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With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

Regional integrated energy systems (RIES) can economically and efficiently use regional renewable energy resources, of which energy storage is an important means to solve the uncertainty of renewable energy output, but traditional electrochemical energy storage is only single electrical energy storage, and the energy efficiency level is low. Hydrogen energy storage has the advantages of large energy storage capacity, long storage time, clean and pollution-free, and can realize the synergistic and efficient utilization of electricity and thermal power. Based on this, this paper proposes a synergistic planning method for an integrated energy system with hydrogen storage taking into account the coupled use of electric-thermal energy, which effectively reduces the system carbon emission and improves the comprehensive energy efficiency level. Firstly, this paper constructs an electric-thermal coupling model of the hydrogen energy storage unit and proposes an optimization strategy for the integrated energy system containing hydrogen storage taking into account the utilization of electricity and thermal power. Secondly, a planning optimization model with the lowest economy and carbon emission and the highest comprehensive energy efficiency was constructed. Third, the CSPO-GE optimization algorithm is proposed for solving the problem, which significantly improves the solution efficiency. Finally, a planning optimization simulation of RIES for a residential community W in northern China verifies the effectiveness of the model and method proposed in this paper. The comparative analysis of the three schemes shows that compared with the integrated energy system with conventional electrochemical energy storage and heat storage tank as the main form of energy storage and the integrated energy system with only hydrogen storage, the integrated energy system with hydrogen storage and heat storage tank can reduce carbon emissions by 43.8% and 7.61%, respectively, and improve the integrated energy efficiency level by 337.14% and 14.44%. • An electrothermal coupled production strategy based on dynamic equilibrium feedback regulation is proposed. • A hydrogen-containing RIES planning and optimization model considering economy-environment-efficiency is constructed. • A multi-objective chaotic particle swarm algorithm (CPSO-GE) based on greedy and elite retention strategies is proposed • The impact of cost variation of hydrogen storage devices on the economics of integrated energy systems is considered. [ABSTRACT FROM AUTHOR]

• A simple, large-scale fabrication of cooling paper via pulping and papermaking technology. • The cooling paper is facilely deconstructed and regenerated to architect the secondary cooler. • The cooling paper features a high solar reflectance of 94% and emissivity of 0.95. • The cooling paper shows the sub-ambient temperature drop of 6 ∼ 8.8 °C under directly solar radiation at daytime. Passive radiative cooling materials provide coldness without energy consumption for all-day thermal comfort by reflecting solar irradiation and emitting heat into the 3 K universe. However, the conventional radiative cooling materials involve complex multilayer structures and unsustainable polymers, showing the non-recyclable disadvantage, which induces resource waste and environmental issues. Herein, we reported a low-cost, scalable, and eco-friendly radiative cooling material (namely cooling paper), consisting of the delignified, fibrillated cellulose fibers and nano-sized hydroxyapatite (HA) via the mature pulping and papermaking process. The resulting cooled paper can be recycled, and it can be easily deconstructed to harvest cellulose fibers and HA, individually. The recovered source materials can be reused to prepare secondary products that show comparable performance to the original cooling paper, including a high solar reflectance of ∼94% and an infrared emissivity of ∼0.95 in the atmospheric transparency window. Such cooling paper enables superior cooling performance with the temperature drop of 6 ∼ 8.8 °C under directly solar radiation. Based on the EnergyPlus simulation, our cooling paper shows a average cooling energy saving of ∼29 % in buildings across China. The recyclable cooling paper with high cooling capability and scalability, as well as environmental friendliness, shows promising potential for sustainable energy-efficient buildings. [ABSTRACT FROM AUTHOR]

