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Strengthening environmental regulation (Reg) is an important measure to solve energy and environmental problems, then to realize the profit sustainable growth (Gro). Taking 116 listed renewable energy enterprises in China from 2010 to 2019 as samples, this paper uses FE and SYS-GMM models to examine the moderating effect of three types of Reg in the relationship of factor market distortions (Dist) and the Gro. The conclusions are as follows: For the direct impact, capital and labor market distortions (DistK and DistL) hinder the Gro. Specifically, the absolute value of the coefficient of DistK in state-owned enterprises (SOEs) is greater than that of the DistL, which indicates that the inhibitory effect of DistK in SOEs is more significant. For the indirect impact, the coefficients of economic and supervised environmental regulation (RegE and RegS) are positive and significant, and promote the Gro of SOEs and non-SOEs, while legal environmental regulation (RegL) is the opposite, which shows that Reg has significant "cost effect" and "rebound effect". Moreover, Reg has a positive moderating effect, which is mainly reflected in SOEs, and alleviates the inhibitory effect of DistK and DistL on Gro to a certain extent. Finally, this paper puts forward some targeted policy suggestions. [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]

This paper uses panel data on renewable energy in China. Thus, the current analysis fills the gaps by examining the relationship between green technology innovation and renewable energy and CO 2 emissions from 1990 to 2018. The current study examines all concerns connected to panel data analysis with advanced panel estimators, such as cross-sectional dependence, stationarity, variation in slope parameters, and structural break. Our findings show that test results reveal that green technology innovation and renewable energy have a negative and considerable influence on CO2 emissions in the long run. Moreover, the short-run relationship of green technology innovation, on the other hand, is not significant—as evidenced by the findings of robustness tests such as AMG and CCEMG. Other empirical results revealed that GTI, REN and NEN significantly reduced local CO 2 emission, while POP and PI had no obvious reduction effects on CO 2 emissions. Different GTIs had the same spatial "symbiotic effects" on CO 2 emission reduction in the short term, showing positive spatial spillover reduction effects. Lastly, we conclude that the use of green technology innovation has positive externalities. Some policies to assist green innovation technologies and renewable energy resources have been suggested for the Chinese government to enact. • This paper uses panel data on renewable energy in China. • The current study examines all concerns connected to panel data analysis with advanced panel estimators. • The short-run relationship of green technology innovation is not significant. • We conclude that the use of green technology innovation has positive externalities. [ABSTRACT FROM AUTHOR]

The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy (RE) in the power system and establish an electricity mix dominated by RE power. According to China's 14th Five-Year Plan, the proportion of non-fossil energy power generation should reach about 39% by 2025. However, the impact of the increase in share of RE power on carbon emissions of the electricity sector remains to be estimated. To this end, the purpose of this paper is to capture the nonlinear characteristics of RE on electricity-related carbon emissions by using panel smooth transition regression (PSTR) model and provincial panel data covering the period 1991–2020 under the background of provincial RE quota system. The estimation results indicate that, (i) in the four transition variables of PSTR model such as the installed capacity of power generation, substation equipment capacity, total electricity consumption and total power generation, the nexus between RE deployment and electricity-related carbon emissions was detected as nonlinear. (ii) The heterogeneous RE carbon abatement effect is reflected in its increasing penetration in provincial power systems. (iii) Carbon abatement performance of RE generation decreases in the negative range with the increase of transition variables. (iv) The estimation coefficient of RE is positive at the higher value of the transition variable in the PSTR model of carbon emissions per capita. As a result, the RE quota with the best emission abatement performance should be designed based on the provincial power resource endowment and the medium and long-term expected electricity consumption. [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]

With the increasing penetration of renewable energy, the traditional energy storage operation based on individual framework —users own and operate independently mode may become impracticable due to conflicting interests, insufficient utilization, and poor interoperability. Riding on the wave of the proliferation of sharing economy, storage energy sharing expands the existing storage energy without requiring costly and time-consuming infrastructure investments. However, the development path of shared energy storage (SES) mode is not clear due to the asymmetric decision-making of the owners of energy storage systems under bounded rationality. In this paper, the diffusion of the business model of SES among multiple renewable energy stations (the owners, RES) and its key factors are analyzed based on the evolutionary game. The goal is to maximize social welfare and ensure the continuous growth of the sharing market. The numerical simulation is carried out based on the data from northwest China to interpret the development path. The result shows that, in renewable energy cluster the stations with intermittent output or with the higher prediction accuracy are more willing to participate in sharing. The energy storage sharing mode fails when the energy storage capacity ratio of RES is less than 10%. While the high-level ratio (more than 30%) is not conducive to the diffusion of the sharing model in RESs with low power generation prediction accuracy. [Display omitted] [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]

