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With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

In power systems with high penetration of renewable energy, traditional physical model-based optimal dispatch methods suffer from modeling difficulties and poor adaptability, while data-driven dispatch methods, represented by reinforcement learning, have the advantage of fast decision making and reflecting long-term benefits. However, the performances of data-driven methods are much limited by the problem of distribution shift under insufficient power system scenario samples in the training. To address this issue, this paper proposes an improved scenario division method by integrating the power system's key physical features and the data-driven variational autoencoder (VAE)-generated features. Next, based on the scenario division results, a multi-scenario data-driven dispatch model is established. The effectiveness of the proposed method is verified by a simulation conducted on a real power system model in a province of China. [ABSTRACT FROM AUTHOR]

With the energy structure transition and the development of the green power market, the role of electricity retailers in multi-market green power trading has become more and more important. Particularly in China, where aggressive green energy policies and rapid market transformations provide a distinct context for such studies, the challenges are pronounced. Under demand-side response, electricity retailers face the uncertainty of users' electricity consumption and incentives, which complicates decision-making processes. The purpose of this paper is to explore the optimization decision-making problem of multi-market green power trading for electricity retailers under demand-side response, with a special focus on the Chinese market due to its leadership in implementing substantial green energy initiatives and its potential to set precedents for global practices. We first construct a two-party benefit optimization model, which comprehensively considers the profit objectives for electricity retailers and utility maximization for users. Then, the model is solved by the Lagrange multiplier method and distributed subgradient algorithm to obtain the optimal solution. Finally, the effectiveness of the incentive optimization strategy under the multi-market to promote green power consumption and improve the profit of electricity retailers is verified by arithmetic simulation. The results of this study show that the incentive optimization strategy under multi-market, particularly within the Chinese context, is expected to provide a reference for electricity retailers to develop more flexible and effective trading strategies in the green power market and to contribute to the process of promoting green power consumption globally. [ABSTRACT FROM AUTHOR]

With a significant share of renewable power generation integrated into the power supply, it is crucial to timely adjust the regulating peak load for coal-fired power plants equipped with CO2 capture to ensure the stable operation of the multi-energy supply system. In this paper, the effects of varying boiler loads on the techno-economic performance of the retrofitted power plant were studied. Furthermore, the potential for reducing the cost of CO2 capture was investigated, and early opportunities for demonstration were discussed. Results showed that when the boiler load decreased from 100% turbine heat acceptance condition to 50% turbine heat acceptance condition, the cost of CO2 capture increased from 37.0 $/t CO2 to 57.0 $/t CO2, cost contribution of energy penalty and extra capital investment also increased from 20.6 $/t-CO2 to 25.7 $/t-CO2, and from 16.4 $/t-CO2 to 31.3 $/t-CO2, respectively. Furthermore, by improving separation efficiency from 0.15 to 0.5, a 25% to 30% reduction in CO2 capture cost can be achieved. The cost of CO2 capture could decrease by 42.2–50.5% when the cumulative capacity reaches 250 GW under the high investment learning rate scenario. According to the distribution of coal prices and renewable energy sources in China, the early demonstration projects of multi-energy supply systems should prioritize the northern region. The results of this work can provide informative references for making roadmaps and policies for CO2 emission reduction toward carbon neutrality. [ABSTRACT FROM AUTHOR]

Bearing in mind European Green Deal assumptions regarding a significant reduction of green house emissions, electricity generation from Renewable Energy Sources (RES) is more and more important nowadays. Besides this, accurate and reliable electricity generation forecasts from RES are needed for capacity planning, scheduling, managing inertia and frequency response during contingency events. The recent three years have proved that Machine Learning (ML) models are a promising solution for forecasting electricity generation from RES. In this review, the 8-step methodology was used to find and analyze 262 relevant research articles from the Scopus database. Statistic analysis based on eight criteria (ML method used, renewable energy source involved, affiliation location, hybrid model proposed, short term prediction, author name, number of citations, and journal title) was shown. The results indicate that (1) Extreme Learning Machine and ensemble methods were the most popular methods used for electricity generation forecasting from RES in the last three years (2020–2022), (2) most of the research was carried out for wind systems, (3) the hybrid models accounted for about a third of the analyzed works, (4) most of the articles concerned short-term models, (5) the most researchers came from China, (6) and the journal which published the most papers in the analyzed field was Energies. Moreover, strengths, weaknesses, opportunities, and threats for the analyzed ML forecasting models were identified and presented in this paper. [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]

