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Additively manufactured nano-MEH systems are widely used to harvest energy from renewable and sustainable energy sources such as wind, ocean, sunlight, raindrops, and ambient vibrations. A comprehensive study focusing on in-depth technology evolution, applications, problems, and future trends of specifically 3D printed nano-MEH systems with an energy point of view is rarely conducted. Therefore, this paper looks into the state-of-the-art technologies, energy harvesting sources/methods, performance, implementations, emerging applications, potential challenges, and future perspectives of additively manufactured nano-mechanical energy harvesting (3DP-NMEH) systems. The prevailing challenges concerning renewable energy harvesting capacities, optimal energy scavenging, power management, material functionalization, sustainable prototyping strategies, new materials, commercialization, and hybridization are discussed. A novel solution is proposed for renewable energy generation and medicinal purposes based on the sustainable utilization of recyclable municipal and medical waste generated during the COVID-19 pandemic. Finally, recommendations for future research are presented concerning the cutting-edge issues hurdling the optimal exploitation of renewable energy resources through NMEHs. China and the USA are the most significant leading forces in enhancing 3DP-NMEH technology, with more than 75% contributions collectively. The reported output energy capacities of additively manufactured nano-MEH systems were 0.5–32 mW, 0.0002–45.6 mW, and 0.3–4.67 mW for electromagnetic, piezoelectric, and triboelectric nanogenerators, respectively. The optimal strategies and techniques to enhance these energy capacities are compiled in this paper. Highlights: The current technology evolution and advancements in 3DP-NMEHs were evaluated. Categorization and comparison of 3DP-NMEHs were performed in terms of inputs and energy conversion. The emerging applications of 3DP-NMEHs were discussed briefly. The potential challenges confronted by 3DP-NMEHs and respective recommendations were summarized. Sustainable use of recyclable waste generated during the COVID-19 pandemic was proposed. [ABSTRACT FROM AUTHOR]

The uncertain nature of renewable energy resources (RERs) and fast demand response lead to recurring voltage violations in the power systems, which causes frequent transformer tap shifting and capacitor switching. Therefore, this paper resorts to the static var compensators (SVCs) to manage the bus voltages based on the multi-agent deep reinforcement learning (MA-DRL) algorithm. The proposed scheme includes several system agents and SVC agents to collaboratively adjust the injected reactive power to restrict the bus voltages within the normal range. All the agents are trained centrally and executed separately, which requires minimum communication cost. The IEEE 14-bus system, IEEE 300-bus system, and China 157-node urban power grid are used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The rotational inertia and primary frequency response capabilities of power systems are declining as synchronous generators (SGs) are replaced by inverter-based variable renewable energy (VRE) resources. Therefore, when a high VRE proportion is present, it becomes essential to include frequency security constraints in power system planning. Under this circumstance, the decline in SGs would deteriorate the system frequency response performance; thus, inverter-based resources are supposed to provide frequency response support. This paper presents a frequency-constrained stochastic planning method for high VRE share systems. Frequency response support from wind farms is considered in the planning process for the first time, and the unique characteristics of wind power support are addressed. Specifically, the uncertainty of and variations in wind power support capabilities are modeled from the field-measured data, and the optimal combination of various support schemes can be determined by introducing binary variables with novel linear constraints into the planning process. Moreover, the nonlinear frequency constraints are transformed and embedded in the planning model by the proposed computationally efficient adaptive piecewise linearization method. The planning is formulated as a stochastic optimization model to consider the VRE power uncertainty. Finally, case studies on the IEEE 30-bus system validate the proposed method, with results indicating time savings of 22%. Further, compared with the case that only SGs provide frequency support, the results based on the East China system demonstrate that considering wind power support can improve the VRE share from 49.5% to 79.7%. [ABSTRACT FROM AUTHOR]

With the sharply increased development of variable renewable energy resources (VRERs) in recent years, the hydro-wind-photovoltaic (PV) hybrid system (HWPHS) has the prospective to enhance the grid integration of VRERs. Nevertheless, the intense variation associated with wind and PV generation causes uncertainties in the long-term operation of the HWPHS. To overcome this drawback, this paper develops a novel method to derive adaptive operating rules for a cascade HWPHS. First, a scenario-generating method coupling Kernel density estimation with the copula function is proposed to characterize the wind and PV forecast errors. Second, based on the power generation scenarios, an optimal scheduling model for the cascade HWPHS considering transmission section constraints is proposed to simulate the hydro-wind-PV complementary operation; finally, the long-term operating rules for the cascade HWPHS are extracted by grey relational analysis and BP neural network. As a case study, the HWPHS of the Wu River basin in China is chosen. Results demonstrate that the proposed model can effectively utilize the flexibility of cascade hydropower stations, improve transmission section utilization efficiency, and promote clean energy absorption. [ABSTRACT FROM AUTHOR]

Shallow geothermal energy (SGE) is a renewable energy source that has the advantage of being low-cost, clean, and locally sourced compared to fossil fuels, and is thus significant for China to achieve its future goals of carbon peaking and carbon neutrality. However, determining how to improve the operational efficiency of SGE systems is a key factor in the sustainable development and utilization of geothermal energy. This study examined the long-term operational efficiency of SGE systems and applied numerical simulation methods of hydro-thermal coupling to a SGE utilization project in Shandong Province, China. The effect of the distribution of pumping and injection wells on the operation efficiency of the SGE system was analyzed, and the parameter of operation efficiency, defined by the ratio of the practical minable shallow geothermal energy to the theoretical shallow geothermal energy, was applied to quantify the operation efficiency of the SGE system. The simulated results show that the phenomenon of heat transfixion is significant in the current operation scheme, where one of three pumping wells is located downstream of the study area, which indicates that the local groundwater flow field mainly controls the operation efficiency of the SGE system. In the optimized operation scheme, the distribution of pumping and injection wells can be adjusted according to the feature of groundwater flow and temperature fields. The degree of heat transfixion significantly declines and the operation efficiency increases by 71.5%. In addition, further improvements in the operational efficiency of the SGE system can be considered through the running time. The findings of this paper will be useful for the construction and management of SGE systems. [ABSTRACT FROM AUTHOR]