Renewable portfolio standard is an effective administrative tool to guide the behavior of electricity producers and impact the renewable energy diffusion. However, currently the renewable energy quota is generally set to be static and the efficiency is limited. In this paper, we proposed a dynamic renewable portfolio standard policy and we aimed to analyze how it will impact the renewable energy diffusion in China. The connections between electricity producers were simulated under both the perfectly competitive market and monopoly market. And a networked evolutionary game approach is applied considering dynamic linking between the electricity producers. The results show that dynamic quota policy is effective in promoting the proportion of wind power generation from 20% to 59.17% and promoting the proportion of solar power generation from 20% to 79.25%. With the sensitivity analysis, we found that renewable energy quota and the on-grid price are the most influential parameters. The proportion will reach 76.47% if quota is 0.7 and 68.1% if on-grid price is 630 Yuan/MWh. And the influence of tradable green certificate prices and generation cost is limited in promoting renewable energy diffusion. This paper offers the Chinese government a potential implementation for the perfection of national renewable energy diffusion. [Display omitted] • Propose a novel dynamic renewable portfolio standard scheme. • Analyze the influences of different kinds of the electricity market. • Investigate parameters affecting the wind power and solar power generation. • Establish dynamic networked evolutionary game models. • Dynamic linking is considered when the connections of players change. [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]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, the renewable energy technology innovation (RETI) may have a potential impact upon the industrial structure upgrading, while green finance will play a moderating part. This paper studies the role of green finance and renewable energy technological innovation on industrial structure in China. We found that RETI has contributed significantly to the adjustment of industrial structure. The research results of PVAR (Panel Vector Autoregressive) model further prove this dynamic and continuous positive promotion. The threshold regression results indicate that with the improvement of green finance, there is a non-linear relationship between RETI and industrial structure. In areas where green finance is relatively low, RETI can inhibit the upgrading of industrial structure. When the degree of green finance development is relatively high, the influence of RETI on industrial structure is remarkably positive. Heterogeneity analysis shows that in eastern China, renewable energy technological innovation has significantly promoted the industrial structure upgrading. Therefore, policy makers should take various measures to expedite the green finance development and strengthen the green finance support to renewable energy technology innovations. Chinese government has the need to continue to implement related green credit policies and expand the source of green funds. • Study the impact of renewable energy technology innovation on industrial structure. • Green finance is a moderating variable. • Threshold regression model is used to study nonlinear relationship. • Renewable energy technology innovation positively impacts industrial structure. • Green finance has a positive moderating effect. [ABSTRACT FROM AUTHOR]

Green economic growth and sustainable development are inextricably linked, and encouraging green economic growth has practical implications in today's world. In this context, this study examines the impact of environmental regulation on renewable energy development and China's green economy from 1990 to 2018. We look at how environmental regulations affect green economic growth and renewable energy technologies. Using the Meta frontier SBM model's super-efficient data envelopment analysis, it is possible to determine the relative level of green economic growth in China's provinces based on their energy efficiency. Environmental regulations were also assessed using an improved fuzzy inclusive appraisal method. Finally, we investigate the possible mechanism and discuss our findings. The study discovered an unreliable indicator of green growth during the research period, attributed to the non-serious nature of government strategies. The results show that the DEA method consistently confirms how the piece is put together. On the other hand, the sub-results models invariably affect countries with high GDP per capita. Finally, the impact of environmental regulations on the growth of renewable energy sources was studied. Green economic growth depends on environmental regulation policies, which contribute significantly to renewable energy development. Population size, economic development level, technological innovation, industrial structure, urbanization, environmental regulation, and FDI influence green economic growth, but the spatial effect of each influencing factor varies. The findings of this paper form the basis for China's pursuit of green economic growth and the development of renewable energy policies. • Proposed a novel framework on R & D expenditures, low carbon energy transition and green economic growth. • Study analyzes the effects of the multiple R & D expenditures in the context of Belt & Road Initiative economies. • Dynamic linking is considered when the connections of players' change. • Established vibrant empirical model and suggested implications for green economic recovery. [ABSTRACT FROM AUTHOR]

As a result of the COVID-19 epidemic, a worldwide economic slump has reduced the depletion of natural resources, lowering their costs. The loss of renewable energy profitability might hinder the attainment of specified goals of sustainable development goals. By using Chinese provinces data from 1995 to 2020, this research examined the relationships between renewable energy investment (REI), green finance (GFI), growth of the economy (GDP), renewable energy production (REP), and private sector participation (PSP) in China. According to this analysis, REI, REP, and GFI are more variable throughout the given period than GDP. And PSP. A bidirectional substantial causal correlation between REI and REP was identified using the Generalized method of moments (GMM). Still, the regression coefficient between GDP and REI and REI. and GFI has a one-way causal relationship. There was no evidence that the PSP directly impacted the REI. Based on the empirical findings of this research, we propose that policies be designed to reduce volatility in REI GFI, and REP and increase support to improve sustainable economic development and environmental and renewable energy production. Examine between green financing and environmental conservation for long-term environmental quality. • There is a dire need to measure the examined the relationships between renewable energy investment (REI), green finance (GFi). • Bidirectional substantial causal correlation between REI and REP was identified using the Generalized method of moments (GMM). • There was no evidence that the PSP had a direct impact on the REI. • This paper improve sustainable economic development as well as environmental and renewable energy production. [ABSTRACT FROM AUTHOR]

