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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]

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

Green total factor productivity is a vital measure of sustainable progress, holding immense implications for attaining both economic growth and environmental preservation in a mutually beneficial manner. Focusing on green total factor productivity, this paper examines its nexus with low-carbon energy technology using the Instrumental Variable Generalized Method of Moments (IV-GMM) model, based on a panel dataset in China during 2005–2018. This paper also examines the asymmetric impact of low-carbon energy technology on green total factor productivity. In addition, the moderating and mediating effects are checked. The main findings are that (1) low-carbon energy technology is a promoting factor for green total factor productivity. (2) Low-carbon energy technology exerts a more prominent marginal impact on green total factor productivity when green total factor productivity is at higher quantile levels. (3) Renewable energy generation not only drives green total factor productivity directly, but also further increases the promotion effect of low-carbon energy technology on green total factor productivity, showing a positive moderating role. (4) Energy structure transition and industrial structure transition are two internal impact mechanisms between low-carbon energy technology and green total factor productivity. These findings suggest that the government can promote green total factor productivity development by developing policies related to low-carbon energy technology and fully releasing the effects of technology on sustainable development. • This paper assesses the level of low-carbon energy technology (LCET) in China. • This paper examines the effect of LCET on green total factor productivity (GTFP). • LCET plays a significant role in enhancing GTFP. • Renewable energy generation positively moderates the nexus between LCET and GTFP. • Energy structure transition and industrial structure transition are two mechanisms. [ABSTRACT FROM AUTHOR]

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

The significance of renewable energy as a pivotal green industry in decarbonizing the global economy and addressing the climate change is profound. The rise of China's regional renewable energy serves as a testament to its transition from an industrial powerhouse to a leader of sustainable growth, offering valuable insights for a sustainable future worldwide. This study analyzes renewable energy efficiency, alongside the factors that influence it, in Qinghai Province over 2000–2021. It uses a combination of the Logarithmic Mean Divisia Index factor decomposition, Data Envelopment Analysis of Super-SBM models, and field research with a rounded approach. The study finds a robust increase in renewable energy capacity, particularly after 2016. Efficiency in renewable energy generally has risen, although periods of inefficiency were noted from 2014 to 2019. Despite fluctuations, the overall impact of factors such as renewable energy structure, electricity intensity, energy security, energy intensity, carbon productivity, and carbon emissions, all contribute positively to the development of renewable energy, notably in recent years. The paper concludes with a discussion of green industrial policies with wider implications for the renewable energy sector. • The rise of China's regional renewable energy offers valuable insights for sustainability. • Renewable energy capacity in Qinghai increased robustly over 2000-2021. • Renewable energy efficiency has risen but with inefficiency from 2014 to 2019. • Despite fluctuations, the overall impact of influencing factors promoted renewable energy, notably in recent years. • There is a need for stable green industrial policy, diverse energy mix, strengthening grid infrastructure, and promoting sustainable energy. [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]

The comprehensive promotion of electric vehicles is critical for green and low-carbon energy transformation and dual-carbon goals in China. Battery swapping station is a hub to meet the battery-swapping demands of EVs and consumes renewable energy power (REP). Moreover, the potential of battery swapping station cluster (BSSC) must be explored urgently. Therefore, the day-ahead dispatching model of BSSC is proposed for the efficient consumption of REP and battery-swapping demands of electric taxis (ETs) in this paper. Firstly, the battery-swapping demands of ETs in dynamic spatiotemporal distribution are aggregated by the KNN algorithm. Secondly, a dual-objective model of the day-ahead dispatching model with economy and efficient consumption of REP is constructed, and the NSGA-II algorithm obtains the optimal strategy. Finally, taking a city of China as an example, the charging-discharging strategy of BSSC is provided. The results show that the day-ahead dispatching model is of practical significance to get an optimal charging-discharging strategy of cluster loads for REP consumption and economic battery-swapping service. • Aggregate the battery-swapping demands of ETs by the KNN algorithm. • Construct a day-ahead scheduling model for balancing CDC of BSSC and REP consumption. • Apply the NSGA-II algorithm to solve the bi-objective model. • Select a city of China for the study to verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Abstract By building a green economy development index to measure the level of green economy development, taking 150 renewable energy listed companies of China for example, this paper constructs a threshold effect model to investigate the non-linear relationship between renewable energy investment and the green economy development index from the perspective of green credit. Results mainly show that: firstly, the impact of renewable energy investment on the green economy development index includes dual threshold effects from green-credit, the effect is divided into three stages: promoting, restraining and promoting successively. Secondly, for large-sized companies, the impact of renewable energy investment on the green economy development index includes one threshold from green-credit, with the effect coefficients at each stage being 0.1034 and −0.0113, successively. However, for medium, small, and micro sized enterprises, the impact of renewable energy investment on the green economy development index includes dual threshold effects from green credit, with the effect coefficients at each stage being 0.1310, −0.0033, and 0.0244, successively, and the inhibition effect not being significant. Thirdly, our results also find that improving expenditure on environmental pollution control and adjusting industry structure are conducive to increasing the green economy development index. Highlights • Non-linear relationship between renewable energy investment and green economy development is explored here. • Dual threshold effects from green-credit on renewable energy investment and green economy development exists. • Medium, small, and micro sized enterprises are the dominant forces of green economy. [ABSTRACT FROM AUTHOR]