In recent years, with the increasing impact of extreme weather events on energy security, energy vulnerability has increased significantly, and more and more international institutions and departments have begun to incorporate resilience governance into energy security. This paper focuses on China's inter-provincial energy security assessment. Compared with existing relevant research, the significant features of our work are (i) introducing the concept of energy resilience and presenting its evolution mechanism and evaluation criteria, (ii) developing a gray relational projection model by using the level difference maximization and optimization theory, (iii) measuring the energy resilience of 30 Chinese provinces over space and time. Our results show that the spatial–temporal patterns of energy resilience in China changed significantly from 2005 to 2018. High energy resilience moved from provinces with abundant nonrenewable energy before 2010 to provinces with high energy diversity. Energy endowment is a primary condition to ensure a region's energy resilience. Renewable energy development, energy investment, economic development, and policy coordination play vital roles in ensuring regional energy resilience. Energy investment and economic development can effectively improve the energy resilience of resource-poor areas. This study's results will serve as a reference for China and contribute to expanding knowledge in this field. [ABSTRACT FROM AUTHOR]

Industrialized aquaculture is an essential trend for aquaculture development in China, owing to its considerable advantages in lower water consumption, higher productivity, and sustainability. However, information on its current status has been scarce up to now. This paper reviewed the current status and has identified existing problems as well as proposing possible solutions for the development of industrialized aquaculture in China. This field is still at an early stage of development and is mainly distributed in coastal regions. Major constraints on industrialized aquaculture include high capital and operational costs, the uncompetitive market price of aquatic products, uneven distribution of production and farming areas, a lack of suitably experienced managers and operators for recirculating aquaculture systems, and the coronavirus disease 2019 (COVID-19) pandemic. Possible solutions to these problems include technological innovations in systems optimization, the use of renewable energy sources and biofloc technology, the pollution-free certification of industrial aquaculture products, increased numbers of professionals in water quality control and waste management, and the financial assistance to companies and farmers along the aquaculture industrial chain. [ABSTRACT FROM AUTHOR]

In the context of low carbon economy development, controlling fossil energy consumption and promoting development in renewable energy are important paths for energy transition in various countries. Taking China as an example, this paper investigates the green finance policy coupling effect of fossil energy use rights trading (FET), renewable energy certificates trading (RECT), and renewable energy subsidies (RES) on the low carbon economy using a dynamic recursive computable general equilibrium (CGE) model. The main findings of this paper are as follows. (1) When using a game equity fixed-cost allocation model (Game-EFCAM) to allocate fossil energy use rights quotas among sectors, allocations differ in only a few sectors compared to the base period, and most sectors have relatively stable allocations compared to the base period. (2) The implementation of FET and RECT has a negative impact on per capita GDP. In the short term, RES can mitigate the negative impact of FET and RECT on per capita GDP, but eventually, the government needs to guide the enterprise innovation to improve the industrial structure to realize the double benefits of green finance policy. (3) The implementation of FET and RECT limits fossil energy consumption and also reduces the production possibility frontier of the secondary industries with higher levels of fossil energy consumption. The implementation of FET and RECT increases the proportions of tertiary industry and renewable energy. (4) The implementation of FET and RECT reduces carbon emissions. In other words, the implementation of FET and RECT mitigates the negative environmental externality. RES can enhance the carbon reduction efforts of FET and RECT. This research not only provides policy analysis for the development of the low carbon economy in China, but also gives a reference for other developing countries' low carbon economy transition. [ABSTRACT FROM AUTHOR]

Efficient allocation of resources and transition towards cleaner sources of energy are among the key factors in minimizing the negative externalities arising from the growing dependency on fossil fuels. Moreover, environmentally benign trade policies are crucial due to the rapid expansion in global trade and comparative advantage. To explore the relationship between global trade and Consumption‐Based Carbon Emissions (CBCE) in China in the context of renewable energy consumption and energy efficiency from 1990 Q1 to 2020 Q4, this paper employs the dynamic Autoregressive Distributed Lags (Dynamic ARDL) model to evaluate the connection between international trade, renewable energy usage, energy efficiency, and CBCE, with the Kernel‐Based Regularized Least Squares analysis being used to determine the causal association. The findings reveal that GDP and imports are directly linked with CBCE in the long run, while exports, energy efficiency, and renewable energy consumption have a negative significant long‐run and short‐run influence on CBCE. In addition, exports help in the reduction of CBCE by sharing and adapting environmentally friendly technologies adopted in, for example, renewable energy and ecological advancements. Renewable energy promotes the quality of the environment, which is attributable to the performance of renewable energy and environmentally friendly technologies that directly stimulate the reduction of CBCE emissions. By cutting CBCE, energy efficiency tends to boost environmental quality. The research findings have noteworthy policy implications; trade enhances the quality of environment by introducing lower energy intensive production methods and technology that support sustainable development. As a result, this study advocated quite stringent policies in terms of aligning international trade orientation with environmental quality policy in China. Furthermore, energy efficiency policies are required to lower CBCE by focusing on high‐energy‐using industries and providing alternative clean energy sources. [ABSTRACT FROM AUTHOR]