The issue of large-scale retirements of renewable energy modules has attracted considerable attention from governments and the public worldwide. Using the Chinese wind and photovoltaic industries as examples, this paper, for the first time, employs a real options approach to explore the optimal time for energy firms to retire their power plants and to predict the future trend of renewable energy wastage from a bottom-up perspective. The results show that the optimal retirement time for the four subdivided categories ranges from 16 to 23 years. The later the investments are made, the earlier the decommissioning time comes and the lower the project returns. Furthermore, wind projects have been found to generate more revenue than PV projects for the same size, and the gap continues to widen. Offshore wind technology always has the longest optimal service life (18.62 years in 2022) and the greatest project returns (10.84 million CNY in 2022). Annual utilization hours, the renewable electricity price and the waste price can accelerate the retirement of plants and generate more revenue for energy companies, while the initial investment cost has a completely opposite effect. The first wave of PV retirements will occur in 2035 at 305.82 GW, while onshore wind will be in 2036 at 530.77 GW and offshore wind will not explode until 2040 at 65.84 GW. An assessment of potential policies suggests that for every 100 CNY increase in incentive strength, the retirement wave arrives 1 year earlier. In contrast, for every 100 CNY increase in the strength of penalties, the retirement wave is delayed by 1 year. In addition, we verify that the size of the plants does not affect the forecast of the retirement trend, indicating that the assumptions about installed capacity do not cause bias. [ABSTRACT FROM AUTHOR]

With the growing share of the climate-sensitive renewable energy market supply in China, estimating future energy drought risk (ED) is essential. In this paper, based on CMIP6, energy demand and power generation are estimated from 2023 to 2100 under SSP2-4.5 and SSP5-8.5 climate scenarios, and ED is defined from high demand (HD), low wind-solar generation (LWS), and residual load (RL). The results show that the ED exacerbation is relatively high under the SSP5-8.5. Between 2023 and 2100, the duration and severity of HD and RL notably increase, while LWS changes are relatively weak. We find that HD and RL exhibit high summer risks in the south and high winter risk in the north. The return periods vary significantly and extends over time in most regions. Moreover, there are few ED when the installed power generation capacity (IPGC) is increased. When the IPGC increases by 2%–5%, the LWS will decrease at least 20%–72%. With a 10% increase, the LWS will be mitigated by at least 80%, whereas the mitigation for RL is limited, approximately 3–17% at different rates. This work performs the first evaluation of future ED and provides the useful references for risk mitigation in China based on CMIP6. [ABSTRACT FROM AUTHOR]

Due to the inherent uncertainty and the mismatch between renewable energy output and load demand, renewable energy-based system optimization is increasingly important in China. Therefore, electricity demand response (EDR) is critical to the stability and efficiency of an integrated renewable energy system (IRES). The customers' demand response under the time-of-use (TOU) mechanism is the key to the entire process. However, how to optimize integrated renewable energy system based on accurately identifying the electricity demand response participation of customers is one of the main issues at this stage. To solve the problem, this paper presents a novel approach for integrated renewable energy system optimization considering electricity demand response management and multistage energy storage systems from the perspective of Fujian Province, China. To enable large-scale renewable energy integration, the original output is processed using the Hampel identifier (HI)-Savitzky-Golay filter (SGF) technology. A machine learning (ML)-based identification model is developed for EDR to determine whether the customers are participating or not. Driven by the time-of-use mechanism, customers can make dynamic adjustments based on the Logistics function. After that, an integrated renewable energy system model optimization strategy is proposed based on satisfying customers' electricity demand response. Throughout the optimization process, the multistage energy storage system plays a vital role in the residual fluctuation absorption for renewable energy filtering, the dynamic adjustment process of the demand response, and the integrated renewable energy system optimization. Through extensive case studies and discussions, it is demonstrated that random forest (RF) and support vector machine (SVM) reach 80 % identification accuracy with a 20 % testing ratio. According to the optimization approach proposed in this paper, the minimum operation cost can be calculated to be 9.336*106 CNY. The methodology presented in this paper establishes a special relationship between electricity demand response identification and dynamic adjustments, and provides an optimization model for Fujian Province, China, which is a reliable reference for future work. [ABSTRACT FROM AUTHOR]

The increasing importance of innovation-driven development requires empowering enterprises as the main drivers of innovation in emerging energy technologies. The existing literature primarily emphasizes government support for renewable innovation, with limited research on external collaborations. This paper searches and collects announcements of listed renewable energy companies regarding strategic alliances during 2009–2021 to explore whether renewable energy alliances promote innovation and their mechanism to motivate innovation efforts, using the Two-way Fixed Effects Model. The main results suggest that renewable energy alliances increase innovation output significantly. The mechanism analysis reveals that establishing renewable energy alliances indirectly enhances innovation output via transaction cost savings and alleviates financing constraints. The heterogeneity analysis indicates that factors such as firm ownership, size, knowledge absorption capacity, green investor concerns, and enterprise life cycle significantly impact the innovation incentives from renewable energy alliances. This paper enriches the research on the drivers of renewable energy innovation and provides policy insights for encouraging autonomous innovation in renewable energy enterprises. [ABSTRACT FROM AUTHOR]

Poverty alleviation is an important work of the Chinese government in recent years. According to the international poverty standards of the world bank, China's poverty reduction population accounts for more than 70% of the world. Photovoltaic poverty alleviation is a significant way for regions rich in solar energy resources to transform the advantages of renewable energy resources into the driving force of social and economic development. It is also an effective means for China to implement power poverty alleviation. While promoting emission reduction in these regions, it accelerates economic development and implements targeted poverty alleviation. This paper analyzes the comprehensive benefits of typical market entities of photovoltaic poverty alleviation projects, and establishes the environment, economic and social benefit evaluation models for poor households, the state and government, photovoltaic enterprises and grid corporation. In the model, we creatively put forward an index system to characterize the poverty alleviation effect, and consider the additional industrial benefits brought by photovoltaic poverty alleviation projects. Finally, a typical photovoltaic poverty alleviation project in Haiyuan County, Northwest China is selected to verify the feasibility of this model. [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]

