy constitute a significant initiative for numerous countries in their pursuit of sustainable development and efforts to alleviate climate change. However, the influence of a multitude of uncertain factors on the evolutionary path of new energy is currently poorly studied. By establishing a dynamic evolution model for new energy under polymorphic uncertainty, this paper analyses the complex interaction between new energy, economic growth, and carbon trading over the period 2020–2060, using China as a case study. We employ numerical simulation and sensitivity analysis to investigate the evolutionary trajectories of the new energy system under various parameter value scenarios. We show that the evolutionary trajectories will undergo substantial fluctuations before 2030, subsequently stabilizing from 2030 onwards. The study highlights that an excessively rapid pace of new energy development is detrimental to new energy systems, whereas energy storage system deployment has the opposite effect. There exists a significant risk of the system collapsing as a result of slow new energy development, over-building energy storage facilities, or over-intervening in carbon trading. We also find that overdevelopment of energy storage system may have greater negative impacts on the economic system than underdevelopment. [Display omitted] • Dynamic evolution model of new energy under polymorphic uncertainty is constructed. • New energy production elasticity and energy ratio are innovatively constructed. • Excessive intervention in carbon market can lead to the collapse of new energy system. • Overdeveloped energy storage hinder the synergy of new energy and economic growth. [ABSTRACT FROM AUTHOR]

Taking 141 listed renewable energy enterprises in China as a sample, the Richardson model is adopted to measure their investment efficiency in this paper. On this basis, an intermediary effect model of panel data is constructed to empirically analyze the intermediary effect of green financial development on renewable energy investment efficiency through bank loans, short-term loans, and long-term loans. We find that China's green financial development has a negative impact on bank loan issuance in general, and inhibits the improvement of renewable energy investment efficiency to a certain extent, with an effect degree of 0.0017. Besides, the short-term loan has few intermediate effect on investment efficiency, while there is no intermediary effect of long-term loans. Moreover, as for the over-investment renewable energy enterprises, intermediary effect of bank loans exists. Green financial development can inhibit over-investment in renewable energy by reducing bank credit issuance; for renewable energy companies of under-investment, on the contrary, it aggravates the under-investment to a certain extent. This paper suggests that the government should both construct and consummate the green financial system through policies and regulation. Financial institutions should actively produce innovative green financial products and support the development of renewable energy enterprises and the renewable energy enterprises should strengthen their internal management and develop financing channels. • This paper measures the green financial development index from 2011 to 2016. • A Richardson model is adopted to measure renewable energy investment efficiency. • Green financial development can inhibit over-investment in renewable energy by reducing bank credit issuance. • For renewable energy enterprises that are underinvesting, green financial development cannot alleviate under-investment. [ABSTRACT FROM AUTHOR]

Based on China's provincial panel data from 2001 to 2015, the drivers of energy technological innovation, e.g., energy price, public financial policy, knowledge stocks, energy structure, and environmental regulation, are analyzed by using the generalized method of moment (GMM) in this paper. Through the construction of one kind of geometric distribution lag model, which is also called partial adjustment model, we empirically analyze and compare the influencing factors of energy technological innovation from the perspectives of fossil energy and renewable energy. The specific conclusions obtained in this paper are: (1) The impact of the energy price on fossil energy technological innovation is greater than renewable energy, which means that the current energy price in China is much lower than its optimal level and the development of renewable energy technology needs the support of price mechanism. (2) The development of these two kinds of energy technology innovation heavily relies on governmental policy support. (3) The accumulation of energy technology innovations will be conducive to the vertical spillover effect of knowledge, and further encourage the development of energy technology. Based on the above findings, we then propose some relevant policy proposals to promote energy technological innovation in China. [ABSTRACT FROM AUTHOR]

Low-carbon technology has become the focus of addressing global climate challenges but is facing the supply restriction of critical high-tech metals. Recycling has become a powerful measure to solve this issue. In the paper, a comprehensive recycling potential index (RPI) is constructed to evaluate the recycling potential of high-tech metals for low-carbon energy technologies in China from 2020 to 2050, and development strategies are proposed based on the evaluation results. The results indicate that the future trends of recycling potential show four evolution modes – either reaching or rapidly rising to a high level, increasing to the middle and middle-high level, unsteadily staying at the low and middle-low level, or remaining at a low and continuously decreasing level. According to the evolution trend, different strategies, including key development, reserves, digestion, and transfer, should be adopted in different stages. Co, Li, Dy, Nd, Tb, and Eu should be the focus of technology, funds and policy from both the government and enterprises due to their high recycling potential in the long term. Moreover, measures should be taken to encourage recycling and mitigate the supply risk of high-tech metals for low-carbon energy technologies, including tracking the development of low-carbon energy technologies, adjusting the list of critical high-tech metals, promoting recycling technology, and exploring substitute resources. [Display omitted] • A comprehensive recycling potential index is constructed to evaluate the recycling potential of high-tech metals. • The future trends of recycling potential of high-tech metals show four evolution modes. • Strategies like key development, reserves, digestion, and transfer should be adopted in different stages. [ABSTRACT FROM AUTHOR]