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In China, where energy activities, predominantly driven by fossil fuel combustion, account for nearly 90% of the country's greenhouse gas (GHG) emissions and coal power alone contributes over 40%, the shift towards carbon neutrality is a critical national ambition. This study conducts a comprehensive comparison of the environmental impacts of solar photovoltaic power generation (SPPG) and coal power, employing both life cycle assessment and ecological footprint analysis. We meticulously analyze the complete lifecycle of SPPG, pinpointing key stages of GHG emissions, and offer nuanced, localized policy recommendations. Our findings indicate that a 1 kWp SPPG module emits 1,601.18 kg of GHGs over its lifespan, equating to 1.35 kg/kW-h per unit of electricity produced--substantially lower than the 4.81 kg/kW-h emitted by coal power, thus highlighting the latter's heightened environmental detriment. Additionally, this study assesses the ecological footprint of both energy sources in Ningxia. SPPG emerges with an ecological surplus, showcasing a per capita footprint of 0.0342 hm², compatible with Ningxia's ecological capacity. In stark contrast, coal power exhibits a sustained ecological deficit over the past 5 years, with a growing per capita footprint of 0.6529 hm², underscoring its unsustainability. This research provides a detailed comparative analysis of the environmental impacts of SPPG and coal power in Ningxia, offering valuable insights for energy policymakers and industry stakeholders. It underscores the urgent need for industrial restructuring towards more sustainable and renewable energy sources, aligning with China's broader objectives of environmental preservation and achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

The building sector is one of the largest energy user and carbon emitters globally. To increase the utilization rate of renewable energy and reduce carbon dioxide emissions, the optimal technical scheme of active public institutions and coupled utilization of renewable energy is studied. In this study, the energy consumption of three types of public institutions in various regions of China was simulated by using DeST building energy consumption software, combined with energy conversion efficiency and data released by the National Bureau of Statistics, and the total energy demand and total energy supply of public institutions were predicted using the load density method. Based on the coupling mechanism of the MARKAL model, the optimal proportion of renewable energy in the energy supply of public buildings in different regions is determined. Through the study of the number of public institutions in various regions of China, energy consumption characteristics, construction area, and other related data, the reverse energy flow method is creatively proposed, and the active and renewable energy coupling algorithm from the energy demand side of public institutions to the energy supply side is established. The results show that the central region has the highest utilization rate of renewable energy in the public sector, reaching 36.18%. The use of renewable energy in public buildings in hot summer and warm winter zones decreased to 35.08%, and it was 12.82% in cold zones. By 2025, the proportion of renewable energy resources in China is expected to reach 29.2%. The energy coupling model and algorithm constructed in this paper can provide a basis for the coupling macro configuration of renewable energy in public institutions in China. [ABSTRACT FROM AUTHOR]

Financial incentives play a key role in promoting renewable energy investments that can help China achieve the 'dual carbon' goal. The national emissions trading scheme (ETS) and the renewable energy portfolio standard (RPS) are two existing market-based policy instruments that can generate stable expected returns for low-carbon projects. This paper studies the interactive distribution effects of these two market-based instruments. We use the micro-level thermal power plant data to investigate the abatement effects of the national ETS, in which the details show that the existing rate-based ETS will result in higher negative impacts on power units, whose installed capacities are smaller than 400 MW. The interactive distribution effects between the two markets will occur when the permit allocation standards of the national ETS become stricter than the existing ones. Provinces in Eastern China and Northern China will face high pressure on costs in both ETS and RPS markets. When the levels of the permit allocation standards are set as 70% of the existing ones and the carbon price is assumed to be 200 yuan/ton in 2030, the annual market size of the national ETS will be nearly 100 billion yuan, and the annual market size is predicted to be 250 billion yuan. In the existing rate-based national ETS, the China Certified Emission Reduction (CCER) mechanism will have an offsetting effect, which should be taken into serious consideration during the policy-making processes in the future. [ABSTRACT FROM AUTHOR]

The ongoing transition from fossil fuel-based electricity generation toward green energy relying on the intermittent renewable energy sources indispensably requires development of novel energy conversion and storage methods. Depending on a particular location and local resources, pumped storage, lithium- or sodium-ion batteries, compressed air energy storage, as well as the so called power-to-gas (P2G) technologies may be applied. Taking into account the abundant solar energy resources available in the northwestern China, such as Ningxia hui autonomous region, and local water resources coming from the Yellow River, a power-to-hydrogen (P2H2) distributed energy conversion system is proposed in this paper, which is based on a high-efficiency reversible Solid Oxide Cell (rSOC). The conducted studies comprise tests with simulated current based on the actual photovoltaic power station data, and with usage of the as-obtained Yellow River water for the electrolysis mode without any pretreatment. It is documented that the reversible operation is beneficial, and the tested cell can operate for a prolonged time. Of importance, Na, Ca, Mg, and Si elements remain in an evaporator, and do not contaminate the cell, while higher than the initial boron concentration can be found in the condensed exhaust gases. The respective operational parameters of the system correspond to an electrolysis current density loading up 433.3 mA cm−2 for 4 h, as well as fuel cell operation mode with a current density of 8.3 mA cm−2 for 12 h. It is found that the average voltage losses in the electrolysis cell and fuel cell mode are 0.27 %/cycle and 0.886 %/cycle, respectively, indicating that the lifetime of the cells can be more than 800 h. The reported studies demonstrate validity of applying rSOC-based P2H2 system, especially if abundant photovoltaic power and water resources are available. [Display omitted] • The Yellow River water was utilized by rSOC for the first time. • The designed test current was modeled with local photovoltaics. • The P2H2 nearby consumption system can reversibly operate for over 800 h. • The degradation rates in SOFC mode are lower than those in SOEC mode. • The Yellow River water has no significant effect on the degradation rate. [ABSTRACT FROM AUTHOR]