Developing renewable energy has become a major strategy for China to accelerate the energy transition and combat climate change. Accordingly, a guarantee mechanism for renewable energy consumption with renewable portfolio standards (RPS) has been set in China. However, currently, the top-down allocation of regional renewable energy consumption targets often has issues of unfairness and inefficiency. It is necessary to investigate the issue of how to stimulate the renewable energy consumption potential on the demand side and reasonably formulate the consumption responsibility weights of various market entities. This paper aimed to develop a new methodology for the weight allocation of renewable energy consumption responsibilities. In doing so, an integrated model of an evolutionary game and stochastic optimization was constructed between market entities and governments. Then, the equilibrium strategies of market entities and governments were obtained through the evolutionary game. Furthermore, based on the equilibrium strategies, this paper optimized the renewable energy consumption weight of each market entity, which constitutes the optimal allocation scheme of renewable energy consumption responsibility weights. Finally, using the data of 7069 market entities in Hubei Province in 2021, this study simulated the model to verify its effectiveness and practicability. The results indicate that the willingness of market entities to assume more consumption responsibility is positively correlated with the government's incentives and the maturity of the green electricity trading market. This study provides important implications for optimizing government regulations and promoting renewable energy consumption. [ABSTRACT FROM AUTHOR]

A Chinese solar greenhouse (CSG) is an agricultural facility type with Chinese characteristics. It can effectively utilize solar energy during low-temperature seasons in alpine regions. The low construction and operation costs make it a main facility for agricultural production in the northern regions of China. It plays an extremely important role in "Chinese vegetable basket projects". Energy is one of the important issues faced by CSGs. The better climate resources in the northern regions of China make it possible to apply solar energy as a green and sustainable energy source in the production of CSGs. Faced with the increasingly serious environmental problems of the new century, the Chinese government has made a decision and put it into practice to improve the rate and efficiency of solar energy utilization in agricultural facilities. In this paper, we summarize the research on the application of photovoltaic power generation and solar thermal technology in CSGs. The application of these advanced solar technologies has made great progress. With the further improvement of economic benefits and the establishment of relevant support policies and incentive mechanisms, the combination of CSG and solar energy technology will have certain application prospects and satisfy China's requirements for long-term sustainable development. [ABSTRACT FROM AUTHOR]

Climate change is directly linked to a broad array of changes because of disorganized activities within the economic system and human intervention. Climate change affects the well-being status of both non-living and living things. Relevant policies to mitigate and adapt to climate change conditions concentrate on solutions that intend to use renewable energy instead of fossil fuels or other conventional energy sources. This study aims to process a review focused on how renewables advance environmental quality and create relevant benefits within severe economic activities. This study elaborates on the case of China for two main reasons. First, China has a pivotal role in the economic system worldwide. Second, China is making serious attempts to transition into a low-carbon economy. An integrative review was processed to receive selected publications. The advantage of this process is that it considers empirical and non-empirical studies, policy papers, and conceptual frameworks. Inclusion and exclusion criteria were applied to retrieve the final number of publications. Review results from 39 well-acknowledged Journals provided 180 selected publications categorized into seven study groups: data analyses, model optimization studies, market issues, renewable energy technology publications, nuclear energy publications, ocean energy publications, and policy-related studies. Policy implications concern China's efforts to accelerate the integration of renewables in the energy mix. Hence, the country should increase energy efficiency in consumption and process investment plans based on robust research and development efforts. [ABSTRACT FROM AUTHOR]

The development of renewable energy in China has made remarkable achievements, but the problem of renewable energy consumption has become increasingly prominent. This paper establishes a power market trading system for renewable energy, with the aim of promoting large-scale renewable energy consumption and increasing the enthusiasm of renewable energy producers and users to participate in market transactions. First, according to the power generation cost, the backup cost of renewable energy power plants and the possible quotation strategies of other renewable energy producers, a quotation model of renewable energy producers is established. In the clearing of the spot market by renewable energy producers, the independent market operator conducts the first-stage clearing of the electricity market with the goal of maximizing social welfare. After the announcement of the clearing results, the renewable energy producers that did not win the bid will revise their quotations and carry out the second stage clearing to realize the consumption of renewable energy. In this paper, the particle swarm algorithm combined with the CPLEX solver is used to solve the problem, and finally, different scenarios are analyzed through example analysis. The results show that, compared with the conventional power market trading mechanism, the energy abandonment rate of the power market trading mechanism for renewable energy proposed in this paper drops from 8.2% to 2.1%, and the profit margin of renewable energy producers increase by 6.6%. It is demonstrated that the proposed electricity market mechanism can effectively promote the consumption of renewable energy and increase the income of renewable energy producers. [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]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