[Display omitted] • It analyzes the feasibility of achieving net zero emission in the Chinese power sector by 2050 and the required policy measures. • It is essential to foster the concurrent development of renewable energy, energy storage, and demand response technologies. • The carbon pricing mechanism with exponential growth is more suitable. • Referring to the European offshore wind power investment model is beneficial for the development of offshore wind power in China. The low-carbon transition in China's power sector plays a crucial role in the mitigation of climate change worldwide, and increasing renewable energy penetration rate is widely recognized as the key approach to decarbonize this sector. This paper proposes a renewable energy penetration model to examine the feasibility for net zero emission by 2050 in China's power sector taking into account of economic and social development. It also evaluates the impacts of carbon pricing and financial incentives on renewable energy penetration and carbon emissions. The results indicate that along with economic development, China's electricity demand will continue to grow, but at a gradually slowing rate. It is possible for the power sector to achieve net zero emission by 2050 while meeting this growing electricity demand, with a renewable energy penetration rate of 75%. To ensure the achievement of the goal, we recommend setting the carbon price with the current market price as the baseline and increasing it annually by a relative increment index of 10%. Furthermore, given the high initial cost and late start of offshore wind power, we suggest incorporating associated grid connection cost into the transmission and distribution price to ensure the comprehensive and healthy development of renewable energy. [ABSTRACT FROM AUTHOR]

Based on the analysis of energy structure and the development trends of advanced nuclear energy technology, combining the complementary advantages of nuclear energy and other energy sources in China, the Fluoride-Salt-cooled high-Temperature Advanced Reactor (FuSTAR) system has been proposed. FuSTAR system is designed to address production capacity issues in areas with energy shortages or resource concentration and can be combined with high-temperature process heat to achieve high-value-added processes such as hydrogen production. In this paper, the Tri-structural isotropic fuel combined with helical cruciform elements has been studied in detail on the neutron physics and thermal-hydraulic properties, and the flow and heat transfer experiment is carried out for the first time. The multilayer nonlinear programming method has been applied to the design of thermal transport systems. Then the optimal parameters and configuration of the thermoelectric conversion system are obtained by the superstructure optimization method. The inherent safety of FuSTAR is demonstrated through deterministic safety analysis. In addition, the iodine-sulfur cycle technology and the characteristics of tritium production are also analyzed. This study highlights the significant potential of integrating nuclear energy with other energy sources in an optimized energy-production system. • Multi-purpose reactor energy system for power - hydrogen - tritium production. • Over 50 % maximum thermal efficiency. • Simultaneous analysis of design, optimization, and safety. [ABSTRACT FROM AUTHOR]

In this era of global warming the importance of climate risk cannot be understated, and finding ways to reduce climate risk is a topic worthy of study. In this paper, we innovatively examine the role of renewable energy technology innovation on climate risk in China. In addition to their linear relationship, we also investigate the asymmetric and heterogeneous impact, detect the impact channels, and find that (1) increased renewable energy technology innovation can effectively alleviate the climate risk situation. Accordingly, the development of renewable energy technology innovation can make a significant contribution to CR abatement. (2) Pronounced impacts of renewable energy technology innovation on climate risk can be observed in the higher quantiles (75th and 90th) of climate risk. (3) Renewable energy technology innovation is a powerful weapon for eradicating climate risk in provinces with a higher level of government fiscal expenditure. And (4) renewable energy technology innovation has an impact on climate risk by facilitating energy consumption efficiency, which is a necessary mediator. These conclusions inspire us to put forward several corresponding policy implications for better climate risk governance and renewable energy technology innovation development. [ABSTRACT FROM AUTHOR]

To achieve the goal of "carbon peaking and carbon neutrality", China is vigorously developing renewable energy. This paper aims to examine the major contributors to regional inequality in renewable energy consumption by analyzing the 30 provinces in China. We have analyzed the inequality of China's renewable energy consumption with Dagum Gini coefficient, and then use the Generalized Divisia Index Model (GDIM) to decompose the influencing factors contributing to the inequality of renewable energy consumption. The main conclusions are summarized as follows: First, renewable energy consumption was higher in the western region than in the central and eastern regions, and the regional inequality in renewable energy consumption have increased over time. Second, the study reveals that inter-group disparity is the primary source of regional inequality in renewable energy consumption in China. Third, at the national level, the results of the GDIM decomposition show that economic development continues to rely on fossil energy consumption, which negatively impacts the low-carbon transition of energy. Given China's complex geographical conditions, it is crucial for different provinces to develop their own strategies for renewable energy development, taking into account unique resources and challenges. [ABSTRACT FROM AUTHOR]