This paper examines the nexus between fiscal decentralization and renewable energy demand by including income inequality, economic growth, urbanization, and economic globalization as the main determinants in the energy demand function for the case of China. Quarterly frequency data for the period 1980–2018 are used for empirical analysis. Our empirical results show fiscal decentralization positively impacts the demand for renewable energy; in other words, fiscal decentralization can help increase renewable energy demand. In addition, income inequality is negatively linked to renewable energy consumption, while economic growth is positively associated with renewable energy demand. Urbanization and economic globalization add to renewable energy consumption. This study presents Chinese authorities with new guidelines for using fiscal decentralization as an economic tool to formulate effective energy policies for long-term development of the use of renewable energy sources. [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 China Certified Emission Reduction scheme (CCER) and the Cap-and-Trade (CaT) mechanisms jointly constitute the Emission Trading Scheme (ETS), which is expected to have a profound impact on China's social and economic decarbonization. However, previous studies have primarily focused on the impact of the CaT mechanism, neglecting the fact that CCERs serve as a carbon offset trading mechanism. This paper focuses on the impact of the CCER mechanism on China's energy economy and environment by constructing a recursive dynamic computable general equilibrium model that couples CaT and CCER mechanisms. Introducing the CCER mechanism based on the CAT mechanism leads to increased output and reduced prices in renewable energy sectors, cascading positive effects across various energy-utilizing sectors to counter the decline in Gross Domestic Product (GDP) and residential welfare. The finding suggests that China's unique CCER mechanism is poised to play a more important role in promoting renewable energy to mitigate global warming, given its potential to transform the structure of energy production and consumption. Finally, targeted policy recommendations are proposed for implementing the CCER mechanism. [ABSTRACT FROM AUTHOR]

The China Certified Emission Reduction scheme (CCER) and the Cap-and-Trade (CaT) mechanisms jointly constitute the Emission Trading Scheme (ETS), which is expected to have a profound impact on China's social and economic decarbonization. However, previous studies have primarily focused on the impact of the CaT mechanism, neglecting the fact that CCERs serve as a carbon offset trading mechanism. This paper focuses on the impact of the CCER mechanism on China's energy economy and environment by constructing a recursive dynamic computable general equilibrium model that couples CaT and CCER mechanisms. Introducing the CCER mechanism based on the CAT mechanism leads to increased output and reduced prices in renewable energy sectors, cascading positive effects across various energy-utilizing sectors to counter the decline in Gross Domestic Product (GDP) and residential welfare. The finding suggests that China's unique CCER mechanism is poised to play a more important role in promoting renewable energy to mitigate global warming, given its potential to transform the structure of energy production and consumption. Finally, targeted policy recommendations are proposed for implementing the CCER mechanism. [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]

Corporate environmental information disclosure systems are important for controlling pollution caused by corporate activities. However, different motives associated with environmental information disclosure have different influences on the financing of companies. This paper adopts renewable energy companies instead of high pollution industries as a research object. The study analyzes the resource-dependent disclosure motivation of renewable energy companies, and the impact of environmental information disclosure on the scale and cost of direct and indirect financing. The results show the following. First, renewable energy companies in China have a resource-dependent motivation to disclose environmental information, with a gap between the level of environmental information disclosure and their actual environmental performance. Second, renewable energy companies may obtain more direct financing amount and lower indirect financing costs, but cannot obtain lower direct financing costs and more indirect financing amount by improving the level of environmental information disclosure with the resource-dependent motivation. Third, there are differences in the specific incentives for environmental information disclosure among the Eastern, Middle, and Western regions of China. The government needs to standardize the detailed rules and standards of the corporate environmental information disclosure system, and improve the environmental protection awareness and the implementation of green credit in the Western region. [ABSTRACT FROM AUTHOR]

To achieve a high penetration of renewable energy integration, an effective solution is to explore the interdependence between numerical weather prediction (NWP) data and historical wind power to improve prediction accuracy. This paper proposes a novel combined approach for wind power prediction. The characteristics of NWP and historical wind power data are extracted by using the feature extraction technique, the predictor is designed based on extreme learning machine (ELM) and least squares support vector machine (LSSVM) model, and then key parameters of the prediction models are optimized by improving cuckoo search (ICS) to obtain a reliable value, which is defined as the pre-combined prediction value (PPA). To obtain a reliable result, a variance strategy is developed to allocate the weights of the pre-combined prediction model to obtain the final predicted values. Four seasons dataset collected from regional wind farms in China is utilized as a benchmark experiment to evaluate the effectiveness of the proposed approach. The results of comprehensive numerical cases with different seasons show that the proposed approach, which considers multiple-error metrics, including error metrics, accuracy rate, qualification rate, and improvement percentages, achieves higher accuracy than other benchmark prediction models. • A novel combined framework is proposed to predict short-term wind power. •Linear and nonlinear feature extraction strategies are applied to analyze the character of NWP data. •A variance combined strategy is used to allocate the optimal weight of the primary combined model. •The wind power prediction error analysis is conducted by multiple-error performance metrics. [ABSTRACT FROM AUTHOR]