Hydrogen is receiving unprecedented momentum and is projected to meet a sizable share of the final energy demand in the future. The coupling between the hydrogen and power systems can help integrate volatile renewable energy, reduce curtailment, and realize long-term energy storage. Different coupling modes are being proposed, yet quantitative comparisons are absent. To fill this gap, this paper firstly summarizes the system composition of potential power–hydrogen coupling modes and analyzes their advantages and disadvantages. Then, a model for power–hydrogen coordinated planning optimization is proposed for quantitative analysis. Southern Xinjiang is chosen as a representative of the northwestern area in China, which has plentiful renewable resources and a relatively small local load at present, for a case study. Through result analysis, it is found that the mode of power–hydrogen coupling at the source side, either for in situ utilization or for long-distance transport via pipelines, shows better economic competitiveness. The discussion provides suggestions and a reference to policymakers for formulating infrastructure or industry plans in advance to better accommodate the rapidly developing renewable energy. [ABSTRACT FROM AUTHOR]

The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

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

The 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]

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]

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]

[Display omitted] • PCM energy storage and PV/T coupled multi-source heat pump systems were combined. • The thermal performance, energy efficiency, and economy of the system were analyzed. • The performance of paraffin C17 and water as energy storage materials were compared. • The performance of six low-temperature PCMs applied to the system were analyzed. • Compared to the existing system, it saves 56 % of energy and 27.7 % of operating costs. To improve the application of renewable energy in the heating zone, as well as to address the limitations of air and water source heat pump. The study presents a PV/T (photovoltaic/thermal) coupled air–water source heat pump system integrated with phase change energy storage. A theoretical analytical model and TRNSYS simulation model of the system were developed to evaluate the thermal performance, energy efficiency and economics of the system. The performance of phase change energy storage was compared with that of water storage, and the effect of different phase change materials on the system characteristics. The results show that the coupled system achieves a seasonal performance factor of 2.3, a 56 % reduction in energy consumption, and a 27.7 % reduction in operating costs compared to a conventional gas boiler system. Comparative analysis with the water storage system showed that the system equipped with phase change materials performed well in terms of energy consumption, operating costs and heating stability. In addition, the density of the phase change material has a biased effect on the overall performance of the system. This paper can provide a reference value for the study of renewable energy heating systems in cold zone. [ABSTRACT FROM AUTHOR]

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

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

In the extant literature, there are numerous discussions on China's environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint. [ABSTRACT FROM AUTHOR]

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

This paper examines the nexus between fiscal decentralization and renewable energy demand by including income inequality, economic growth, urbanization, and economic globalization as the main determinants in the energy demand function for the case of China. Quarterly frequency data for the period 1980–2018 are used for empirical analysis. Our empirical results show fiscal decentralization positively impacts the demand for renewable energy; in other words, fiscal decentralization can help increase renewable energy demand. In addition, income inequality is negatively linked to renewable energy consumption, while economic growth is positively associated with renewable energy demand. Urbanization and economic globalization add to renewable energy consumption. This study presents Chinese authorities with new guidelines for using fiscal decentralization as an economic tool to formulate effective energy policies for long-term development of the use of renewable energy sources. [ABSTRACT FROM AUTHOR]