The increasing generation of renewable energy and its concurrent technological innovation are driving the transformations of the energy sector, but little effort has been made at the regional level to specify the heterogeneous impacts of different types of renewable energy development on multi-dimensional energy security. Therefore, this paper establishes a four-dimensional energy security assessment system based on the current energy market situation and economic context of China. Renewable energy generation and technological innovation were simultaneously used as the core proxies for renewable energy development. Then, the panel quantile regression method was used to analyze the heterogeneity of the impact of solar, hydro, and wind energy on energy security, covering 30 provinces in China from 2006 to 2019. The empirical results show that renewable energy power generation generally promotes energy security, but it cannot be effectively applicable to all levels of energy security. Renewable energy technology innovation has surprisingly hindered energy security. These results can serve as a policy and practical guide, suggesting that provincial governments in China should implement energy security and renewable energy policies in line with local characteristics. • The redefined provincial energy security presents obvious spatial heterogeneity. • Panel quantile regression was applied to balanced provincial panel data. • Hydropower contributes only to medium and low levels of energy security. • Wind and solar power contribute differently to all levels of energy security. • Renewable energy technological innovation impedes energy security. [ABSTRACT FROM AUTHOR]

Clean energy plays an essential role in responding to environmental crises. Accurate forecasting of clean energy power generation can provide necessary references for the formulation of energy policy. This paper proposes a novel fractional discrete grey model with a dynamic time delay function (DTDFF-DGM (1,1)) to forecast clean energy power generation. This model introduces the fractional accumulation operator and the dynamic time-delay function into the discrete grey model, which ensures the priority of new information in the original data and improves the model's adaptability to different sample data. The optimal parameters of the model are calculated by the dynamic linkage between the fitting error and the test error, which effectively avoids the overfitting problem. Empirical studies have proved that the model has better prediction accuracy compared to other methods. Finally, the proposed model is employed to forecast clean energy power generation in China. The results show that from 2020 to 2025, the overall growth rate of hydropower, wind power and nuclear power in China will be 9.27%, 119.61% and 36.38%, respectively. Based on the discussion of the forecast results, relevant policy suggestions were made. This paper realizes the transformation from a static model to a dynamic model in methodology and promotes the sustainable development of clean energy power generation in application. [Display omitted] • A novel fractional discrete grey model is established. • The model is the general paradigm of the existing six discrete grey models. • The jump error is avoided in the transition from discrete to continuous. • The dynamic time-delay function is introduced. • China's clean energy power generation is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

This paper discusses the current development strategy, technology and industrialization of China's hydrogen energy industry in the transportation field, summarizes the characteristics and development experience, and makes a comparative study with the situation of some developed countries. The results show that the current development of hydrogen energy has formed a broad consensus in China and is becoming the overall development of China's national level consciousness. However, China's hydrogen energy industry is still facing problems such as high cost of comprehensive utilization, imperfect standards and regulations for hydrogen energy utilization, obvious tendency of industrial blind development and structural overcapacity risk. Therefore, some policy suggestions were proposed for the future development, such as strengthening top-level design, strengthening pilot demonstration, promoting the development of the whole hydrogen industry chain, and reducing the cost of hydrogen and fuel cell vehicles in the field of transportation. [Display omitted] • The development of hydrogen energy industry has become China's national consensus. • China has formed three major industrial clusters of hydrogen and fuel cells. • China's hydrogen industry is facing the risk of overcapacity. • China should strengthen the top-level design of hydrogen development strategy. [ABSTRACT FROM AUTHOR]

Despite the considerable contribution of hydropower for meeting electricity demand and meanwhile achieving free carbon emission, the rationality of hydropower exploitation needs to be reassessed in the context of hydropower curtailment being severe in some hydro-dominant areas. In this paper, a two-stage fuzzy-stochastic chance-constrained interval (TFCI) regional energy system optimization model under multiple complexities is developed for systematically assessing the rationality of existing hydropower exploitation plan, and reflecting the tradeoff between system cost and reliability for Sichuan territory where the exploitable hydropower resources rank first in China. Results showed that the degree of hydropower overcapacity would become far more severe under the real existing energy structure planning. Instead of continuously boosting hydropower exploitation, proper limitation on hydropower installed capacity expansion to make other renewable energy obtain deserved promotion can effectively reduce system cost and improve the utilization efficiency of all the renewable technologies. The highest utilization efficiency of hydropower, wind power and solar power could achieve [90%, 100%], [100%, 100%], and [100%, 100%], respectively. The obtained results also indicated that greater uncertainty about system cost may have to be faced if policymakers aim to lower risk and enhance system reliability. Suggestions are provided for eliminating the irrationality of hydropower in Sichuan and other similar hydro-dominant regions based on above mentioned conclusions. • Developing a TFCI model for the rationality of renewable energy development. • Evaluating Sichuan's hydropower exploitation from a comprehensive view. • Investigating far more severe hydropower curtailment under existing energy policy. • Suggesting proper limitation on hydropower exploitation. [ABSTRACT FROM AUTHOR]