An efficient and equitable allocation scheme for renewable portfolio standard (RPS) quota is of great significance to renewable energy (RE) development and the improvement of the electricity trade market. This study establishes a quota allocation model based on the lowest cost of RE generation to determine the RPS targets (LC-RPS) of 30 Chinese provinces. Subsequently, an index system based on energy consumption, RE resource endowment, historical responsibility, and transmission facilities is constructed to determine the RPS targets (IN-RPS). Finally, the two scenarios mentioned above are compared with the RPS target allocation scenario published by the Chinese government (GM-RPS) and with the NO-RPS scenario. The results show that: Compared with those of GM-RPS and IN-RPS, the power generation cost associated with the LC-RPS is reduced by 8.5% and 49.4%, respectively, and the unit power generation cost is reduced by 9.4 and 39.7 RMB/MWh, respectively; the fairness of the LC-RPS is marginally worse than that of the other three scenarios, but the fairness of the power generation cost is still relative average, thereby demonstrating distribution fairness. This paper appeals to the Chinese government for the perfection of a national renewable energy certificates (REC) trade market and offering additional REC for solar generation. •Least-cost quota (LC-RPS) and index system allocation schemes are proposed. •The renewable energy (RE) generation capacity of 30 Chinese provinces is determined. •The power generation cost of the LC-RPS is reduced compared with other schemes. •The LC-RPS scheme is more efficient and meets national RPS targets. •The generation resources are diversified with the improvement of the national REC trade market. [ABSTRACT FROM AUTHOR]

Offshore wind power is an important renewable energy source and plays an essential role in optimizing the energy structure worldwide. Simultaneously, offshore wind turbine (OWT) selection is a complicated process since it concerning various variables and optimization scenarios. In this paper, a novel fuzzy Bayesian network-based model for multiple-attribute decision-making (MADM) is proposed. First of all, a three-layer decision-making framework for OWT selection is established through systematically combing previous studies, expert knowledge, and the principal component analysis (PCA) results by treating the wind turbine parameters, wind turbine economy, wind turbine reliability, and navigation safety as the attributes, and the corresponding 11 influencing factors are identified and quantified. Moreover, a triangular fuzzy number is introduced to fuzzify each influencing factor, and the belief degree for different linguistic variables corresponding to the specific influencing factor is employed in the fuzzy IF-THEN rule system. Then, the belief rule base is transformed into the Bayesian network as the conditional probability tables (CPTs), which can directly express the influence relationship of various factors and realize the integration of various influence factors to obtain the optimal scheme. Finally, the proposed model is validated by taking a case study in busy waterways in the Eastern China Sea as an example. This research provides an intuitive, feasible, and practical way for OWT selection. • A novel fuzzy Bayesian network-based MADM model for OTW selection in busy waterways is proposed. • A three-layer decision-making framework is established for the OWT selection. • Comprehensively consider each influencing factor's qualitative and quantitative characteristics. • Model can not only conduct the uncertainty caused by ambiguity but also intuitively achieve optimal reasoning and evaluation. [ABSTRACT FROM AUTHOR]

China, India, and the USA are the world's biggest energy consumers and CO 2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO 2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO 2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO 2 emissions. This indicates that curbing CO 2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal. • Renewable energies, coal consumption, economic growth, and CO 2 we examine. • We investigate the causal predicted relationship on China, India, and the USA. • An advanced methodology in Machine Learning is used. • India has a prediction of an increase in emissions of CO 2. • China and the U.S. present a more promising path to sustainability than India. [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]

The increasing penetration of renewable energy leads to seasonal fluctuation in the power system. This also results in continuous low-renewable-output events, which pose significant challenges for ensuring adequate renewable energy supply and arouse growing concern. To analyze the seasonal fluctuation characteristics of renewable in different timescales, this paper first decomposes the renewable time series into three components: climate, seasonal, and daily. Then an Itô process is introduced to model the climate and daily components considering the time series' stochastic characteristics and time correlations. Finally, the proposed model is first tested based on case studies on historical data from two selected weather stations in China. Moreover, the method is further applied to analyzing data from 253 weather stations across China at the provincial level. The results indicate that low-renewable-output events are more likely to have a longer duration in central China. [ABSTRACT FROM AUTHOR]

In the context of the construction of new power system, the installed scale of energy storage is steadily increasing in order to deal with the problem of safe and reliable operation of the system resulting from a large proportion of renewable energy installations connected to the grid. The pumped storage plants (PSP) have peak shaving, frequency modulation and standby functions which play a major role in ensuring the safety of the system and the consumption of renewable energy. By analysing the evolution of the pricing mechanism of transmission and distribution (T&D) tariffs and PSP, this paper analyses the influencing factors of PSP on T&D tariffs under different stages of electricity market development and establishes a conduction model. The empirical analysis shows that as the electricity market improves, the costs that PSP need to conduct through T&D tariffs continue to decrease. Therefore, it is necessary to accelerate the construction of the electricity market and to reflect the value of PSP through market regulation, in order to enable the PSP to recover part of their fixed capacity costs without relying on T&D tariffs, and to gradually achieve self-profitability. [ABSTRACT FROM AUTHOR]