With the goals of carbon peaking and carbon neutrality, China's renewable energy has entered a stage of rapid development. The government gives financial and power-rate subsidies to clean power while putting great support on its construction. However, there is currently a big gap in the government's subsidy on new energy power generation, which is challenging to meet the demand for renewable energy consumption and sustainable development. In this regard, participating in the market is inevitable for renewable energy development, which is significant for promoting renewable energy power consumption and alleviating the subsidy dilemma. Considering the market-based mechanism, this paper regards the electricity market, the tradable green certificate market, and the carbon emissions allowance trading market as an integrated energy platform system that couples carbon emissions with electricity, linking generators and retailers. We consider two scenarios, including green electricity–green certificate separation and unity, and introduce the intermittency of new energy generation to construct the optimal pricing decision for this platform supply chain. We explore the optimal price of tradable green certificate for renewable power and the equilibrium demand for green power and thermal power in two circumstances. The results show that: (1) there is an equilibrium solution in various conditions. Moreover, the optimal price of green certificate in condition two, namely green electricity–green certificate unity, is higher when the on-grid price of green electricity and thermal one and the substitution effect of these two powers satisfy a certain constraint, which can stimulate generator and retailer to generate and consume green electricity as much as possible. (2) The price of carbon emissions and the responsibility weight of renewable electricity consumption both have a positive influence on the optimal price of green certificate and the share of equilibrium demands for green power, whereas intermittency of new energy generation has a negative impact on them. Adjusting the carbon price and incentive responsibility weights and taking relevant measures to reduce intermittency in different situations help to reduce thermal power demand and promote green power consumption. (3) When the prices of green certificates in diverse circumstances are in a certain interval, the impact intensity of changes in green certificate price on electricity demand will arise. It is conducive to performing the facilitative role of green certificate price on the power market better and stimulates the generation and consumption of new energy power in the carbon-electricity coupling market. • Through the carbon-electricity coupling perspective, the optimal TGC price was explored. • Introducing substitution effects of green power and thermal power to analyze optimal TGC prices. • A higher incentive responsibility weight of renewable consumption in scenario two can promote the retailer to consume. • Impact intensity of changes in green certificate price on power demand will arise when the price is in a certain interval. [ABSTRACT FROM AUTHOR]

Based on the extended environmental input-output model and complex network theory, this paper reviews and evaluates the global energy transition based on the principle of shared responsibility, and identifies the key countries affecting the energy transition from the perspective of embodied energy. The results show that although the proportion of clean energy and renewable energy use remains low (only 34.6% and 8.8%), the global energy transition process has progressed rapidly in the past 20 years. From 2000 to 2016, global energy consumption decreased global warming potential (GWP) by 18.7%, acidification potential (AP) decreased by 33.37%, but eutrophication potential (EP) increased by 28.42%. The United States is the largest contributor to the global energy transition, with a total reduction of 1.52 × 10^5 Mt CO 2 -eq, 148.32 Mt SO 2 -eq and 12.4 Mt P O 4 3 − -eq through the energy transition. The energy-consumption emissions from China and other developing countries show an increasing trend (From 2000 to 2016, China increased its emissions by 1.49 × 10^5 Mt CO 2 -eq, 65.09 Mt SO 2 -eq and 76.64 Mt P O 4 3 − -eq). With the slowdown of economic growth and the promotion of energy transition, the growth rate of energy-consumption emissions gradually decreases. Considering embodied energy plays an important role in the scientific evaluation of global energy transition. Under the principle of shared responsibility, ignoring embodied energy is expected to overestimate China's GWP by 4.5%, AP by 3.7%, and EP by 7.4%, and underestimate America's GWP by 10.5%, AP by 7.48%, and EP by 12.5%. We, therefore, focus on the transfer of pollution due to embodied energy and find that China, Russia, India, and South Africa are important agents for the embodied pollution transfer between communities. • Consider the impact of embodied energy on energy transition assessments. • Identifying key countries affecting energy transition from embodied energy. • Calculated the energy transition process of each country. • Measure the energy transition process from multiple perspectives. [ABSTRACT FROM AUTHOR]