Abstract Currently, wind and solar energy have not been well utilized in China, and the rate of abandoned wind and solar facilities in China is increasing annually. Renewable portfolio standards (RPS) are an effective system for promoting large-scale renewable energy integration and consumption and realizing the goal of renewable energy development. To clarify the interactive relationship between the different levels and multiple actors in RPS, this paper uses policy network theory to analyze the interactive relationship of stakeholders from the three aspects of network subject, network structure and network interaction. The policy network of the RPS consists of the policy community, professional network, intergovernmental network, producer network and issue network. Under the RPS, to meet their own needs, participants affect the formulation and implementation of the RPS through the actions of confrontation, alliance, competition and cooperation. In different stages of developing the RPS, the openness and integration of policy networks change accordingly. This study overcomes the limitations of past simple analyses of the actor relationship in the policy process and thereby offers certain reference significance. Highlights • The actors of RPS policy networks are analyzed. • This paper analyze the game relationship of the stakeholders from three aspects. • This research reveals the network relationship between multiple stakeholders. • This study breaks through the limitations of past analysis of actor relationship. [ABSTRACT FROM AUTHOR]

In January 2017, the Chinese government released the first special plan for the development of geothermal energy, named “ The 13th five-year plan for geothermal energy development and utilization (2016–2020) ”, which promotes the development of geothermal energy to the national energy strategic level. As a stable and low-carbon renewable energy, it is significant to develop geothermal energy to relieve air pollution and supply continuous base load power. This paper first introduces the resource endowments of geothermal energy in China, the current status and development targets of geothermal energy use, as well as series of related policies on China's geothermal energy. Then the economic, environmental and social benefits of geothermal energy development are analyzed respectively. Next, based on the PESTEL framework, this paper analyzes the unfavorable factors in the development of geothermal energy in China. Fourth, based on the PESTEL analysis results, we give some countermeasures and solutions for the future development of China's geothermal energy from two aspects of technology and policy. Finally, based on the above analysis, the corresponding conclusions and policy recommendations are given. [ABSTRACT FROM AUTHOR]

Factors influencing the development of renewable energy have emerged as a hot topic of policy discussion in recent years. However, the direct impact of natural resource dependence on renewable energy has been overlooked, especially in emerging economies. Using Chinese province data from 2005 to 2019, this study employs a nonlinear panel model and a Quantile Regression with Nonadditive Fixed Effects for Panel Data (QRPD) model to examine the impact of natural resource dependence on renewable energy development and explores the great importance of government policy support. The study indicates that the influence of natural resource dependence on renewable energy development supports the "conditional resource curse" hypothesis, showing a U-shaped nonlinear relationship. The effect of natural resource dependence and government policy support on the development of renewable energy shows a dynamic change trend. In the early stage of renewable energy development, policy support is crucial, while during the growing and mature stages, natural resource dependence exerts a stronger driving force. The results of the mechanism test indicate that natural resource dependence can boost renewable energy development through green technology innovation and environmental regulation channels. This paper's conclusion provides a theoretical foundation for fostering the sustainable development of the renewable energy industry and is vital to China's efforts to reach peak carbon and carbon neutrality. • Nonlinear panel and QRPD models are employed. • Impact of natural resource dependence (NRD) on renewable energy development is revealed. • Dynamic effect of NRD and government policy support is discussed. • NRD has a negative and then positive impact on renewable energy development. • Pathways to improve renewable energy development through NRD are identified. [ABSTRACT FROM AUTHOR]

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified. [Display omitted] • The impact mechanisms of traffic and temperature on the EB's RC are revealed. • The accuracy of the revised EB's operating schedule is greatly enhanced. • The impact mechanisms of carbon emissions reduction on the EB's RC are revealed. • The EB's RC under different charging modes is quantitatively evaluated. • The fast RC, sustained RC, and remaining RC of the EB are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

Identifying the research topics of China's energy transition policy and predicting future research trends are crucial for policymakers to make informed decisions and advance the energy transition. This study applied the Latent Dirichlet Allocation (LDA) to extract 26 major research topics from the 13,976 abstracts of Chinese policy research papers in web of science (WOS), conceptualized the five most popular topics and used the ARIMA model to predict trends over the next 36 months. The results show that except for Economic and Environmental Impact of Renewable Energy Consumption (Topic13), which will first experience unanticipated fluctuations and then show strong growth capacity, all other topics will continue to remain positive growth trend. Research and Development (Topic3) is driven by the urgency of China's energy transformation. Economic and Environmental Impact of Renewable Energy Consumption (Topic13) is driven by the potential for the development of renewable energy. Economic Impact of Climate Change (Topic26) is driven by the climate change debate. Economic Growth, Urbanization, and Energy Consumption (Topic7) is driven by a discussion of their relationship and the mechanisms influencing them. Regional Efficiency and Productivity Analysis (Topic19) is driven by regional differences in China's energy policies. [ABSTRACT FROM AUTHOR]