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]

The demand for the power grid system's capacity to undergo peak-shaving is increasing as the proportion of renewable energy rises. In China, nuclear power units usually only provide a base load operation in the view of safety and economic considerations, but they do not provide load adjustment services, which undoubtedly increases the pressure of grid load adjustment. In this paper, a novel flexibility load adjustment strategy of the CHP nuclear unit is studied, which is achieved by introducing the thermal storage tank (TST) into the Rankine cycle without changing the output of the nuclear reactor. The AP1000 pressurized water reactor nuclear power unit for combined heat and power is taken as an example, and the thermodynamic model is established through the water vapor equation. Furthermore, the reference system is simulated for the goal of minimizing the imbalance between power supply and demand, and the flexibility–environment–economy benefits are evaluated. The results show that the heat storage/release of the TST may achieve power output flexible adjustment of the nuclear unit, and the power imbalance of the reference energy system is reduced from 1107.99 MWh to 457.24 MWh, a reduction of 58.73%. The introduction of a 600 MWh TST can enable the reference unit to contribute 335 MWh of peak electricity within the reference day. From the perspective of replacing the power generation output increment of coal-fired power units with equal amounts, it can achieve a reduction of 106.09 tons of coal consumption in the case day, which means that 277.73 tons of CO2 emissions can be reduced. The profit of the reference unit can be improved by CHY 70,125 via participating in load adjustment in the case day if following the time-of-use electricity price. [ABSTRACT FROM AUTHOR]

The large-scale centralized development of wind and PV power resources is the key to China's dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh. [ABSTRACT FROM AUTHOR]

With the increasing severity of climate change, the power industry, as one of the main sources of carbon emissions, is playing an extremely important role in the process of low-carbon energy transformation. The purpose of this paper is to try to find a general method to solve the optimal path for the low-carbon evolution of the power supply structure so as to meet the challenges faced by the low-carbon transformation of the power industry in the future. This paper first uses the capacity coefficient index (CCI) to represent the power generation ability of different technologies and proposes a forecasting method for the CCI of renewable energy generation. In this paper, a two-layer optimization model considering multiple constraints is established and solved using the MPC method. The results show that China's installed capacity of renewable power could account for more than 50% in 2030, while the carbon emissions will decrease after reaching a peak in 2023. On the premise of ensuring sufficient reserve adjustment capacity of thermal power units, increasing the proportion of renewable energy generation is an important way to realize emission reduction in the power industry. [ABSTRACT FROM AUTHOR]

Solar hydrogen production technology is a key technology for building a clean, low-carbon, safe, and efficient energy system. At present, the intermittency and volatility of renewable energy have caused a lot of "wind and light". By combining renewable energy with electrolytic water technology to produce high-purity hydrogen and oxygen, which can be converted into electricity, the utilization rate of renewable energy can be effectively improved, while helping to improve the solar hydrogen production system. This paper summarizes and analyzes the research status and development direction of solar hydrogen production technology from three aspects. Energy supply mode: the role of solar PV systems and PT systems in this technology is analyzed. System control: the key technology and system structure of different types of electrolytic cells are introduced in detail. System economy: the economy and improvement measures of electrolytic cells are analyzed from the perspectives of cost, consumption, efficiency, and durability. Finally, the development prospects of solar hydrogen production systems in China are summarized and anticipated. This article reviews the current research status of photovoltaic-photothermal coupled electrolysis cell systems, fills the current research gap, and provides theoretical reference for the further development of solar hydrogen production systems. [ABSTRACT FROM AUTHOR]