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

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

Under the background of "carbon neutrality" and "carbon peak" concepts, China desires to develop a new power system based on renewable energy sources (RES), which will be the primary energy support in prospective China. Thus, it is imperative to improve the peak shaving capability of power system to address the problem of random fluctuation and intermittency of RES by developing various energy storage systems. An innovative approach to enhance the flexibility of the conventional thermal power unit (TPU) through the utilization of flywheel energy storage array (FESA) is presented, simulated, and evaluated in this paper. Using the relatively practical and specific model of TPU and FESA, modified frequency modulation and automatic generation control (AGC) instruction tracing operation scenario models are constructed. A comprehensive control strategy of FESA and a well-designed operation coordinated control method for TPU with FESA are proposed and applied. The simulation results are distinctively processed and evaluated by the methods in "two documents", aiming to assess the real-world operation performance of the model proposed in this paper. The comprehensive analysis of the indicators demonstrates that the FESA can improve the flexibility and economy of the units. This research may guide the usage of FESA to improve the operational flexibility of TPU. • Composition and Control Methods of the flywheel energy storage array are provided. • A coordinated control scheme for the thermal power unit with flywheel energy storage array is proposed. • Frequency modulation and AGC instruction tracking scenario models are constructed and simulated. • AGC regulation indicators are conducted and analyzed to evaluate the unit's performance. [ABSTRACT FROM AUTHOR]

This paper studies the impact of the development of green finance on China's energy consumption structure. 17 basic indexes and the improved entropy weight method are used to construct the green finance index (GFI). Multiple regression, panel regression, and spatial regression are used to study the impact of green finance on China's traditional energy and renewable energy consumption. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. The green finance in each province not only helps the local development of green energy but also plays a good role in the production and utilization of clean energy consumption in surrounding provinces. Therefore, the government should support the green finance, reduce traditional energy consumption, and increase renewable energy consumption. [ABSTRACT FROM AUTHOR]

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

China has set a goal to achieve peak CO2 emissions before 2030 and carbon neutrality by 2060. To achieve the goals of carbon peak and carbon neutrality, China needs to address the challenge of the large and still growing CO2 emission base. This paper investigated the energy consumption and CO2 emission in Beijing from 2020–2035 based on the energy elasticity coefficient and contribution value of the sub-energy increment (CVSI) method. Beijing is one of the first cities in China to propose the "carbon peak" target as of 2020. From 2020 Beijing will strive to achieve the goal of carbon neutrality. The results show that in 2035 the CO2 emission in Beijing may drop to 50% of 2020. This decline would be affected by economic growth, energy efficiency and the proportion of renewable energy use. Beijing's energy supply mainly comes from outside the region. Therefore, for Beijing, in addition to increasing the proportion of renewable energy sources outside the region, its own energy acceptance also needs to be strengthened, including strengthening energy storage construction, actively researching and promoting carbon capture and utilization of gas-fired units, which are effective ways to achieve carbon neutrality target. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies. [Display omitted] • Enrich the view of renewable energy's indirect impact on carbon emissions. • Renewable energy's carbon emission reductions go beyond replacing fossil fuels. • Constructed a mediating effect model between renewable energy and carbon emissions. • Renewable energy can promote or inhibit carbon emissions through various pathways. • Research helps develop more effective renewable energy sustainability strategies. [ABSTRACT FROM AUTHOR]