With the proposal of the carbon peaking and carbon neutrality goals, China's energy structure is gradually shifting from relying on fossil fuels to relying mainly on renewable and clean energy systems. However, clean energy represented by wind and photovoltaic power generation is difficult to operate and consume separately due to output fluctuations and uncertainties. Hydropower stations have good regulation capabilities and can operate in conjunction with wind farms and photovoltaic power stations to alleviate the instability of new energy generation. The southwestern region of China is rich in hydropower resources, and a large number of cascade hydropower stations with regulatory reservoirs have been built. The complementary operation of cascade hydropower with wind power and photovoltaic resources around the watershed, and the full utilization of the regulating capacity of cascade hydropower to bundle and deliver high-quality electricity, is an important means of achieving energy transformation. To quantify the carrying capacity of cascade hydropower stations on wind power and photovoltaic resources, this paper proposes a nested calculation model for medium to long-term optimal scheduling of hydropower to short-term optimal allocation of hydro-wind-photovoltaic power. The short-term scheduling calculation boundary is determined based on the mid-term and long-term optimization scheduling calculation results of hydropower, the scale of wind and photovoltaic power during short-term scheduling is adjusted, and scheduling with the goal of maximizing source load matching, maximizing power generation, and minimizing abandoned power are optimized. Decoupling is carried out by using a hierarchical nested strategy to calculate the scale of wind and photovoltaic resources that can be carried by cascade hydropower stations. Applying this model to the cascade hydropower station group in the Yalong River Basin, the scale of wind and photovoltaic resources carried by the "three reservoirs and seven cascade" cascade hydropower stations in the Yalong River Basin is calculated. The research results show that considering the 2025 planning level year and 5% curtailment rate constraint, the cascade hydropower in the Yalong River basin can carry 1.396 million kW of wind power resources and 10.74 million kW of photovoltaic power resources. The research results have a certain reference value for the optimization of water solar energy complementary power generation systems in the watershed. [ABSTRACT FROM AUTHOR]

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. How to ensure the accommodation of renewable energy will also be the core issue in the future development process of renewable-dominated electric power systems. In this context, shared energy storage (SES), a novel business model combined with energy storage technologies and the sharing economy, has the potential to play an important role in renewable energy accommodation scenarios. This paper systematically organizes the application prospect, development status and key technologies of SES in the renewable energy accommodation scenario in the context of China, providing helpful references for the promotion of the business model. Firstly, a typical SES framework for renewable energy accommodation is described, and three basic forms of SES in this scenario are presented. Moreover, the application prospect of SES in the renewable energy accommodation scenario is quantitatively analyzed based on the renewable energy generation planning under the carbon peaking goal and the current guarantee mechanism of renewable energy accommodation. Furthermore, the rules for energy storage systems that provide the peak-regulation ancillary service in typical regions and provincial administrative regions in China are summarized, and the development status of SES in the renewable energy accommodation scenario is analyzed, combined with the actual market data. Finally, the key technologies to promote the further development of SES for renewable energy accommodation are presented. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

The renewable energy industry, in particular, has experienced an immense amount of pressure that has stemmed from the novel COVID-19 pandemic. This study, however, investigates the renewable energy production initiatives that have taken come into place as a reaction to the COVID-19 pandemic, using a time series data of China in particular. The study uses the robust ARDL bounds testing approach in order to get sound parameter estimates. The findings of the study reveal that COVID-19 pandemic has significantly reduced the renewable energy production in China, both in the short and long run. In addition to this, the GDP and trade tend to positively impact the incidence of renewable energy production in the wake of the Covid-19 pandemic. In the same context, it has been observed that the energy price has a significant and negative impact on renewable energy production, particularly in the long-run, during the pandemic period. Keeping these observations in consideration, it can be asserted that the government should ideally adopt a short-term policy, while mid-term and long-term action plans should be formulated, so as to achieve the renewable energy targets in the future. In this regard, the research implications and future directions have thoroughly been discussed in the paper. [ABSTRACT FROM AUTHOR]

In China, as an important source of renewable energy, the standard biogas production module (SBPM) plays a key role and accounts for the majority of biogas production. Given its greater environmental pollution, it is particularly important to assess its quantitative sustainability status for optimizing system design and policy-making. This paper conducted the sustainability assessments of the open-loop standard biogas production module (OL-SBPM) and closed-loop standard biogas production module (CL-SBPM). Compared with the OL-SBPM system, the CL-SBPM system integrates a power generation subsystem. To evaluate two types of systems quantitatively, energy, emergy and entropy methods have been utilized in this study. The results illustrated that only partial indicators are more sustainable in the CL-SBP system rather than all indicators by comparing with the OL-SBPM system, which is contrary to the prevailing view. Taking the information entropy as an example, the equivalent information entropy flow values of the OL-SBPM and CL-SBPM systems are 2.04 × 1025 bits and 1.47 × 1025 bits, respectively, which also demonstrate that the OL-SBPM system has more useful information resulting in higher degree of sustainability. Therefore, these two systems need to be selected according to the existing conditions, rather than the subjective ideation. [ABSTRACT FROM AUTHOR]

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]

Reducing greenhouse gas emissions is urgent for the global community with rising climates. Considering the importance of renewable energy in mitigating climate warming, forecasting renewable energy generation is vital for the Chinese government's future low-carbon and green development plan. This paper proposes a novel multivariable grey model based on historical data on China's renewable energy generation and three industries. A novel information accumulation mechanism with two adaptive factors is designed to improve the traditional multivariable grey modeling defect. Based on the proposed mechanism, this paper optimizes the initial and background values and nonlinear model structure with the whale optimization algorithm. The forecasting results show that the fitting MAPE is 1.13%, comprehensive MAPE is 2.60%, MSE is 50.86, and RMSE is 7.13, which significantly improve the forecasting accuracy of traditional GM(1,N) and are better than other compared models. The forecasting results show that China's renewable energy generation will gradually increase to 5834.02 TWh. The Chinese government should keep the previous Five-Year Plans rising trend of the three industries in the future Five-Year Plans to support renewable energy industries. In China's future energy system, it is necessary to promote incentive policies and capital investment for actively accelerated development to make renewable energy the leading force. [ABSTRACT FROM AUTHOR]