In order to solve the problem of randomness and volatility caused by the rapid growth of renewable energy (RE), energy storage systems (ESSs)—as an important means of regulation—can effectively improve the flexible regulation capacity of power systems utilizing a high proportion of RE. Most of the current ESS capacity configuration procedures are carried out based on the typical scenario method or time series production simulation. This method tends to determine the size of the ESS configuration through multiple trial simulations. Uncertainty of simulation prediction data can result in the existence of an excess capacity or lack of configured capacity. In addition, this method reflects the ESS demand under specific targets, but it fails to fully utilize RE generation characteristics. The configuration process lacks the mathematical mechanism of RE consumption, and the calculation process is too complicated. In view of the shortcomings of traditional ESS optimal configuration methods, this paper examines the mathematical mechanism of RE consumption and proposes the ESS optimal configuration analysis method based on "equal area criterion". First, the principle of RE consumption is analyzed and the "RE consumption characteristic curve" is proposed according to RE characteristics. In addition, a working principle diagram of RE consumption, including ESS, is constructed to visually show the consumption capacity of RE and the working position of ESS. Then, the ESS optimal configuration process, based on the "equal area criterion", is proposed to achieve an accurate match between ESS capacity demand and RE consumption targets. Finally, the power grid of a region in China is taken as an example. We prove that the proposed method can save 1.41 × 103 MWh of ESS capacity and provide a more "mathematical" and "convenient" systematic solution for RE consumption and ESS optimization compared to the production simulation method. [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]

This paper presents a hybrid model constituting dynamic smoothing technique and particle swarm optimization techniques to optimally size and control battery energy storage systems for wind energy ramp rate control and power system frequency performance enhancement. In today's modern power system, a high-proportion renewable energy grid is inevitable. This high-proportion renewable energy grid is a power system with abundant integration of renewable energy resources under the presence of energy storage tools. Energy storage tools are integrated into such power systems to balance the fluctuation and intermittence of renewable energy sources. One of the requirements in a high-proportion renewable energy grid is the fractional power balance between generation and load. One of the requirements set by power system regulators is the generation variation between two time points. A power producer is mandated to satisfy the ramp rate requirement set by the grid owner. This paper proposes dynamic smoothing techniques for initial size determination and particle swarm optimization based on optimal sizing and control of battery energy storage systems for ramp rate control and frequency regulation performance of a power system integrated with a large percentage of wind energy systems. Wind energy data taken from Zhangjiakou wind farm in China are used. The results indicate that the battery energy storage system improves the ramp rate characteristics of the wind farm. In addition, the virtual inertia capability of the battery energy storage system enabled the transient and steady-state frequency response of the test power system to improve significantly. [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]

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. Therefore, ensuring frequency stability and system security will emerge as pivotal challenges in the future development process. Created by combining a Li-ion battery and a supercapacitor, a hybrid energy storage system (HESS), which possesses robust power regulation capabilities and rapid response capabilities, holds promise for supporting the frequency stability of power systems. In this context, the assessment of the economic viability of HESSs providing multitype frequency response services becomes a critical factor in their deployment and promotion. In this paper, an economic analysis approach for a Li-ion battery–supercapacitor HESS towards a multitype frequency response is presented. First, a multitype frequency response-oriented operational mode for the HESS is designed, outlining the roles and functions of the Li-ion battery and the supercapacitor in delivering distinct services. Moreover, building upon the analysis of the power trajectory of Li-ion batteries, a lifetime model for the HESS is proposed based on the rain-flow counting method. Furthermore, considering the competitive landscape for the HESS in the frequency regulation ancillary service market, a full lifecycle economic assessment model is proposed. Finally, case studies on actual power system frequency data and PJM market data are performed to verify the effectiveness of the proposed method, and the simulation results confirm that the HESS exhibits robust performance and a competitive advantage in providing multitype frequency response services. Additionally, it demonstrates commendable economic benefits, establishing its potential as a valuable contributor to frequency response services. [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 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]

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]