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

As global energy demand continues to grow, the demand for renewable energy continues to rise. To meet this demand, many countries have begun to actively promote the development of offshore wind power projects. Since siting is the key to the success of offshore wind power projects, this paper aims to develop a mixed decision-making framework to address the siting of offshore wind power station (OWPS). Firstly, establish a relatively comprehensive OWPS evaluation attribute system. Secondly, the pythagorean hesitation fuzzy set (PHFS) was used to describe the evaluation information in the OWPS site selection process. It can ensure the hesitancy and fuzziness of evaluation information, and is not constrained by the sum of membership and non membership being less than 1. Thirdly, the improved SWARA method is used to calculate the weight of attributes. Finally, an extended MULTIMOORA (Multi-Objective Optimization on the basis of a Ratio Analysis plus the Full Multiplicative form) method is proposed to rank the siting alternatives for OWPS. The proposed method is applied to the study of OWPS site selection in Shandong Province, China. Through calculation, the comprehensive ranking values are G 1 = 14, G 2 = 7, G 3 = 4, G 4 = 8 and G 5 = 13. Therefore, A 3 is the best alternative. Through sensitivity analysis and comparative analysis, it was verified that the proposed model has good reliability and stability. • A new multi-attribute decision-making model is proposed. • The attribute system for site selection evaluation of OWPS is established. • Expression of evaluation information by pythagorean hesitation fuzzy set. • Pythagorean hesitation fuzzy set and SWARA are combined to calculate attribute weight. • An improved MULTIMOORA method is proposed. [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric effects of oil price shocks on coal and renewable energy consumption in China over long and short periods. The novelty of this study is to investigate whether the consumption of coal and renewable energy are asymmetrically affected by the oil price in a time–frequency framework by performing a Fourier nonlinear ARDL model which is robust to overcome the multiple smooth structural changes in data. The bounds test of the FNARDL specification provide strong evidence of cointegration among variables, including coal energy consumption, renewable energy consumption, oil price, and economic growth. Results reveal the following: First, the oil price-coal energy consumption and oil price-renewable energy consumption relationships are nonlinear. Second, oil price increases have significant short-run effects on coal energy consumption. However, oil price increases induce an increase in renewable energy consumption in China in both the short and the long term. Finally, the relationship between coal energy consumption and economic growth is U-shaped. Hence, increasing oil prices boost China's prospects for coal in the short term and its usage of renewable energy in the long run. • Effect of oil price on coal and renewable energy consumptions in China is tested. • Strong evidence of cointegration among variables is shown. • Oil price increases have significant short-run effects on coal energy consumption. • Oil price increases induce an increase in renewable energy consumption in China. • Relationship between coal energy consumption and economic growth follows U-shaped. [ABSTRACT FROM AUTHOR]

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

• Comprehensive energy base planning model integrating DLR and industrial DR. • Extends DLR to planning stage, linking RES generation with DLR calculations. • Process modeling of coal-to-methanol production and energy-consuming process. • Highlights potential for optimizing energy base operations with industrial loads. • Real case study on energy base validates effectiveness of proposed model. The integration of renewable energy sources (RES) into power systems during the low-carbon transformation has resulted in the emergence of energy bases due to geographical imbalance between electricity production and consumption. Existing research often assumes that the transmission capacity is fixed when optimizing energy base sizing, without considering the dynamic changes in the real environment. Additionally, energy base planning traditionally relies on allocating flexible resources to ensure flexibility and hedge against operational risks resulting from RES uncertainty. However, the approach neglects the inherent operational flexibility of local high-consumption loads and their potential for generation substitution. To address these issues, the paper proposes an optimal energy base planning method considering dynamic line rating (DLR) and integrated industry demand response (DR). Firstly, a planning-oriented approach is proposed to estimate transmission capacity by establishing the relationship between wind/solar power generation and DLR calculation. Furthermore, the study explores the operational flexibility and maximum generation substitution capacity of the chemical industry using the state-task network. Finally, the proposed model is validated using a modified energy base located in North China. Numerical results demonstrate that considering DLR and industrial DR improves the economy of the energy base and facilitates RES utilization. [ABSTRACT FROM AUTHOR]

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

Multiple geographically dispersed data center buildings have been increasingly positioned in renewable-rich areas due to their high energy consumption. This paper proposes an optimal multi-energy portfolio for zero carbon data center buildings in the presence of proactive demand response programs. In the data center buildings, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via multi-energy conversion and storage devices, which are modeled as 100% renewable energy hubs for zero carbon multi-energy supplies. In order to exploit the hub-internal operational dispatchability and flexibility, a comprehensive energy consumption model of data center buildings is proposed to facilitate the demand response in terms of available serves, while the variable speed pumped storage (VSPS) is modeled to capture its dynamic operational characteristics. The energy‑carbon production, conversion, storage, and consumption are formulated as an energy‑carbon matrix, which are solved via a two-stage method to obtain the optimal portfolio. Case studies on southwest China data center buildings are implemented to demonstrate the effectiveness and superiority of the proposed methodology on cost-effective accommodation of RESs. Simulations results show that the system portfolio cost can be reduced by at most 17.8% with a higher operational flexibility. • A cost-effective data center building is proposed to accommodate zero carbon targets. • Hydro-solar-wind 100% renewables are formulated for multi-energy supplies. • VSPS and data center energy consumption are modeled to exploit inherent flexibility. • The energy-carbon production, conversion, storage, and consumption are optimized. [ABSTRACT FROM AUTHOR]