With the further increase of domestic oil demand, the diversification strategy of energy supply represented by alternative energy sources, such as alcohol fuel which has become a direction of China's energy policy. Alcohol fuel can reduce conventional engine emissions by replacing conventional gasoline and diesel, but their unconventional emissions -- formaldehyde -- tend to have higher concentrations than conventional engines. Based on this, this paper analyzed the physical and chemical properties of mixture of methanol and gasoline and its feasibility as an energy fuel, and conducted experiments on formaldehyde emission of gasoline and methanol gasoline respectively, and then obtained a large number of experimental data that studied and analyzed the experimental results and methods, and drew relevant research conclusions. The results show that the high ratio of alcohol fuel can replace the use of chemical fuel and has good energy saving and environmental protection characteristics. When the same fuel is tested, the formaldehyde emission increases first and then decreases with the increase of power. In this paper, a large amount of formaldehyde emission data from alcohol fuel engines are obtained through bench experiments, which provides a scientific basis for the future development of alcohol fuel vehicle combustion system and the formulation of environmental emission standards. [ABSTRACT FROM AUTHOR]

Due to the growing demand on renewable energy, photovoltaic (PV) generation systems have increased considerably in recent years. However, the power output of PV systems is affected by different weather conditions. Accurate forecasting of PV power output is important for system reliability and promoting large-scale PV deployment. This paper proposes algorithms to forecast power output of PV systems based upon weather classification and support vector machines (SVM). In the process, the weather conditions are divided into four types which are clear sky, cloudy day, foggy day, and rainy day. In this paper, a one-day-ahead PV power output forecasting model for a single station is derived based on the weather forecasting data, actual historical power output data, and the principle of SVM. After applying it into a PV station in China (the capability is 20 kW), results show the proposed forecasting model for grid-connected PV systems is effective and promising. [ABSTRACT FROM PUBLISHER]

China and the United States are both major countries in the world in the production of and trade in wind energy products, and they are also important trading partners. Therefore, it is of great practical significance to analyze and evaluate the Sino-US bilateral wind power complementarity for re-examining their respective comparative advantages and re-understanding the benefits that trade liberalization brings to both countries, in an attempt to strengthen the trade relations between China and the United States and enhance trade complementarities in wind energy products under the global circumstances of fierce competition. In this paper, based on the trade data from the UN Comtrade database in 2007-2016, a quantitative analysis was conducted on the complementarity of Sino-US wind energy products, by adopting the quantitative research methods of trade combination degree index (TCD), export similarity index (SI) and trade complementarity index (TCI). The results shows that: i) the total trade volume of wind energy products between China and the United States has increased rapidly, and the trade surplus between China and the United States has been expanding year by year; ii) the overall trade balance of wind energy products trade between the two countries is generally stable, and the dependence of China's wind energy products on the United States is much higher than that of the U.S wind energy products on China; iii) the Sino-US wind energy products between China and the United States are highly competitive in the international market; iv) Sino-US wind energy products have different degrees of complementarity in bilateral trade. Finally, this paper proposed policy implications based on the findings of this study. [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]

Copyright of Advances in New & Renewable Energy is the property of Editorial Office of Advances in New & Renewable Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since the emergence of the COVID-19 pandemic, people all around the globe have seen its effects, including city closures, travel restrictions, and stringent security measures. However, the effects of the COVID-19 pandemic extend beyond people's everyday lives. It impacts the air, water, soil, and carbon emissions as well. This article examines the effect of energy and the COVID-19 pandemic on China's carbon dioxide emissions in light of the aforementioned context, using the daily data from 20 January 2020 and ending on 20 April 2022. Using the nonlinear autoregressive distributed lag model for empirical analysis, the findings indicate that COVID-19 pandemic confirmed cases and renewable energy advance environmental sustainability due to their negative effects on carbon dioxide emissions, whereas fossil fuel energy hinders environmental sustainability due to its positive effect on carbon dioxide emissions. Moreover, these results are also supported by the results of the frequency domain causality test and the Markow switching regression. In light of these results, there are several policy implications, such as vaccination, renewable energy utilization, and non-renewable energy alternative policies, which have been proposed in this paper. [ABSTRACT FROM AUTHOR]

LVDC buildings use a low-voltage direct current (LVDC) distribution system for energy transmission and integrate photovoltaic (PV), battery energy storage (BES) and the utility grid as building energy resources. This technology can reduce energy loss in conversion to a certain extent and increase renewable energy compared with traditional AC distribution systems. Under the national goal of carbon peaking and carbon neutrality, LVDC buildings have been proven to be a new approach to energy conservation and emission reductions, and have been applied in engineering in China. However, the construction methods and integrated technologies of those projects are not clear, and technical barriers and policy constraints for the engineering application of LVDC buildings are not systematically discussed yet. This paper presents the latest study of LVDC building engineering applications the advantages and drawbacks of LVDC development in China. First, relevant policies and standards which support the development of LVDC building industries are summarized. More than 60 practical LVDC projects are investigated, and the application characteristics and the technology status of building types, and their capacity and design methods, etc., are analyzed. The attitudes of stakeholders toward LVDC buildings are surveyed to determine the policy direction according to the demands of this technology, with reference to building practitioners who intend to engage in LVDC projects. [ABSTRACT FROM AUTHOR]

Accurate solar and wind generation forecasting along with high renewable energy penetration in power grids throughout the world are crucial to the days-ahead power scheduling of energy systems. It is difficult to precisely forecast on-site power generation due to the intermittency and fluctuation characteristics of solar and wind energy. Solar and wind generation data from on-site sources are beneficial for the development of data-driven forecasting models. In this paper, an open dataset consisting of data collected from on-site renewable energy stations, including six wind farms and eight solar stations in China, is provided. Over two years (2019–2020), power generation and weather-related data were collected at 15-minute intervals. The dataset was used in the Renewable Energy Generation Forecasting Competition hosted by the Chinese State Grid in 2021. The process of data collection, data processing, and potential applications are described. The use of this dataset is promising for the development of data-driven forecasting models for renewable energy generation and the optimization of electricity demand response (DR) programs for the power grid. Measurement(s) renewable energy generation Technology Type(s) supervisory control and data acquisition system Sample Characteristic - Location China [ABSTRACT FROM AUTHOR]