In order to achieve the goal of carbon peaking and carbon neutralization, we must vigorously develop renewable energy. As one of the important renewable energy sources, the development and utilization of biomass energy has a high cost, and it is difficult to compete with traditional fossil energy in the early stage of development. Therefore, it is necessary for the government to escort the development of the biomass energy industry through legal means. First of all, on the basis of fully analyzing the development prospects of China's biomass energy, the article sorts out the laws and regulations related to biomass energy in China, and finds the shortcomings. Secondly, this paper draws on the institutional experience of the United States, Brazil, Sweden and other countries with relatively developed biomass energy industry, and provides suggestions for improvement from three aspects: law, policy and administrative system, with a view to supporting China's development of biomass energy industry and realizing the "dual carbon target" theoretically. [ABSTRACT FROM AUTHOR]

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

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

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

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

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

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

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]

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

With the development and refinement of the carbon emissions trading market, the relationship between the carbon market and the stock market has grown increasingly intertwined. This has led to a surge in research investigating the interactions between the carbon market and related sectors. This study examines the intensity and direction of spillover effects among ten industries associated with carbon emissions, spanning traditional and emerging energy sectors. Through static analysis, we find that spillover effects between industries in the carbon and stock markets are bidirectional and asymmetric. Dynamic analysis reveals that the carbon market, acting as the primary recipient of spillover effects, is notably influenced by traditional energy industries such as coal and oil, followed by photovoltaics, new energy vehicles, and others. The magnitude of these spillover effects is subject to fluctuations influenced by energy crises and events like the COVID-19 pandemic, while policy interventions can alter the overall trends in net spillover effects across various industries. [ABSTRACT FROM AUTHOR]

The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the "Three North" region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads. [ABSTRACT FROM AUTHOR]

This study aims to theoretically explore the technological systems of tropical island zero-carbon building (TIZCB) to scientifically understand the characteristics of these buildings in terms of energy utilization, energy conservation, energy production, and intelligent system mechanisms. The purpose is to address the inefficiencies and resource wastage caused by the traditional segmented approach to building energy consumption management. Thus, it seeks to achieve a comprehensive understanding and application of the zero-carbon building (ZCB) technology system. This article focuses on the demands for energy-efficient comfort and innovative industrialization in construction. Through an analysis of the characteristics of TIZCB and an explanation of their concepts, it establishes a theoretical framework for examining the system mechanisms of these buildings. Additionally, it delves into the energy utilization, energy conservation, energy production, and intelligent system from macro, meso, and micro perspectives. This approach results in the development of an implementation strategy for studying the mechanisms of energy usage, conservation, and intelligent production systems in TIZCB. The results show that: (1) this study delves into the theoretical underpinnings of TIZCB, emphasizing their evolution from a foundation of low-carbon and near-zero energy consumption. The primary goal is to achieve zero carbon emissions during building operation, with reliance on renewable energy sources. Design considerations prioritize adaptation to high-temperature and high-humidity conditions, integrating regional culture along with the utilization of new materials and technologies. (2) A comprehensive technical framework for TIZCB is proposed, encompassing energy utilization, conservation, production capacity, and intelligent systems. Drawing from systems theory, control theory, and synergy theory, the research employs a macro–meso–micro analytical framework, offering extensive theoretical support for the practical aspects of design and optimization. (3) The research implementation plan establishes parameterized models, unveiling the intricate relationships with building performance. It provides optimized intelligent system design parameters for economically viable zero-carbon operations. This study contributes theoretical and practical support for the sustainable development of TIZCB and aligns with the dual carbon strategy in China and the clean energy free trade zone construction in Hainan. [ABSTRACT FROM AUTHOR]