Integrated energy system is an important approach to promote large-scale utilization of renewable energy. Under the context of energy market reformation and technology advancement, the economic operation of integrated energy system confronts new challenges, in terms of multiple uncertainties, multi-timescale characteristics of heterogeneous energy, and coordinated operation of hybrid energy storage system. To this end, this paper investigates the multi-timescale rolling optimization of integrated energy system with hybrid energy storage system considering the above challenges. Firstly, a basic framework of an integrated energy system with hybrid energy storage system (consisting of battery and hydrogen storage) is proposed, and the typical devices are modeled in detail. Secondly, the parameters and variables are divided into fast/slow timescale according to dispatch needs, and the multi-timescale problem of heterogeneous energy and the coordinated operation of the hybrid energy storage system can be solved simultaneously through two-stage optimization. Thirdly, the dispatch model is incorporated into the framework of model predictive control, the uncertainty of price, renewable energy and load can be effectively handled. Finally, a case study is conducted using an industrial park in the southern coastal region of China, the comparison with the rule-based method shows 60.65% reduction in the operating cost of hybrid energy storage system, the comparison with robust optimization shows 7.01% reduction in the total cost of the system, thus the feasibility and effectiveness of the proposed method are verified. • The application of HESS in IES is considered and modeled in a more detailed way. • Based on the two-stage approach, the heterogeneous energy multi-timescale scheduling problem and the HESS coordinated operation problem of IES can be solved simultaneously. • The dispatch model is incorporated into MPC for rolling optimization, and multiple uncertainties are effectively handled. • Using an industrial park in the southern coastal region of China as case study, the feasibility and effectiveness of the proposed method are verified. [ABSTRACT FROM AUTHOR]

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

• A multiple criteria analysis method is proposed to compare renewable energy and traditional solutions for off-grid island power supply. • Life cycle cost is used to build the economic model. • The fuzzy analytic hierarchy process is used to quantify the risk level. • A simulation platform is built to obtain the energy utilization. • Applied to the actual project to verify the feasibility of the method. Renewable energy microgrids are a new option for powering remote islands. To explore the feasibility of constructing island microgrid in China, based on the failed Dongfushan Island Demonstration Microgrid Project caused by equipment failure, low economic benefits, low residents' satisfaction, and poor power supply stability, this paper compares two power supply methods, microgrid and submarine cable. A systematic multiple criteria analysis method is established to compare these two methods, including economic analysis, risk assessment, energy spilled and energy shortage. Net present value and the life-cycle cost method are used to establish the economic cost model. Fuzzy analytic hierarchy process is used to establish the risk assessment model. Additionally, the simulation using PVsyst software is used to calculate the energy spilled and energy shortage. Furthermore, future trends are predicted with data to provide suggestions for decision-makers. Multiple criteria analysis results showed that energy spilled and shortages are inevitable for the use of microgrid on seasonally tourist islands like Dongfushan Island, with energy spilled and shortages rate as high as 50.11% and 37.57% in the worst case. The microgrid risk level is relatively low risk, higher than the lowest risk level for submarine cables. At full capacity, the cost of microgrid (34.03 million yuan) is comparable to submarine cables (30.31 million yuan), making the latter more suitable for power supply due to its better reliability. [Display omitted] [ABSTRACT FROM AUTHOR]