Clarifying the clean energy (CE) development path is significant for realizing energy system transformation, coping with climate risks, and ensuring energy and ecological security. This paper uses national data from China from 1978 to 2021 as a sample. It considers the year-by-year dynamic indicators of changes in technology, population, industry, and economic factors in the short term. It takes the mandatory carbon emission reduction targets set by the country as the basis for carbon constraints. The Markov chain model was introduced to construct a power demand structure prediction model under scenarios to more accurately quantify the energy-saving and emission-reduction paths under different carbon constraints and economic development scenarios. The results show that China's electricity demand will rapidly grow in the short term. The upper limit constraint of thermal power generation under the high and normal economic growth models still has room to grow in the short term under the target carbon emission constraint scenario. During 2025–2030, the overall lower limit growth rate of the CE power generation structure under the target emission reduction scenario must exceed 8%, and the overall growth rate under the high-efficiency emission reduction scenario must exceed 12%. By 2030, the proportion of hydropower in CE generation is estimated to decrease to 33.7%, while nuclear power, wind power, and photovoltaic power generation will increase to 16.3%, 30.5% and 19.5%, respectively. These results provide a reference for the government to formulate a CE development path against the background of carbon constraints. [Display omitted] • Clarified China's short-term energy development path under carbon constraints. • Thermal power will not exit the market quickly in 2030. • Constructed an energy and power prediction model under carbon constraints. • Wind energy and photovoltaic energy will become the main development energy sources. • Support low-carbon power sector transformation under carbon policies. [ABSTRACT FROM AUTHOR]

The global shift to renewable energy is conducive to carbon reduction, but its impact on the economy is still uncertain. Unlike existing research focusing on the effect of domestic renewable energy (RE), this paper considers the global RE connection among countries and examines the impact of global RE development on economic growth (EG) using China as a sample. In addition, we apply a novel wavelet-based quantile-on-quantile method, which can estimate the local influence of the α-quantile of global RE on the β-quantile of the EG in different periods. The finding shows that the upper quantiles of RE promote EG , and this effect is greater at the upper quantiles of EG in the medium- and long-term. This is mainly because China plays a leading role in RE development and has an advantage in exporting RE -related products with the development of global RE. The finding proves the growth effect, indicating that RE is a blessing for China's EG. However, in the short term, a higher level of global RE development impedes China's EG due to high upfront costs of RE production, fierce competition from other countries, and insufficient energy supply when significant investment shifts from non-renewable energy to RE. The empirical results provide important policy implications to balance RE 's short-term inhibitory effect and long-term promoting effect on EG in the process of the global energy transition. • The global RE connection and the impact of global RE development on economic EG. • Applying wavelet-based quantile-on-quantile method can estimate the local influence of global RE on EG in different periods. • Upper quantiles of RE promote EG is greater at the upper quantiles of EG in the medium- and long-term. • The growth effect indicating that RE is a blessing for China's EG. • Balance RE's short-term inhibitory effect and long-term promoting effect on EG in the process of energy transition. [ABSTRACT FROM AUTHOR]

The development of renewable energy is the key to tackling climate changes and ensuring energy security. Meanwhile, the process is usually associated with a huge investment and financing gap, especially for transitional countries like China. Hence, developing and innovating the traditional financial system is urgent. However, existing studies have mainly focused on traditional financial perspectives, and few papers have critically examined how digital financial inclusion affects the growth of renewable energy industries. To this end, using Chinese provincial data from 2011 to 2020 and applying Feasible Generalized Least Squares (FGLS) method, this study explores the effect of financial inclusion on renewable energy and its underlying mechanisms from the production and consumption perspectives. It is found that the impact of financial inclusion on the production side of the renewable energy industry is significantly better than on the consumption side, and there is heterogeneity effect in different energy resource varieties, different regional locations, and different financial regulation intensities. The financial inclusion on renewable energy has a significant pulling effect in photovoltaic and wind provinces, but not in large hydropower provinces. Then, its driving effect is particularly pronounced in the northern region. Nonetheless, it is not significant for renewable energy consumption in the southern region. Besides, this positive effect cannot be achieved without stronger financial regulation. The mechanism of action assessment finds that optimizes the consumption pattern, increase the competition of commercial banks, and improve technological innovation all contribute to the positive effect whereas, FDI shows the negative effect. This study provides new evidence on China's achievement of the energy transition, suggesting the need to further improve incentives for FDI firms and to strengthen consumption-side guidance. [ABSTRACT FROM AUTHOR]