Sustainable energy sources, such as wind energy, are pivotal in driving our energy landscape towards a more environmentally conscious and responsible future. Wind power, as an exemplar of clean and renewable energy solutions, adeptly harnesses the kinetic energy of the wind to generate electricity. While wind energy significantly contributes to our sustainability objectives, the quality of the energy it produces is equally essential. A critical challenge in this context is harmonic distortion, which manifests as unwanted fluctuations in the frequency and amplitude of electrical waveforms. Effectively mitigating these distortions within wind energy systems is vital to maintaining the stability and reliability of power grids, guaranteeing that the electricity supplied adheres to high-quality standards. The objective of this study was to conduct a technological prospection focused on the contemporary scenario of genetic algorithm applications in addressing harmonic variations. This investigation unearthed a total of 634 relevant documents. The findings suggest that the utilization of genetic algorithms for enhancing energy quality is a relatively recent but promising field. The State Grid Corp of China emerged as the principal contributor, with ten noteworthy inventors identified. Remarkably, both China and the United States lead in patent filings. The insights gleaned from these documents underscore the potential for further exploration and the synergistic application of these techniques. These collaborative efforts have the potential to yield processes and devices that offer significant economic and environmental advantages for the energy industry, solidifying our commitment to a cleaner and more sustainable energy future. [ABSTRACT FROM AUTHOR]

In order to accelerate the construction of a clean, low-carbon, safe and efficient energy system, China set the provincial weight of responsibility for renewable energy power consumption and established a renewable energy power absorption guarantee mechanism in 2019. As a market incentive policy, it has enduring effect on the low-carbon transformation of the power industry. Firstly, the operation mechanism of the renewable energy consumption guarantee mechanism is analyzed. The general framework, core elements and supporting measures are clarified. Secondly, a stock-flow diagram is constructed based on the system dynamics method. It contains the green electricity market sub-module, the green-certificate market sub-module and the excess power absorption market sub-module. Finally, multiple scenarios are set up to simulate the impact of the green-certificate market and excess power absorption market improvements on the installed capacity and tariff of China's green power market. The renewable energy guarantee mechanism is an effective means to promote the consumption of green electricity in China. In addition, in the short term the cost of electricity for users has increased, but in the long term the cost of electricity shows a fluctuating downward trend. This study provides theoretical references for the formulation of clean and low-carbon policy objectives in the power industry and the optimization of market mechanisms. [ABSTRACT FROM AUTHOR]

The coal power policy has been influencing the development of China's coal power industry from the aspects of quantity control, technological progress, and market-oriented reform. Meanwhile, the strategic coal power policy of the mid- and long-term future is yet to be well-designed under the carbon peak and neutrality targets. Therefore, it is necessary to have a comprehensive overview of the coal power policy during the past and give targeted prospects for policy-makers. This paper discusses the policy effect on the development and technological progress of the coal power industry by giving an overview of the policy and reform processes of the coal power industry in China in the past 20 years. The results indicate that China's coal power policy has promoted the progress of coal power generation technology, optimized the coal power structure, accelerated the diversified investment in the power industry, and alleviated the overcapacity problem of coal power generation. After discussion, we conclude that: (1) It is necessary to gradually reduce the average generation hours of coal-fired power units while retaining high-quality coal-fired power units. (2) The renewable energy enterprises that adopt the support services of coal power enterprises should provide reasonable capacity compensation costs to create favorable conditions and achieve sustainable development for China's coal power industry. (3) To deploy coal power units combined with large-scale renewable energy in the western and northern regions will achieve efficient energy utilization. (4) Different strategies should be adopted for different coal power units, and the peak regulation potential of coal power units with low-capacity parameters should be explored. [ABSTRACT FROM AUTHOR]

Reasonable regional integrated energy planning is an important prerequisite for the construction of a Near-Zero Carbon Emission Demonstration District (NCEDD). An integrated energy planning scheme that is based on a three-step planning method with the objective of achieving an NCEDD is proposed in this paper. First, the planning objectives should be determined. After that, the planning strategies should be established. Finally, the planning approaches should be proposed according to the previously determined objectives and strategies. A case study considering the integrated energy planning of the Meishan International Near-Zero Carbon Emission Demonstration District (MINCEDD) is investigated to explain the planning method. In addition, the planning results, which are indicated as indexes, are explained, analyzed, and compared to the ones of other districts. The indexes include a proportion of renewable energy to primary energy (73% by 2030 and 108% by 2050), a proportion of renewable power to total power consumption (98% by 2030 and 111% by 2050), and CO2 emission reduction rates (70% by 2030 and 100% by 2050) and are more advanced than other districts in China. This planning scheme and method can provide a reference for the integrated energy planning of NCEDDs in developed urban areas. [ABSTRACT FROM AUTHOR]