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

Under the carbon peak and neutrality targets, the power generation industry in China is facing an urgent demand for a low carbon transition and participation in the electricity-carbon market. This paper novelty proposes a near-zero carbon emission power plant (NZCEP) integrating gas turbines, wind turbines, power-to-gas and the carbon capture, utilization and storage system. And a two-stage Data-driven Set based robust optimization (DSRO) model, including a day-ahead dispatching phase and a real-time adjustment phase, is conducted to ensure the consumption of renewable energy resources and to develop the optimal operating strategy for NZCEP participation under the electricity-carbon market. The results demonstrated the following outcomes: (1) NZCEP shows better environmental benefits by reducing carbon emissions and consuming renewable energy resources. (2) the DSRO model can resist the interference of wind power output uncertainties and address the issue of traditional robust models being overly conservative. (3) under the electricity-carbon market, NZCEP shows better economic benefits, which can generate additional revenue from selling surplus carbon emission allowances (CEA). Moreover, when the annual average CEA price reaches 355 CNY/t, the NZCEP will achieve full capital cost recovery. • Optimal operation of near-zero carbon emission power plant (NZCEP) is studied. • A Data-driven robust optimization model is proposed for NZCEP operating. • Carbon emissions reduction and wind power accommodation of NZCEP are verified. • The economy of NZCEP participation in the electricity-carbon market is analyzed. [ABSTRACT FROM AUTHOR]

• Province-level grid parity potential of wind and solar PV power plants in China. • Techno-economic feasibility of baseload supply in hybrid renewable energy system. • Correlation analysis of system cost and resource potential and complementarity. • Projected Grid parity potential of renewable energy system for baseload supply. To promote the large-scale deployment and grid integration of renewable-based power system, this paper investigates the province-level techno-economic feasibility of wind-photovoltaic-battery hybrid renewable energy system (HRES) for baseload supply application around China. Firstly, the power generation cost and grid parity potential of province-level standalone wind and photovoltaic power plants are assessed. Then, the optimal sizing of province-level HRESs aims to minimize the net present cost and meet the reliability constraint for baseload supply, which is solved by teaching and learning-based optimization. Finally, the techno-economic comparison between different system configurations, the correlation between HRES cost-effectiveness and resource potential as well as resources complementarity, and the grid parity potential of HRES for baseload supply are quantitatively analyzed. The results reveal that: (i) 84.4% of regions in China can achieve solar photovoltaic plant-side grid parity in 2022, while only 15.6% of regions can achieve wind power plant-side grid parity; (ii) HRESs in all regions are technically feasible but not cost-effective for baseload supply; (iii) wind-photovoltaic-battery HRES is the optimal configuration for most regions, indicating that the wind-solar hybridization is more reliable and cost-effective than standalone power plants; (iv) the economic performance of HRES depends mainly on the wind-solar joint resource potentials and the supply-demand relative deviation; (v) investment cost reduction and utilization of energy curtailment are promising to help HRES achieve plant-side grid parity for baseload supply. The findings of this paper can help policy-makers and investors optimally determine the national pathway of renewable energy transition. [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]

[Display omitted] • A method for spatiotemporal coordination of multienergy systems is proposed. • Virtual energy storage gain is calculated based on spectral analysis. • The hydropower regulation ability affects the virtual energy storage gain. • The optimal coordination range between multiple energy sources is obtained. Utilizing the spatial heterogeneity and climate periodicity of various available renewable energy sources can enhance the multienergy complementarity, which will further reduce the energy storage demand and contributes to the "virtual energy storage gain." In this paper, we propose a spatiotemporal coordination method based on spectral analysis for a wind-PV-hydropower system that targets the maximum virtual energy storage gain. The complementary effect of hydropower on wind and PV power can be seen as changes in the regulation ability resulting from the hydropower construction development as well as a decreased variance in the total system production output. This method is used to determine the optimal coordination distance of multiple energy sources that are matched over different periods representing typical climate variation. A case study in the Yalong River basin in China obtains the best range of hydropower bundling surrounding wind power and PV power stations under different hydropower construction planning scenarios, and it reveals that increased regulation capacity of hydropower will reduce the optimal coordination distance but can achieve more energy balance if both actual storage and virtual storage is accounted for. This approach can realize energy delivery with the optimal coordination distance to meet intensive and efficient development needs, which can provide guidance and support for the planning and construction of wind-PV-hydropower storage systems. [ABSTRACT FROM AUTHOR]