This paper examines the long-term and short-term relationships between renewable energy consumption, output and export, and CO2 emissions in China over the period 1990–2020 from the perspective of industry and agriculture using econometric methods. The results of the study found that there is a long-run relationship and there is a causality between these variables, indicating that renewable energy consumption, output, and export are related to CO2 emissions. Specifically, from a long-term perspective, the results of co-integration and causality reveal that there is a two-way causal relationship between renewable energy consumption, output, export, and CO2 emissions, supporting the feedback hypothesis; that is, output and export have an adverse impact on the environment, while renewable energy consumption has a favorable impact on the environment. In the short term, there is a direct or indirect one-way causal relationship between export, CO2 emissions, and renewable energy consumption, which supports the growth hypothesis. The impulse response analysis has further verified the causality test results and supported this hypothesis. However, there is a strong negative correlation between industrial and agricultural export and renewable energy consumption, which will cause the use of renewable energy to fail to meet the peak demand for industrial and agricultural export in the short term. Conversely, large amounts of fossil fuels will be consumed to meet output and export demand. Therefore, on the road to social, economic, and environmental sustainability, it is necessary to consider the impact of economic growth and energy consumption (renewable and non-renewable energy) of related industries on CO2 emissions, which also provides a strong basis for the development and reduction of China's renewable energy and the long-term implementation of the emission control policy. [ABSTRACT FROM AUTHOR]

The current legal and policy system of renewable energy in China has set up a framework of policy instruments, which provides an important foundation for dealing with climate change and promoting the healthy development of the renewable energy industry with the goal of "carbon neutrality" and "emission peak". However, the current policy instruments cannot meet the needs for rapid development of the renewable energy industry. This paper investigates, analyzes, and concludes the status of renewable energy development along with related policy instruments in different renewable energy sources by literature and points out the problems of current policy instruments, and puts forward corresponding countermeasures. Moreover, from the perspective of energy consumption market transformation, the authors carried out an analysis of China's challenges of policy instruments, pointing out that China's renewable energy policy instruments have the potential to take one step further in the areas of the regulatory system, legal system and legal security system. [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]

Under the Kyoto Protocol, the Clean Development Mechanism (CDM) expects to facilitate the North-South knowledge spillovers for climate-friendly technologies. This paper examines the effect of this voluntary international climate cooperation on firm innovation and knowledge spillovers through the lens of CDM projects in China. Using a matched Difference-in-Differences (DID) approach, we find that CDM projects contribute to firms' innovation quantity, quality, and direction in renewable energy and energy efficiency technologies. These effects are more pronounced in inducing wind, hydro, and solar energy. We explore the role of foreign sponsors in knowledge spillovers. Sponsoring firms play the technology supplier role by raising the innovation quantity and quality, while sponsoring governments perform the information intermediary role by facilitating citation flows. [ABSTRACT FROM AUTHOR]

China has built the world's largest power infrastructure. Those upgrading power grid facilities not only contribute to providing enough end-used energy for the world's factories, but also offering a basic guarantee for the clean strategy of Building a Beautiful China proposed by the Chinese government. The national grid system supported by extra-high voltage and ultra-high voltage grids as the backbone makes it possible for a non-dispatchable renewable energy source to be connected to the national grid and transmitted to terminal consumers in load centers. The aim of this paper is to test whether China's advanced power grids have played a positive role in promoting power generation of intermittent renewable energy source. A novel nonlinear estimation named panel smoothing transition regression is introduced to capture heterogeneous effects of grid-connecting renewable energy source across regions. The empirical results show that whereas power grid infrastructure generally enhances power generation of renewable energy source and consumption in energy bases and load centers, the effects change across different voltage levels of power grids. The extra-high voltage power grids show strong support for grid-connecting renewable energy source, while the effect of ultra-high voltage power grids is unexpectedly insignificant. The extra-high voltage power grids have not yet become the backbone of the national grid, which is the main reason for the inadequate grid-connected renewable energy source to the ultra-high voltage power grids, indicating the importance of upgrading the power grid infrastructure. [ABSTRACT FROM AUTHOR]

Poor access to modern energy services, or energy poverty, continues to be a significant barrier to socioeconomic progress and well-being. The complicated connections between public investment, incentives, supplier chains, and the financial success of energy poverty alleviation efforts are explored in this paper. This research examines the history of eradicating energy poverty worldwide, particularly in China. It examines how these aspects affect the efficiency and long-term viability of reducing energy poverty initiatives. This research synthesizes the evidence on government expenditure patterns and their impact on initiatives to reduce energy poverty via an extensive literature examination. The development of infrastructure, capacity building, and the deployment of energy technology are all made possible in large part by government spending. Financial and regulatory incentives have also been shown to encourage the energy industry's private sector engagement and innovation. These incentives help expand underprivileged groups' access to electricity by creating an atmosphere conducive to investment. This research also examines supply chains' crucial role in combating energy poverty. For the effective installation and upkeep of energy projects, efficient and resilient supply chains are crucial because they guarantee the availability of vital materials and resources. An integrated supply chain strategy may improve project results, save costs, and eliminate risks related to logistical difficulties. Government funding, incentives, and supply chains all have a connection that affects how well energy poverty alleviation programs function financially. Maintaining projects after their first execution requires sustained financial performance. It explores how supply network interruptions may affect financial performance, highlighting the need for robust supply chain management techniques. As a result, this study adds to a comprehensive knowledge of the complex processes underpinning the reduction of energy poverty. It offers insights into developing efficient policies and strategies by examining how government actions, incentives, supply chains, and financial performance interact. These observations are relevant for practitioners, investors, and academics trying to increase access to sustainable energy sources and reduce poverty in addition to policymakers. This report provides helpful recommendations for boosting the effectiveness and endurance of energy poverty reduction activities as nations work to reach global sustainable development objectives. [ABSTRACT FROM AUTHOR]