Renewable energy is an effective solution to alleviate the energy crisis and achieve sustainable development, and is gradually growing into an important energy source to support economic and social development. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. Given this background, this paper proposes a novel evaluation method for renewable energy technical plans based on improved rough set theory and grey cloud model. Firstly, based on the normalized evaluation data, self-organizing map (SOM) clustering algorithm and system clustering analysis are adopted to discretize the evaluation attributes indexes and decision attributes indexes, respectively. Next, the improved rough set conditional information entropy method is used to calculate the index weights. Finally, the grey cloud model is employed to determine the grade classification of each evaluated plan. At the same time, each grade is quantified by assigning a corresponding score, and the comprehensive performances of renewable energy plans can be calculated, and then the ranking of different plans is achieved. Based on the actual renewable energy development data from a province in China, experiments were carried out to evaluate the performance of the proposed method. The results show that the proposed method performs better than some evaluation methods for renewable energy technical plans. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Use self-organizing map clustering algorithm to discretize the attributes indexes. • Apply improved rough set theory to determine the index weights. • Achieve the complete ranking of plans, and classify the plans into different levels. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation. [ABSTRACT FROM AUTHOR]

Exploring the relationship between government subsidies, market competition, and the total factor productivity (TFP) of new energy enterprises will help countries optimize renewable energy support policies in the context of carbon neutrality constraints and energy demand growth. Based on the panel data of 145 listed new energy enterprises from 2007 to 2020, this paper investigates how government subsidies affect the TFP of new energy enterprises and the moderating effects of market competition. Our main findings are as follows: (1) Government subsidies positively affect the TFP of new energy enterprises. Heterogeneity analysis suggests that government subsidies have a larger effect on the TFP of non-SOEs, midstream and upstream enterprises, and smaller enterprises. (2) Industry market competition negatively moderates the effect of government subsidies on TFP, while enterprise competition power has a positive moderating effect. The marginal effect of government subsidies is significantly positive only when the industry market competition is below a certain threshold or the enterprise competitive power exceeds a certain threshold. (3) Government subsidies enhance the TFP by promoting invention and utility model innovation of new energy enterprises. In addition, market competition significantly moderates the relationship between government subsidies and utility model innovation, thereby moderating the marginal effect of government subsidies on TFP. The findings contribute to a better understanding of the relationship between government support, market competition, and new energy development. [ABSTRACT FROM AUTHOR]

• Economy of waste PV module recycling is discussed based on cost-benefit analysis. • The costs and benefits of PV overall recovery process are analyzed. • Recovery of waste PV module will have a low economic potential in China. • Fiscal policy and recovery strategy are provided for government and enterprises. With the rapid development of renewable energy, the impact on environment and resource caused by waste photovoltaic modules has been realized gradually. To solve the problem, recycling becomes an effectual way. Therefore, the aim of this paper was to assess the economic feasibility of the photovoltaic modules recycling project in China by using cost-benefit analysis. It was found that, under the estimated treatment quantity will generate in China in 2020–2034, the recovery cost per kilowatt (kW) of photovoltaic modules will be 25.11 USD, the unit benefit is 25.68 USD/kW, and the unit net benefit is 0.57 USD/kW. The net present value (NPV) and benefit-cost ratio (BCR) are 21.14 million USD and 1.023. The sensitivity analysis indicated that the sale benefits of recycled materials and tax were the most sensitive factors affecting the project's economy. Finally, we proposed ways to improve the economy for the government and related enterprises. [ABSTRACT FROM AUTHOR]

Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

Among the regulatory policies, feed-in tariffs (FIT) and renewable portfolio standards (RPS) are the most popular to promote the development of renewable energy power industry. This paper uses system dynamics (SD) to establish models of long-term development of the renewable energy power industry under FIT and RPS schemes, and provides a case study of China's wind power industry by using scenario analysis method. The model, on the one hand, not only clearly shows the complex logical relationship between the factors but also reveals the process of coordination between the two policy tools in the development of the renewable energy power industry. On the other hand, it provides a reference for scholars to study similar problems in different countries, thereby facilitating an understanding of the renewable energy power's long-term sustainable development pattern under FIT and RPS schemes, and helping to provide references for policy-making institutions. The results show that the integrate implementation of FIT and RPS can promote long-term and rapid development of China's wind power industry given the constraints and actions of the mechanisms of RPS quota proportion, the tradable green certificates (TGC) valid period, and fines. In addition, in the period of the construction of the TGC market, RPS quota growth rate and fine have a no significant effect on industrial development, however, with TGC market game becoming more and more fierce, both of them have a significant positive impact on the long-term development of the industry. TGC valid period has little effect on industrial development in our study. At the end of the paper, policy implications are offered as references for the government. [ABSTRACT FROM AUTHOR]