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of "power grid company - retailers - users" based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity. • Accurately identify the RE consumption of users under the unified clearing mode. • Construct a transmission mode of RPS assessment among grid, retailers, and users. • Construct a distributed training framework of multi-agent. • The research is helpful in promoting the consumption of new energy. [ABSTRACT FROM AUTHOR]

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of "power grid company - retailers - users" based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity. • Accurately identify the RE consumption of users under the unified clearing mode. • Construct a transmission mode of RPS assessment among grid, retailers, and users. • Construct a distributed training framework of multi-agent. • The research is helpful in promoting the consumption of new energy. [ABSTRACT FROM AUTHOR]

Improving the efficiency of renewable energy and electricity utilization is an urgent problem for China under the objectives of carbon peaking and carbon neutralization. This paper proposes an optimization scheduling method of electric vehicles (EV) combined with wind and photovoltaic power based on the Frank-Copula-GlueCVaR. First, a joint output model based on copula theory was built to describe the correlation between wind and photovoltaic power output. Second, the Frank-Copula-GlueCVaR index was introduced in a novel way. Operators can now predetermine the future wind-photovoltaic joint output range based on this index and according to their risk preferences. Third, an optimal scheduling model aimed at reducing the group charging cost of EVs was proposed, thereby encouraging EV owners to participate in the demand response. Fourth, this paper: proposes the application of a Variant Roth–Serve algorithm; regards the EV group as a multi-intelligent group; and finds the Pareto optimal strategy of the EV group through continuous learning. Finally, case study results are shown to effectively absorb more renewable energy, reduce the consumption cost of the EV group, and suppress the load fluctuation of the whole EV group, which has a practical significance and theoretical value. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

The spatial distribution of biomass resources is not uniform. At present, the zoning of biomass energy development suitability is primarily based on resource potential, whereas energy demand is ignored as an important factor affecting the degree of local energy self-sufficiency. Under the constraints of high transportation costs, solar energy with low geographical constraints can be a supplementary energy source for biomass despite its instability. Based on the energy utilization potential of solar energy and biomass resources, this paper evaluates the energy surplus factor (ratio of renewable resource potential to energy demand) of each city in the study area, takes meeting the specific energy surplus factor as the construction prerequisites of biomass combined heat and power (CHP) plants, calculates the biomass resource utilization rate and energy surplus factor in the study area under different conditions, and provides zoning suggestions and data reference for the unified planning of biomass CHP plants. The minimum energy surplus factor that is suitable for the development of biomass energy is set as the construction threshold of biomass CHP plants (The construction threshold is the minimum condition for the construction of biomass CHP plants. Only areas where the energy surplus factor reaches the preset construction threshold are allowed to build biomass CHP plants). The results show that the construction threshold is negatively correlated with the utilization rate of biomass resources. When the construction threshold is less than 1.4, the utilization rate of biomass resources decreases rapidly with the increase of the construction threshold; when the construction threshold is greater than 1.4, the utilization rate of biomass resources decreases slowly and tends to be flat. It is suggested that biomass resources should be developed in different regions and in stages, and priority should be given to developing areas with an energy surplus factor greater than 1.4. Areas with an energy surplus factor of 0.3–1.4 are considered secondary development areas, and areas with an energy surplus factor of less than 0.3 are not recommended for development; these can meet 31% and 59% of the total energy demand and reduce 50319380 tons and 180524400 tons carbon emissions so that the limited construction cost can meet higher energy demand and biomass resource utilization. • Priority development areas are identified based on solar and biomass potential. • Energy surplus factor is calculated to determine the development suitability. • Strategies for zoning and phased planning of biomass resources are proposed. [ABSTRACT FROM AUTHOR]