As a kind of renewable energy enterprise, wind power enterprise plays an important role in the energy transformation. However, its financing problems are also widespread. The purpose of this paper is to study the financing mode selection in order to improve sustainable development and future benefits of wind power enterprises. First, an evaluation index system is constructed through literature research and expert interviews, and the weight of each index is determined comprehensively by G1 and information entropy methods. On this basis, a financing mode selection model of wind power enterprises is constructed by using the prospect theory and hesitant fuzzy set. Next, this framework is used for case study. Financing patterns are ranked according to the comprehensive prospect value. The results show that financial leasing is the most suitable financing mode. Finally, the applicability and optimization of the model are proved by sensitivity analysis and comparative analysis. [ABSTRACT FROM AUTHOR]

Based on China's multilevel engagement strategy in Latin America and the Caribbean, this paper seeks to investigate Argentina's subnational strategies towards the Asian giant in terms of energy transition in two areas: the production of renewable energies and the production of lithium as a storage medium. The perspectives of asymmetric interdependence and structuralism are used to explain the pattern of links between the two countries; and studies of paradiplomacy are used to understand the international actions of Argentina's provinces. The analysis focuses on energy initiatives between 2014 and 2023, using a qualitative methodology with case studies. The initial argument maintains that the development of clean energy is a complementary interest between the Argentine provinces and China, as the Asian country builds its leadership in the field of energy transition, and the provinces diversify their local production matrices. [ABSTRACT FROM AUTHOR]

The cross-regional renewable hydrogen supply is significant for China to resolve the uneven distribution of renewable energy and decarbonize the transportation sector. Yet the economic comparison of various hydrogen supply routes remains obscure. This paper conducts a techno-economic analysis on six hydrogen supply routes for hydrogen refueling stations, including gas-hydrogen tube-trailer, gas-hydrogen pipeline, liquid-hydrogen truck, natural gas pipeline, MeOH truck, and NH 3 truck. Furthermore, the impacts of three critical factors are examined, including electrolyzer selection, transportation distance, and electricity price. The results indicate that, with a transport distance of 2000 km, the natural gas pipeline route offers the lowest cost, while the gas-hydrogen tube-trailer route is not economically feasible. The gas-hydrogen pipeline route shows outstanding cost competitiveness between 200 and 2000 km, while it is greatly influenced by the utilization rate. The liquid-hydrogen truck route demonstrates great potential with the electricity price decreasing. This study may provide guidance for the development of the cross-regional renewable hydrogen supply for hydrogen refueling stations in China. • The techno-economics of six renewable hydrogen supply routes for hydrogen refueling stations are studied in China's context. • The cost impacts of electrolyzer selection, transportation distance, and electricity price are explored. • Natural gas pipeline H 2 blending route offers the lowest cost at 2000 km distance. • Gas-hydrogen pipeline route's cost is strongly influenced by its utilization rate. • Liquid-hydrogen truck route has the best economics when the electricity price is below 0.1 CNY/kWh. [ABSTRACT FROM AUTHOR]

Existing studies have primarily focused on the resources and technologies related to renewable energy. However, it is essential to investigate the influence of economic, social, and governmental actions on the spatiotemporal changes in renewable energy. This paper utilizes spatial autocorrelation analysis, fixed effects modeling, and Geographical and Time Weighted Regression (GTWR) to analyze the phased characteristics and spatial differences of renewable energy electricity, based on time series and spatial layout data of renewable energy power by province and power source type in China. Additionally, it incorporates relevant economic, demographic, and investment data to identify the driving factors behind the spatiotemporal transformations of photovoltaic (PV) and wind power, as well as the main forces promoting sustainable growth. The study reveals the presence of spatial agglomeration in China's renewable energy power generation. Moreover, a positive correlation is observed between investments in environmental protection (EPI), state-owned electric power (SPI), scientific and technological advancements (STI), and renewable energy electricity. Technological progress has reduced the dependence of renewable energy on the natural environment, facilitating its promotion and widespread adoption. These findings provide empirical support and policy guidance for the sustainable and rapid growth of China's renewable energy industry. [ABSTRACT FROM AUTHOR]

In this research, we developed a three-stage monthly time-of-use (TOU) tariff optimization model to address the concerns of confusing time period division, illogical price setting, and incomplete seasonal element consideration in the previous TOU tariff design. The empirical investigation was conducted based on load, power generation, and electricity pricing data from a typical northwest region in China in 2022. The findings indicate the following: (1) In producing the typical net load curves, the employed K-means++ technique outperformed the standard models in terms of the clustering effect by 4.27–26.70%. (2) Following optimization, there was a decrease of 1900 MW in the maximum monthly abandonment of renewable energy, a decrease of 0.31–53.94% in the peak–valley difference, and a decrease of 2.03–17.27% in the monthly net load cost. (3) By taking extra critical peak and deep valley time periods into account, the average net load cost decreased by 10.36% compared with conventional peak–flat–valley time period division criteria. [ABSTRACT FROM AUTHOR]