For avoiding the occurrence of large-scale blackouts due to disconnected nodes in the power grid, a modified PageRank algorithm is proposed to identify key nodes by integrating the topological information and node type. The node betweenness index is first introduced based on complex network theory, which is modified to reflect the node topological information in the power grid. Then, according to the characteristics of different node types in the power grid, a modified PageRank algorithm is proposed to rapidly identify key nodes, which takes the generator nodes, load nodes, and contact nodes into account. IEEE 39-Bus system and IEEE 118-Bus system are used for the simulations. Simulation results showed that the network transmission efficiencies of the power grid are reduced from 64.23% to 5.62% and from 45.4% to 5.12% in the two simulation systems compared with other methods. The proposed identification algorithm improved the accuracy, and a provincial power grid simulation system in China is used to verify the feasibility and validity. The identified nodes are removed, which split the power grid according to importance index values. The proposed method in this paper is helpful to prevent the occurrence of cascading failure in the power system, and it can also be used to power systems with renewable energy sources and an AC/DC hybrid power grid. [ABSTRACT FROM AUTHOR]

There is a global move toward being "carbon neutral". Reducing the use of coal to generate power has become an inevitable choice for many countries when transforming their energy structures. Many countries have proposed phasing out coal. China is a major energy producing and consuming country and intends to reach a carbon peak by 2030 and become carbon neutral by 2060. China has repeatedly emphasized coal reduction, but has not explicitly proposed phasing out coal, due to the influence of local governments, coal-related enterprises, and the public. This paper explores whether China could declare a "coal phase-out", and the possible reasons for doing so, by constructing an evolutionary game model with two correlations. MATLAB was used to simulate the model results to determine the effectiveness of the fractal results of the model, and the entropy method was used to calculate the development level of "coal phase-out" related indicators in China and Germany. The results show that: (1) The government can phase out coal only when coal-related enterprises and the public can benefit from reducing coal production and consumption. In addition, these benefits are needed to ensure stable economic and social development without affecting people's daily lives; (2) The development level of relevant indicators of "coal retreat" in China is lower than that in Germany. Based on these results, it is concluded that it is difficult for China to announce a "coal phase-out" at present. Faced with this reality, China should improve the efficiency of coal use, install carbon capture and storage facilities, vigorously develop renewable energy and reduce the share of coal in the energy system. [ABSTRACT FROM AUTHOR]

Developing energy from renewable sources and modernizing the energy system are critical components of China's efforts to combat climate change. Policymakers and authorities have made significant attempts to bring them. However, one of the major impediments to China's energy revolution is financial limitations, which are inextricably linked to the country's economic growth. The present research paper intends to investigate the relationship between economic growth and sustainable financial development on the use of energy from renewable sources in both the short and long run in the context of China. To achieve this, the researchers have utilized the panel data consisting of 10 years from 2011 to 2020. When compared to cross-sectional and time-series data samples, the panel data model offers many benefits. For starters, the panel data includes information on the passage of time and the cross-sectional area. Another benefit of using panel-data models with a larger degree of freedom is that they provide more stable and reliable estimates across short periods across cross-sections. In the case of the short run, there is a positive relationship between economic and financial development and the use of energy from renewable sources in the context of all of China. While in the case of long-term effects, the results indicate the adverse impact of financial development on the use of energy from renewable sources in the western regions of China. These results were deduced using the causality test Granger proposed to determine the path of the causal relationship and the direction of the relationship between the variables. These results indicated that the relationship between economic and financial development in east China was unidirectional, and the nature of the underlying relationship was causal. Meanwhile, in east and west China, economic development in China as a whole has been unidirectionally increasing energy from renewable sources. Our empirical findings suggest many strategies for promoting the growth of energy from renewable sources. [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]