• A hybrid prediction system is proposed to provide technical support for achieving energy sustainable development goals. • Extract original complex time series features using CEEMDAN. • Optimize Extreme Learning Machine using particle swarm optimization algorithm. • Experiments are conducted for four seasons of wind speed to verify that the model can effectively predict year-round data. • Experiments demonstrate that CEEMDAN-PSO-ELM can predict complex energy data efficiently and accurately. As environmental concerns and the energy crisis intensify, advancing the use of new energy sources such as wind and photovoltaic is an important means to achieve sustainable energy development. However, the random fluctuation characteristics and seasonality of wind and light make them difficult to predict, which brings many operational risks to grid security and power dispatch. Therefore, this paper uses the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) as the decomposition algorithm, which can effectively avoid the problems of modal confusion and noise residuals and better identify the trend, seasonality and nonlinear characteristics of the series. The Particle Swarm Optimization (PSO) algorithm is also utilized to improve the prediction accuracy and stability of the Extreme Learning Machine (ELM). Combining CEEMDAN and PSO-ELM models, a high-precision hybrid forecasting system that can effectively reduce the effects of stochastic fluctuations is proposed. In this paper, wind speed data from four different seasons at Changma wind farm in China are selected to verify the effectiveness and generalization ability of this hybrid prediction system. The results show that the improvement of ELM by PSO and CEEMDAN significantly improves the prediction accuracy of the model, and the hybrid prediction system can be applied to time series with different data characteristics and variation patterns in each season, and its prediction accuracy and model performance are significantly better than other comparative models. [ABSTRACT FROM AUTHOR]

Under the trend of global low-carbon development, reasonable and accurate prediction of electricity consumption plays an essential role in vigorously adjusting power system structure, promoting electrification, and other energy-saving and emission reduction measures. Considering the development trend of energy consumption, this paper introduces the Logistic model of energy structure into the system structure, and establishes a novel grey prediction model with system structure. According to the division of energy factors with similar attributes, this model seeks the internal relationship of the development of electricity consumption and describes the interaction between related factors and multiple main factors in the form of equations, which makes the model have better applicability and stability. In the validation part, the ten types of energy are divided according to their attributes, and the main factor group and the related factor group are distinguished. The model proposed in this paper is used for simulation and prediction, and is compared with the three types of models (six models). In the two cases, the simulation error of the new model is as low as 3.9790%, and the prediction error is 0.5645%. Compared with other models, the new model has shown good performance in the case of electricity consumption forecasting in China. The effectiveness of the optimization of the model in structure, background, and application is verified. At the same time, based on the analysis and prediction of China's consumption data, this paper gives relevant policy suggestions for developing China's power structure. • A novel model based on energy background (EPMGM(1,M,N)) is established. • The relationship of factors in the system are characterized by the equations. • A Logistic model based on energy structure is introduced to the new model. • China's electricity consumption is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

This paper analyzes energy-related CO 2 emissions and production water use as the constrictions for energy development in northwestern China. By two period division methods such as one-year one-period and multi-year phased period, CO 2 emissions per unit of GDP and production water use are decomposed with a temporal decomposition technique. By compared with the average national level, carbon intensity and water intensity in 2016 are decomposed with a cross-regional decomposition technique. After a pairwise comparison of each influence factor between studied regions, what causes the variations in both intensity indicators among these five northwestern provinces is distinguished. Then the restrictions of energy development could be studied within an integrated framework of decomposing CO 2 emissions and water use in two dimensions such as time and space. Besides, the secondary industry is divided into non-energy industry and energy industry for the analysis of the effects of energy industry development. Moreover, renewable energy substitution factor is newly added to the decomposition of CO 2 emissions per unit of GDP, which is acted as an influence factor for the reduction of CO 2 emissions by the change of energy consumption structure. Finally, policy suggestions for sustainable development of energy industry in northwestern China are proposed. • Carbon intensity and production water use are decomposed by a temporal LMDI technique with two methods of period division. • Carbon intensity and water intensity in 2016 are decomposed by a multi-region decomposition approach. • Renewable energy substitution factor has been added into the spatial-temporal decomposition of carbon intensity. • The secondary industry is divided into energy industry and non-energy industry. • Renewable energy should be promoted during energy development in northwestern China. [ABSTRACT FROM AUTHOR]