Promoting electrical transition in vehicle industry has become one of the main objectives for transportation sectors nowadays. However, no consensus has been reached as to whether the penetration of electric vehicles (EVs) have superiority in energy conservation and carbon reduction with life-cycle thinking. Consequently, this paper applies network evolutionary game theory to investigate the evolution trend of industry energy conservation and carbon reduction with promoting electrification in China. To fit the real decision-making environment faced by manufacturers, the greenness competition interactions, competitive strategy invasion, and market uncertainty are further considered under the impact of dual credit policy. Results show that implementing dual credit policy makes electrical transition an irreversible trend for manufacturers, but it does not mean that internal combustion engine vehicle will disappear, rather, it coexists with EVs in a certain proportion, which is negatively related to consumer's acceptance toward EVs. Meanwhile, to address energy conservation and carbon reduction, manufacturers should be encouraged to choose a fuel reduction strategy to decelerate the industry electrification trend, thus acquiring better energy conservation performances. And before increasing consumer's acceptance toward EVs, increasing the proportion of renewable source in primary energy warrants greater urgency and effectiveness to achieve life-cycle emission reduction advantage of EVs. • It is an irreversible trend for all manufacturers to choose electrical transition. • Internal combustion engine vehicles will coexist with electric vehicles eventually. • High invasion ratio of fuel reduction strategy initially is suggested. • Promoting the clean energy supply is of more urgency and effectiveness. • Optimal new energy credit price exists for fuel and carbon reduction objectives. [ABSTRACT FROM AUTHOR]

In this paper, an improved hybrid MADM method based on interval Decision Making Trial and Evaluation Laboratory (DEMATEL) and interval regret theory are put forward to evaluate five renewable energy alternatives for Fujian province, China. Firstly, the volatility of the evaluation information and the subjectivity of experts or stakeholders are taken into account. Second, political factors are further considered based on existing research. Third, the influence of the subjective initiative of decision makers on the decision result has been paid attention to. Furthermore, the result of the analysis shows that the extended regret theory method should set different parameters to reflect the preferences of decision makers. The ranking results of renewable energy are different with different parameter settings. For example, when α = 0.1 , δ = 0.1 , the priority of clean energy in Fujian Province is hydropower, followed by wind energy, solar energy, geothermal energy, and biomass energy. Sensitivity analysis indicates that the model possesses good serviceability. Based on considering different parameter settings, the Fujian government should invest, in order of priority, in these renewable energy sources to obtain benefits. And the projects related to these renewable energy sources should be evaluated. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, China vigorously develops clean energy and renewable energy. As a result, offshore wind power projects have grown rapidly. The success of offshore wind power projects depends on the location of offshore wind power station(OWPS), and this paper aims to develop a hybrid decision-making framework to address the location of offshore wind power stations. Firstly, a comprehensive evaluation attribute system of offshore wind power station site selection is innovatively constructed, including wind resources, construction conditions, economy, environment and risks. Secondly, probabilistic linguistic term set(PLTS) is used to describe uncertain information, which improves the reliability of decision information. Thirdly, The Best-worst method (BWM) based on probabilistic language term sets determines the weights of attributes, which ensures the accuracy of the attribute weight. Finally, an extended TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method is proposed to rank the alternatives. The proposed method is applied to the location selection of offshore wind power station in Jiangsu Province, China. Through sensitivity analysis and comparative analysis, it is verified that the proposed model has good stability and applicability. • A new multi-attribute decision-making model is proposed. • Establish the evaluation attribute system of offshore wind power station location. • Expression of evaluation information by probability language. • Probability Language and Best-worst Method Combined to Calculate Attribute Weight. • An improved Interactive and Multicriteria Decision Making method is proposed. [ABSTRACT FROM AUTHOR]