As fossil energy is increasingly depleted, promoting the integration of renewable energy into the grid and improving its utilization rate has become an irresistible development trend in China's power industry. However, the volatility of wind power increases the difficulty of economic dispatch in power systems. With the rising participation of wind power in the system, the complexity of traditional microgrid dynamic scheduling problems has increased, transforming into a dynamic economic scheduling problem for wind power thermal power hybrid microgrids. Starting from the concept and research significance of economic dispatch, this article analyzes the current research status of microgrid economic dispatch as well as the impact and influencing factors of wind energy grid connection on it. It summarizes the research performed by scholars in two aspects: scheduling models and solving algorithms in static dispatch, as well as how to deal with wind power randomness in dynamic dispatch and how to balance environmental protection while ensuring economic maximization. Finally, the existing problems in current research were summarized and future development directions were prospected. This research has important application prospects in improving the economy of the system and protecting the ecological environment. [ABSTRACT FROM AUTHOR]

Kitchen waste (KW) has high water content and organic matter, which has great potential for energy application, but how to treat it effectively has always been a difficult problem. In this study, the feasibility of transforming kitchen waste into hydrochar as a solid fuel to replace the primary energy by hydrothermal carbonization (HTC) is put forward. An experimental study of proportioned KW under HTC conditions (reaction temperature, residence time, liquid–solid ratio) is carried out by elemental analysis, industrial analysis, energy density calculation, and calorific value measurement. The results show that a proper extension of the residence time to 3.5 h at a liquid–solid ratio of 10 and a reaction temperature of 265 °C for the kitchen waste after HTC would result in a maximum calorific value of 30.933 MJ/Kg for the prepared hydrochar. The maximum ash content of hydrochar at a 265 °C reaction temperature is 3.94% < 10%, which is much lower than the standard of extra-low-ash coal, and the study shows that the hydrochar prepared from kitchen waste by HTC for combustion will greatly improve the combustion efficiency. The three types of kitchen waste under HTC conditions are compared with the three typical types of coal in China by the van Krevelen diagram. The results show that the combustion properties of hydrochar from kitchen waste prepared by the HTC method are better than those of lignite close to bituminous coal and can provide a theoretical basis for replacing primary energy in the future. Finally, by combining thermogravimetric analysis with mathematical modeling, it is calculated that the hydrochar of kitchen waste has a lower activation energy than those of other biomass, which can better facilitate the reaction. The experimental results further determine the feasibility of hydrochar as an alternative primary energy source and provide a theoretical basis for the future conversion of kitchen waste into hydrochar as a solid fuel through HTC. [ABSTRACT FROM AUTHOR]

In China, one of the most pressing issues that have to be addressed is how to best manage the link between energy consumption and sustainable development. Given this context, the goal of the current article is to investigate the effect of renewable energy consumption on sustainable development. Using provincial panel data from 2005 to 2020 and the province and year fixed effects model for an empirical study, we discover that renewable energy consumption has a favorable impact on sustainable development. Similarly, the findings suggest the influence of non-renewable energy consumption on sustainable development is weaker than that of renewable energy consumption. Moreover, the heterogeneity of the influence of renewable energy consumption and nonrenewable energy consumption on sustainable development in eastern, central, and western China has been demonstrated as well. Notably, the two-stage least squares approach and generalized system method of moments are utilized to examine the robustness of this issue, and the reliability and robustness of the conclusions presented in this study are also confirmed. To sum up, the results in this article provide more evidence that the use of energy is an important contributor to achieving sustainable development in China and realizing the target set for sustainable development in 2030. [ABSTRACT FROM AUTHOR]

Currently, quality air and renewable energy are main concerns in protecting the environment. Comparing willingness to pay for quality air and renewable energy is rare in the existing literature. However, the public faces these issues simultaneously. In addition, population mobility under China's household registration system, i.e., urban living experience, may affect the willingness to pay for environmental protection. Consequently, the difference between people's willingness to pay for quality air and renewable energy in China is discussed. Binary logistic regression is adopted to analyze the correlation factors based on data from the China General Social Survey. The results show that willingness to pay is influenced by environmental attitudes, awareness of energy use, government responsibilities, age, household income level, and trust. The effects of urban living experience on willingness to pay weakens as age decreases. Thus, improving environmental awareness and specialized knowledge remain important means of promoting willingness to pay. Our findings can help marketers and policy designers develop balanced or targeted measures when taking joint actions. [ABSTRACT FROM AUTHOR]