With the large-scale integration of wind and solar power in China, the consumption of these intermittent renewable energies is severely restricted by the capacity of the transmission channel, which leads to massive renewable energy curtailment. Therefore, it would be beneficial to use limited transmission channels to absorb as much renewable energy as possible. In this paper, we propose a chance constraint-based multistage nested hydro-wind-solar coordinated optimal scheduling model to aid peak shaving while ensuring maximum power generation. First, multistage partitioned section chance constraints are introduced to mitigate the power congestion of the transmission network. Then, based on the principle of using hydropower to complement the uncertainty of wind and solar power, the compensation chance constraints are considered. To quantify the uncertainty of wind and solar power, their prediction errors are analyzed using the Gaussian mixture model. Finally, the model is recast and linearized into a mixed integer linear programming model. A case study of a hydro-wind-solar base in Southwest China demonstrates that the proposed model can effectively leverage the regulation ability of hydropower to coordinate multiple power sources with the restrictions of multistage transmission sections, effectively alleviating the congestion of transmission channels and reducing the curtailment of renewable energy. [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]

To find an efficient and economic way to convert wave energy, a one-base multi-buoy offshore floating wave energy converter Sharp Eagle Wanshan is designed, consisting of four absorbing buoys, one semi-submersible barge, and other components. The working principle of the device is described in this paper. An experiment of a 1:13.78 model machine was carried out to test the hydrodynamic performance of the device and make an initial evaluation for the design The influence of wave period, wave height, work load and wave direction was tested. After construction, two-stage open sea tests have been finished in the waters near Wanshan Islands from November 2015 to June 2016. The device showed great power generation capacity with total generated output of 30530.57 kWh, and largest daily generation of 1847.09 kWh. During the open sea tests, the energy conversion efficiency was measured, and results show that capture width ratio of Wanshan remains higher than 20% in the wave period between 4 and 6.5 s and wave height range of 0.6–1.8 m. After operating in a wide range of conditions, including a tropical storm on May 27, amounts of tests data, experiences and lessons have been obtained and will be summed up and presented in the paper. [ABSTRACT FROM AUTHOR]

The abundant geothermal energy in hot dry rock (HDR) formations is an attractive renewable energy resource with great potential. China will develop its first HDR geothermal formation in the Gonghe Basin. HDR is a hard and low-permeability granite containing very few fluids. Development requires fluids to cyclically flow between injection and production wells to extract geothermal energy in the artificial heat transfer zone. Hydraulic fracturing is the main technology for creating flow paths. But few studies have investigated fractures in HDR geothermal formations. This paper investigated fractures as flow paths in HDR geothermal formations during hydraulic fracturing. Hydraulic fractures were simulated using a custom true-triaxial hydraulic fracturing test system in a realistic formation environment, in which a scaled wellbore was used that was built in outcrop granite rock from the Gonghe Basin. Fracture creation in granite was investigated via experiments, as well as influence factors, and what experience could be achieved. This study can be used to design and evaluate hydraulic fracturing projects in potential HDR geothermal formations. • Hydraulic fracturing was simulated in high temperature via experiment. • Fracture creations were studied in outcrop granite of HDR geothermal formation. • In-situ stress and weak planes affects fracture propagation. • Custom designed pumping procedures can enlarge the heat transfer area. [ABSTRACT FROM AUTHOR]

The abundant geothermal energy in hot dry rock (HDR) formations is an attractive renewable energy resource with great potential. China will develop its first HDR geothermal formation in the Gonghe Basin. HDR is a hard and low-permeability granite containing very few fluids. Development requires fluids to cyclically flow between injection and production wells to extract geothermal energy in the artificial heat transfer zone. Hydraulic fracturing is the main technology for creating flow paths. But few studies have investigated fractures in HDR geothermal formations. This paper investigated fractures as flow paths in HDR geothermal formations during hydraulic fracturing. Hydraulic fractures were simulated using a custom true-triaxial hydraulic fracturing test system in a realistic formation environment, in which a scaled wellbore was used that was built in outcrop granite rock from the Gonghe Basin. Fracture creation in granite was investigated via experiments, as well as influence factors, and what experience could be achieved. This study can be used to design and evaluate hydraulic fracturing projects in potential HDR geothermal formations. • Hydraulic fracturing was simulated in high temperature via experiment. • Fracture creations were studied in outcrop granite of HDR geothermal formation. • In-situ stress and weak planes affects fracture propagation. • Custom designed pumping procedures can enlarge the heat transfer area. [ABSTRACT FROM AUTHOR]

China's economy has flourished since reform and opening up. At the same time, China's ability to attract foreign investment in the world continued to increase. However, with the rapid development of the economy, China's energy crisis and environmental pollution have been continuously deepened, exposing increasingly serious problems in the energy consumption structure. As a critical mean to address the environmental problems and achieve sustainable development, the production and utilization of renewable energy resources is particularly critical. This paper aims to investigate the relationship amongst renewable energy consumption, foreign direct investment and gross domestic product in 31 Chinese provinces from 2000 to 2015. Specifically, the unit root test, cointegration test, vector error-correction model, impulse response function analysis, and Granger causality test are employed for the estimations. The empirical results indicate that there is a long-term and stable equilibrium relationship between gross domestic product per capita, foreign direct investment per capita, and renewable energy consumption per capita. Additionally, in the short term, foreign direct investment cannot significantly cause renewable energy consumption change; but in the long run, a modest slowdown in gross domestic product growth and targeted foreign direct investment will generate a significant boost on renewable energy in China. • Relationship amongst renewable energy consumption, GDP and FDI in China is examined. • Vector error correction model and fully modified ordinary least squares are employed. • Long-run equilibrium exists between renewable energy consumption, GDP and FDI. • There is unilateral causality from GDP and FDI to renewable energy consumption in the long run. • FDI cannot significantly cause renewable energy consumption change in the short term. [ABSTRACT FROM AUTHOR]