• Analysis of the techno-economic pathways to net-zero emission attainment in China. • Analysis of peak carbon emission and carbon neutrality by year 2030 and 2050. • Solar PV, biomass, hydro, and wind power are considered for 100 % decarbonization. • River hydro is constructed considering dry, normal, and wet years. • Carbon emission is reduced by 13.26% to 15.3% between 2030 and 2050. With the imminent acute problems and the harsh reality of climate change, many countries/groups of countries have developed policies to reduce their carbon emission. At the end of 2020, the Chinese government announced a revised policy that will see the country attain carbon neutrality by 2060 and peak emission by 2030. This study aims to determine the techno-economic requirements for net-zero emission attainment in China. The models created are used to explicate the 100% integration of renewable energy into the energy systems in a Province in China considering the years 2030 and 2050. This study is novel as it aggregates the detailed requirements of all the energy sectors and the government policies for the case study. While the approach presented in this paper is applied specifically to Sichuan Province, China, the application of this method is limitless as it is vast and viable for other countries. This study can also serve as a template for many high carbon-emitting countries with sizeable RE potential. The total energy demand in the case study is summarized under three sectors; electricity, industry, and transport. Following the government policies, renewable energy sources such as wind power, solar PV, river hydro, and biomass are considered for 100% decarbonization of the case study. River hydro being the predominant renewable energy source in this region is constructed considering three levels of hydro (dry, normal, and wet) years. The 2017 energy demand and supply data are first used to develop/validate the model on the EnergyPLAN simulation platform, then the 2030 proposed pathway to peak carbon emission by the government is analyzed. Three innovative pathways to net-zero emission attainment by 2050 are proposed in this study considering the additional use of biomass (BIO model), pumped hydro storage (EES model), and the import of clean electricity from neighboring provinces (IMP model). Based on the analyses in this study, the proposed pathway by the government cannot achieve net-zero emission by 2050, however, the three optimized strategies/models presented in this study show a clearer and faster path to decarbonization. Carbon emission will reduce by 13.26 %, 14.77%, and 15.3 % between 2030 and 2050 reference models for the dry, normal, and wet year scenarios respectively. From the three optimization models, the total cost of the import model was the lowest under different scenarios. Therefore, the economic feasibility of this approach proves the superiority of the import model in terms of economic benefits. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) trade disputes have been rising in response to certain green industrial policies, i.e., policy mechanisms used to develop domestic RE industries and accrue associated local economic benefits. Since 2011, countries have been increasingly filing trade litigations to counter the use of green industrial policies by their trading partners so that they can expand RE industry competitiveness and the associated manufacturing jobs within their own countries. However, in the absence of systematic studies on the impacts of RE trade duties, evidence regarding their success in achieving these economic goals remains limited. In this paper, the effectiveness of RE trade duties in supporting employment, especially in manufacturing, is assessed. First, the literature on the motivations behind RE trade duties is reviewed, and then the case of trade duties imposed by the US on the imports of solar and wind energy components from China between 2011 and 2019 is examined. Although several factors may drive employment, no evidence is found for the increase in jobs in solar and wind manufacturing in the years after the trade duties were imposed. Meanwhile, downstream jobs in installation, operation and maintenance continued to grow, corresponding to increases in annual installation of solar and wind capacity in the US. These were driven by policy incentives and the declining costs of solar and wind technologies. Overall, this case study highlights the broader implication that trade duties alone are unlikely to promote local manufacturing industries, and countries would benefit from other well-designed policies. • Renewable energy (RE) related trade disputes rising but studies examining effectiveness of trade duties limited. • Literature on the goals behind trade duties on RE components reviewed. • A framework developed to assess the relationship between RE trade duties and manufacturing employment. • Framework applied to examine the case of trade duties by the US on the imports of solar and wind energy components from China. • Trade duties not effective to develop local RE industries; other well-designed policies needed to increase local RE manufacturing jobs. [ABSTRACT FROM AUTHOR]

Following India's efforts to mitigate the emission of greenhouse gases, there has been a transition from fossil fuels to clean energy sources, such as solar and wind, in the energy portfolio. The renewable energy sector is widely acknowledged as a fertile ground for employment creation, as it is labour-intensive. Against this backdrop, the main objective of this paper is to provide an empirical explanation of how the growth of renewable energy sources, particularly solar photovoltaic (PV) technology, affects employment creation in India. The findings reveal that, despite a substantial investment in India's solar PV technology, the number of jobs created by the sector declined marginally from 164000 in 2017–114000 in 2018. India's estimated employment elasticity is just 0.004, implying that the level of employment does not show a significant positive response to changes in installed capacity. Almost 60 per cent of the global solar PV workforce is in China, which has become the leading country both in terms of installed capacity of global solar PV technology and manufacturing of solar PV cells and modules. The wide disparity in solar PV employment between India and China is explained by the former's excessive dependence on China for solar PV cells. Alongside climate conservation, India should, therefore, place more emphasis on revitalising the domestic solar manufacturing industry to bring about efficient use of the nation's untapped resources. [ABSTRACT FROM AUTHOR]