This paper analyzes energy-related CO 2 emissions and production water use as the constrictions for energy development in northwestern China. By two period division methods such as one-year one-period and multi-year phased period, CO 2 emissions per unit of GDP and production water use are decomposed with a temporal decomposition technique. By compared with the average national level, carbon intensity and water intensity in 2016 are decomposed with a cross-regional decomposition technique. After a pairwise comparison of each influence factor between studied regions, what causes the variations in both intensity indicators among these five northwestern provinces is distinguished. Then the restrictions of energy development could be studied within an integrated framework of decomposing CO 2 emissions and water use in two dimensions such as time and space. Besides, the secondary industry is divided into non-energy industry and energy industry for the analysis of the effects of energy industry development. Moreover, renewable energy substitution factor is newly added to the decomposition of CO 2 emissions per unit of GDP, which is acted as an influence factor for the reduction of CO 2 emissions by the change of energy consumption structure. Finally, policy suggestions for sustainable development of energy industry in northwestern China are proposed. • Carbon intensity and production water use are decomposed by a temporal LMDI technique with two methods of period division. • Carbon intensity and water intensity in 2016 are decomposed by a multi-region decomposition approach. • Renewable energy substitution factor has been added into the spatial-temporal decomposition of carbon intensity. • The secondary industry is divided into energy industry and non-energy industry. • Renewable energy should be promoted during energy development in northwestern China. [ABSTRACT FROM AUTHOR]

• The carbon emissions reduction control rate is considered in the economic growth model. • The PLS regression technique and a Markov chain method are used. • Two different potential economic development scenarios are evaluated. • The evolution trends and the optimisation modes of energy mix in different scenarios are explored. • Suggestions on the multi-objective optimisation of energy mix are put forward. Achieving the goals of emissions intensity reduction and energy mix transition along with steady economic growth is a hot topic in China. This paper constructs an economic growth model under emissions reduction control. Using the PLS regression technique, the potential economic growth rates are calculated as 6.64% and 5.35% in 2020 and 2030, respectively. Moreover, employing the Markov chain method and multi-objective optimisation model, we also investigate the evolution trends and the optimisation modes of energy mix in different scenarios. The results show the proportions of clean energy cannot meet the policy targets in the BAU scenario. However, the goal of energy mix can be realized in the "3E" scenario, and a more low-carbon energy consumption structure will be promoted in 2020 and 2030. Furthermore, our results suggest that the Chinese government needs to transform the extensive traditional economic development pattern and strive to achieve the "3E" coordinated development pattern. [ABSTRACT FROM AUTHOR]

China is very ambitious for the development of fusion energy system using the fusion reaction of hydrogen isotopes. According to China magnetic confinement fusion development roadmap, the China Fusion Engineering Test Reactor (CFETR) is expected to be constructed in 2020s, which will be the first hydrogen fusion reactor in China. However, China has not yet established the safety regulatory framework for the licensing of a hydrogen fusion reactor such as CFETR, while the existing regulatory framework is based on the fission reactor development and there are huge differences in the safety characteristics between fusion reactor and fission reactor. In this paper, China's nuclear safety regulation system is reviewed and then key issues are raised for adapting the regulatory framework to the hydrogen fusion reactor, considering the fusion safety characteristics as well as lessons learnt from the licensing of ITER in the French regulations. Gaps between China nuclear safety regulations and CFETR safety concerned demands are also identified and discussed. It is suggested that the engineering design of CFETR shall be done together with the development of corresponding safety regulatory framework. • Gaps identified between China nuclear safety regulations and CFETR safety concerned demands. • Key issues raised for the adaption of regulatory framework to hydrogen fusion reactor. • Overview of China's existing nuclear safety regulation system. [ABSTRACT FROM AUTHOR]

Abstract To achieve China's 2030 goals for renewable energy development, this paper proposes a constrained fuzzy multi-objective optimization (FMO) model to obtain the optimal generation mix of four kinds of renewable power: hydropower, wind power, photovoltaic (PV) power, and biomass power. The optimization results show that a ) the optimal mix of accumulated installed capacity of renewable energy in China from 2017 to 2022 is hydropower > wind > PV > biomass, while that from 2023 to 2030 is PV > hydropower > wind > biomass; b ) the accumulated installed capacity of PV has the fastest growth between 2017 and 2030, and PV power will replace hydropower as the largest renewable power source in 2023. However, hydropower remains the largest renewable power through 2030 in terms of on-grid power generation; c ) these four kinds of renewable power generation can eliminate 34.9–37.5 billion tonnes of CO 2 emissions by replacing coal-fired power generation, with hydropower contributing the most to the reduction; and d ) Investment cost per kilowatt or the rate of power curtailment is not sensitive factor for optimal cumulative installed capacity. The results mean that China should promote PV power generation in a rapid but systematic manner while continuing to develop hydropower. Highlights • An FMO model for renewable energy generation mix is proposed. • Four kinds of renewable energy generation in China are optimized. • PV power will replace hydropower as the largest renewable power source in 2023. • Renewable power generation can reduce CO 2 emissions by 27.9–30.3 billion tons. [ABSTRACT FROM AUTHOR]