Different from the existing studies, this study find the two paths that green finance development (GFD) affects renewable energy development are the clean biased technical progress path and financial constraint path, and at its different stages, there are significant differences in driving effects of GFD and government policies. Through empirically analyzing impact of GFD on renewable energy development with mediation effect model and China's provincial panel data in 2007–2019, this study obtains following conclusions: On the one hand, GFD can promote energy technology innovation to bias to clean energy technology. On the other hand, it can ease the enterprises' finance constraint, thus promotes renewable energy development. In initial stage of renewable energy development, government's supporting policy is the key driving factor, and role of GFD is weak. In growth stage of renewable energy development (accounting for more than 20%), GFD significantly promotes renewable energy development, and driving role of government supporting policy has gradually weakened. In view of above results, the policy recommendations of this paper are, first, government departments and financial institutions should form joint force to promote the growth of green finance scale. Second, balance administrative means and market tools according to the regional renewable energy development stage. [ABSTRACT FROM AUTHOR]

To achieve the carbon-neutral goal set for 2060, China has promoted renewable energy development for more than two decades. Meanwhile, China's electricity market is undergoing a new round of reform by introducing more market-oriented mechanisms and changing the market structure. This paper investigates the impact of three electric utility market structures experimented with in China on promoting renewable energy through a simulation model. The three market structures are vertical monopoly, weak monopoly (separation of power generators and grids), and monopolistic competition (Cournot-Nash competition). The model is calibrated with the actual data of the regional utility network in Beijing, Tianjin, and Tangshan areas. The simulation results show that the electricity market structure plays a vital role in renewable electricity, and the competition among utilities tends to benefit renewable energy development (wind power here). The study's conclusions are helpful to our understanding of further reforms in the electric utility industry and the long-term clean energy target in China. [ABSTRACT FROM AUTHOR]

Abstract China's power sector has become the largest contributor to China's carbon emissions because of its coal-dominated power structure. Replacing fossil fuels with renewable energy is an effective way to reduce carbon emissions and, therefore, a series of targets for renewable electricity generation have been put forward in national plans. However, how these targets will be reached is unclear. This paper uses a Long-range Energy Alternative Planning system (LEAP) model to explore the optimum development path of China's power sector from 2015 to 2050, taking into consideration the impacts of the renewable energy targets. Three scenarios are designed to examine the costs and benefits of developing renewable energy and improving the technologies for renewable power generation, comprising a base scenario, a renewable energy policy scenario and a technological progress scenario. The results show that the power generation cost would increase by at least 2.31 trillion RMB and that CO 2 emissions would be reduced by 35.8 billion tonnes during 2015–2050 if power generation follows current planning. Furthermore, every 1% increase in the capacity factors of renewable electricity would on average result in the cumulative CO 2 emissions decreased by 979 million tonnes and average CO 2 abatement cost decreased by 5.56 RMB/tCO 2 during 2015–2050. Based on this study, several policy implications are proposed for the development of power sector in China. Firstly, government may reconsider the current planning for gas-fired power and nuclear power to reach low-carbon electricity generation. Secondly, adjusting the carbon price can offset the additional cost of renewable electricity generation. Thirdly, promoting advanced technologies to match renewable electricity generation can obtain greater economic and environmental benefits. Finally, from the perspective of development potential, reducing the costs of solar power would be the emphasis at this stage. Highlights • Effects of renewable energy development plan in power sector are evaluated for China. • The optimal development path with minimum cost for the power sector are given. • National plans for renewable electricity can reduce 35.8 billion tonnes of CO 2 until 2050. • Average CO 2 abatement cost for promoting renewable power is 64.53 RMB/tCO 2 during 2015–2050. • Every 1% increase of the capacity factors of renewable power would decrease the average CO 2 abatement cost by 5.56 RMB. [ABSTRACT FROM AUTHOR]

Both developed and developing countries have committed to reduce their emissions through the increased use of renewable energy. This paper aims to compare renewable energy deployment in developed and developing countries represented by Australia and China. The paper firstly argues the validity of comparison of renewable energy deployment in Australia and China. Then, the governance structures in both countries are compared; the paper also compares management mechanisms in terms of funding and incentive support, renewable energy grid-connection and coordination between different levels of governments in both countries. Moreover, the current status of renewable energy development in two countries is summarized. From the study, it can be concluded both countries have set a Renewable Energy Target and promulgated legislation and regulations to enlarge the scale of renewable energy; China shows a stronger commitment to renewable energy than Australia. However, Renewable Energy Certificate mechanism is implemented more effectively in Australia than in China. The paper suggests: augmenting and rebuilding the electricity network and strengthening coordination between different levels of governments for both countries; enhancing manufacturing facilities and incentives for the solar and wind industry for Australia, while developing more-detailed implementation legislation and renewable power quota system for China. [ABSTRACT FROM AUTHOR]