Based on the background of comprehensive green transformation of economic and social development, this paper selects panel data of 30 provinces in China from 2000 to 2019, uses the panel fixed effects model and panel threshold effect model, and discusses the nonlinear correlation mechanism between green investment, industrial structure, renewable energy, and low-carbon development of the transportation industry. The results show that, firstly, industrial structure and renewable energy can significantly promote the low-carbon development of the transportation industry, while green investment has a restraining effect on it (the main reason is that currently its scale is small and its investment in the transportation industry is relatively low). Secondly, industrial structure and renewable energy have a negative moderating and threshold effect in the process of green investment restraining low-carbon development of the transportation industry. Thirdly, these threshold effects have obvious regional heterogeneity characteristics. Based on this, decision-makers should not only continue to expand the scale of green investment and optimize resource allocation but also fully utilize the threshold characteristics of industrial structure and renewable energy in different regions to develop different strategies and achieve the promotion of green investment in low-carbon development of the transportation industry as soon as possible. [ABSTRACT FROM AUTHOR]

This paper explains the energy mix of China's overseas electricity investments across Belt and Road Initiative (BRI) recipient countries. We focus on Indonesia and Pakistan. Our research is based on both newly gathered project-level data and in-depth interviews with stakeholders of Chinese-backed power plants in Indonesia and Pakistan. We examine (1) why Chinese actors are involved in renewable power generation in Pakistan and not in Indonesia, and (2) why Chinese-backed coal-fired projects in Pakistan are cleaner than in Indonesia. We argue that variations along the three dimensions – scope, governance regime, and issue linkage – lead to different energy mixes in Chinese-invested power plants across BRI countries. This framework specifies how supply and demand factors interact across multiple levels regarding the formulation and implementation of China's overseas electricity projects. Our findings shed new light on the environmental implications of BRI projects and the dynamics of renewable energy development in emerging markets. [ABSTRACT FROM AUTHOR]

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO2) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO2 emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO2 emissions; correspondingly, this study builds a model for CO2 emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO2 emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO2 emissions. Finally, this study forecasted a CO2 emission trend, with a slowdown predicted in China by 2022; however, CO2 emission's reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO2 emissions without harming economic development. [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]

While digital finance and renewable energy consumption (REC) are two timely issues, it remains unclear whether the former affects the latter, especially in developing economies. This paper examines the impact of digital finance on China's REC between 2011 and 2018 and explores the underlying mechanisms. Results show that digital finance, along with its coverage breadth and usage depth, significantly improved REC in China and that digital finance in the area of credit has had the most significant impact. Additionally, the results show that loan scale and income level are the main mediation variables, through which digital finance affects REC. The findings also suggest that economic growth and technological progress have increased REC in China, while carbon dioxide emissions have had no meaningful effect on this consumption. The results further indicate that policymakers must pay close attention to the role of digital finance when formulating policies on REC. To promote REC and environmental sustainability, developing economies like China should strengthen the breadth and depth of digital finance development, focus on the influence channels of digital finance, and promote economic growth and technological progress. [ABSTRACT FROM AUTHOR]

Power system planning is essential for ensuring development of a safe and stable power system. Articles on power system planning have been published in recent decades. In this paper, bibliometric analysis is applied to power system planning to identify its basic characteristics, and to summarize the research hotspots and trends. A total of 4562 publications were obtained from the Web of Science during 1971–2020. The 4562 publications cover 8136 keywords, 1526 journals, 107 countries/territories, and 2519 institutions. IEEE Transactions on Power Systems is the key journal in power system planning; USA, China, and England are the countries that dominate publication production. Research hotspots and trends were analyzed using author-keyword co-occurrence analysis and keyword burst detection. Four clusters were identified and topics from Cluster I (central nodes as power system stability and transient stability) and Cluster IV (central nodes as power system simulation and economics) are important for power system planning research. However, their relative popularities have declined over the past two decades. This indicates that Cluster II (central nodes as renewable energy, wind power, and energy storage) and Cluster III (central nodes as distributed generation and smart grids) will be the focus of future research. [ABSTRACT FROM AUTHOR]

Currently, the world is moving rapidly toward carbon neutrality, and renewable energy technology is very important in carbon neutrality. Among various renewable energy technologies, wind power is attracting much attention due to its sustainability, resource abundance, and high applicability. This study analyzed wind power patents from 2010 to 2021 to derive current global originality and convergence information. For IP5 countries, the growth stages of technology and the patent convergence networks were inferred by time series analysis and an association rule mining algorithm, respectively. The results showed that, during the analysis period, about 5000 patents were applied on annual average, and it was analyzed that China held the most patents at 48%, followed by the US, Europe, Korea, and Japan. According to the technology convergence network of patent codes from all the IP5 countries, patents related to 'wind turbines with rotation axes in the wind direction' occupied a very central position, and 'power conversion electric or electronic aspects' and 'integration of patents related to renewable energy sources in buildings with wind power' were found to show high connection strength. By country, it was analyzed that the US and China showed high patent competitiveness onshore and possessed many 'independent power conversion cluster' technologies. The research hypothesis was that technology development trends can be analyzed and the characteristics of each country can be understood through patent analysis in the wind power field. This hypothesis was analyzed through various patent analysis techniques, and this paper has novelty in that it presents the global megatrend in the wind power field through patent analysis and quantitatively presents the current status of technology development in five major countries. [ABSTRACT FROM AUTHOR]

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This paper examines the development of China's wind turbine industry, shedding light on the Chinese mode of disruptive industrial upgrading through policy pragmatism and fragmented, experimental governance. Based on a historical analysis of China's wind turbine industry, the paper highlights three distinct phases, which are all marked by their own inbuilt and potentially self-disruptive impasses and associated crises. In turn, these impasses have forced the Chinese government into radical and flexible interventions, which have spurred on Chinese companies to creatively find new ways to develop and upgrade. The paper illustrates the transformation of Sino-foreign relations by China's non-linear upgrading approach, particularly during the Chinese wind power industry's quality crisis, and its development model. It also discusses the implications this examination of China's approach has for the literatures on China, upgrading, and catch-up. Finally, the paper calls on future studies to enquire further into China's distinct mode of industrial upgrading and its embeddedness in China's institutional context. [ABSTRACT FROM AUTHOR]