The recent growth of the Chinese district heating sector has been very high. No other country in the world can show the same growth rate during the last decades. The heated building area increased six times between 1995 and 2008. China has also enjoyed strong growth of scientific articles and papers about district heating in recent years. One third of all international scientific journal articles and conference papers about district heating came from Chinese scientists during 2010–2012, while Swedish scientists accounted for one quarter according to the Scopus scientific search engine. It is important to identify the Chinese district heating research to judge the potential for future collaborative research on district heating systems between Sweden/Europe and China. The 205 international publications on district heating by Chinese scientists published until 2013 have been mapped and summarised with respect to demand, supply, technology, market and environment. More diversified heat supply with renewable source was grasping the Chinese interest, since many new systems have been established, having more degrees of freedom when choosing various heat supply and technology options. The Chinese district heating systems were compared with sustainable district heating solutions in Sweden. Both countries would benefit from future research cooperation. [ABSTRACT FROM AUTHOR]

n recent years, the annual curtailment ratio of wind power in China has been around 15%. Although the priority dispatch policy for wind power has been put in place in the country, it is not well implemented. One of the reasons for this is that wind power is viewed by some power system operators as “garbage power” due to its inherent intermittency nature. The improvement of social awareness of the value of wind power deployment is crucial for the effective implementation of the priority dispatch policy. In this paper, we analyze the impact of the priority dispatch of wind power on energy conservation and environmental improvement, and then compare the generation cost between wind power and coal-fired power while considering environmental externalities. We conclude that the energy intensity in the system decreases as the proportion of wind power generation increases, and the energy intensity is minimized when the proportion reaches 15%–20% provided a small amount of wind power curtailment is allowed. Meanwhile, we confirm that the wind power priority dispatch has significant positive impacts on environmental improvement. Further, we find that wind power generation cost is very close to coal-fired power cost when environmental cost is taken into account. [ABSTRACT FROM AUTHOR]

Abstract: This paper reviews features of Green Building Label (GBL), the green building evaluation system in China, in terms of management and technology. It is followed by classified statistical analysis on 353 GBL projects issued in the four years from 2008 to 2011, in the context of evaluation agency, evaluation stage, building type, star level, regional distribution, and developer. Then it focuses on technical application of GBL projects including basic technical requirements and 32 applicable technologies, especially renewable energy utilization. Some suggestions are proposed for GBL development and revision of the Chinese national standard (Evaluation Standard for Green Building) in this paper. [Copyright &y& Elsevier]

Abstract: In order to improve living environment for the villages in Tibetan areas of Yunnan, this paper takes Shangri-La’s wooden architecture as research objects, analyses the site selection, plane layout, facade design, building materials and fabric detail of traditional rural housing by investigation. The paper also extracts the local inherent eco-technologies, and identifies the shortcomings of rural housing. Aimed at the flawed characteristics of Tibetan building such as the scattered building location, high Shape coefficient, less–story, poor insulation, massive energy consumption and redundant land occupation, this paper researches adaptable design strategies of green rural housing which is suitable to local condition, so as to boost the sustainable development of rural construction of Tibetan areas in Yunnan. [Copyright &y& Elsevier]

As a crucial issue in the wind power industry, it is a tough and challenging task to predict the wind power accurately because of its nonlinearity, non-stationary and chaos. In this paper, we propose a novel hybrid model, which combines an integrated processing strategy and an optimized local linear fuzzy neural network, to forecast the wind power. First, discrete wavelet transform and singular spectrum analysis are used to filter out the noises and extract the trends from original wind power series, respectively. Then, the novel no-negative-constraint-combination theory together with the CS algorithm are adopted to integrate these two subseries obtained from the first step to retain strengths of each method. Based on the phase space reconstruction model, we could determine the most proper structure of the input sets and the output sets. Next, the local linear fuzzy neural network, with the initial rule consequent parameters optimized by the seeker optimization algorithm, is utilized to make wind power forecasts for a selected number of forward time steps. The numerical results from two experiments demonstrate that the proposed hybrid model is an effective approach to predict wind power, and the accuracy of prediction is highly improved compared with conventional forecasting models. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses fuel ethanol from corn as an example to establish a theoretical model and framework to explore possible impacts of developing bioenergy on food security in China under short run and long run dynamic equilibriums with import supplements. From the three aspects including “fighting for food with people”, “fighting for land with food”, and international trade safety, the conditions that create food safety problems are discussed. In a closed economy, when the decrease in direct or indirect demand for corn caused by corn price rise is larger than the demand increase due to income increase, or when corn demand increase caused by fuel ethanol price rise is larger than the corn demand decrease caused by the decrease in government price subsidy for fuel ethanol, food security problem will appear. Food security problem can be solved by implementing trade policy when a stable import source is available. Otherwise the subsidies, substitutes, technology, etc. should be used to increase the rate of self-supply. Moreover, considering the status quo of corn market, the paper puts forward a set of policies of income and price subsidy, substitutes, and trade and technology to solve the problems. [Copyright &y& Elsevier]

Abstract: CO2 emissions of the electricity supply sector in China account for about half of the total volume in the country. Thus, reducing CO2 emissions in China’s electricity supply sector will contribute significantly to the efforts of greenhouse gas (GHG) control in the country and the rest of the world. This paper introduces the development status of renewable energy and other main CO2 mitigation options in power generation in China and makes a preliminary prediction of the development of renewable energy in the country for future decades. Besides, based on the situation in China, the paper undertakes a comprehensive analysis of CO2 mitigation costs, mitigation potential, and fossil energy conversation capacity of renewable energy and other mitigation options, through which the influence of renewable energy on the mitigation strategy of China is analyzed. [ABSTRACT FROM AUTHOR]