In response to the rising importance of the climate agenda, many countries have restructured their electricity markets to facilitate the utilization of renewable energy. China is an interesting case because it has expanded its utilization of wind and solar energy with unmatched speed. This review starts with an analysis of the 2002 reforms that uncoupled electricity production from transmission. The investigation covers the period leading up to the 2022 proposal, which aimed to build a nationally integrated electricity market. The analysis suggests that a careful alignment of incentives for key market players to produce and consume renewable energy is vital during the process of energy transition. The introduction of feed-in tariffs in 2009 for wind energy, which were subsequently extended to solar energy, stimulated a high growth in installed capacity. However, a high electricity curtailment rate resulted. Since 2018, the Chinese government has resorted to curtailment caps and renewable portfolio standards to increase the utilization of renewable electricity. After the announcement of the "dual carbon goals" in 2020, the Chinese government launched a series of reforms that aimed to nurture growth in the green electricity market and the formation of a nationally integrated electricity market. The removal of interregional trade barriers is a key element of China's current electricity market reforms and will be crucial to determining whether China can achieve its climate goals. [ABSTRACT FROM AUTHOR]

Over the years, energy is becoming an essential factor with an impact on social, economic, and environmental aspects. More than 2.5 billion people are connected to agriculture worldwide, so the importance of agricultural energy production has become increasingly important. This study provides a comprehensive review of renewable energy, environment, and farm publication trends. Two hundred articles from 1988 to 2022 were analyzed, with special attention devoted to the last three extreme years, using the Scopus database and the Bibliometrix tool for analysis and visualization. Research on this topic experienced significant developments after 2008, with many fluctuations being revealed. Historically, China and the USA were the most productive countries in agricultural energy production advancements. However, in the last three years, the research center's respective contributions have undergone major changes. China maintained its dominance, but the importance of the USA fell sharply, and new centers (India, Poland) appeared. Biogas is the most popular method which is used and searched in this area between 1988–2022 since it includes both sustainability and locality. However, between 2020–2022, the importance of the circular economy has been highlighted in the literature. Complex energy systems, dual use of land, and energy storage might be the most important challenges for future research. [ABSTRACT FROM AUTHOR]

Given the increase in population and energy demand worldwide, alternative methods have been adopted for the production of hydrogen as a clean energy source. This energy offers an alternative energy source due to its high energy content, and without emissions to the environment. In this bibliometric analysis of energy production using electrolysis and taking into account the different forms of energy production. In this analysis, it was possible to evaluate the research trends based on the literature in the Scopus database during the years 2011–2021. The results showed a growing interest in hydrogen production from electrolysis and other mechanisms, with China being the country with the highest number of publications and the United States TOP in citations. The trend shows that during the first four years of this study (2011–2014), the average number of publications was 74 articles per year, from 2015 to 2021 where the growth is an average of 209 articles, the journal that published the most on this topic is Applied Energy, followed by Energy, contributing with almost 33% in the research area. Lastly, the keyword analysis identified six important research points for future discussions, which we have termed clusters. The study concludes that new perspectives on clean hydrogen energy generation, environmental impacts, and social acceptance could contribute to the positive evolution of the hydrogen energy industry. [ABSTRACT FROM AUTHOR]

Renewable energy consumption is one of the most important factors in meeting the goal of "30 and 60" in China. However, the maintenance of the transmission section affects the amount of generation transfer, further affecting the consumption of renewable energy. Hence, in this study, a time-series renewable energy production simulation (REPS) is proposed in order to accurately predict the power generation in a simulated situation. According to the results of the REPS, the sensitivity of the different sections' maintenance can be calculated and determined. The appropriate maintenance strategies can be selected for different situations by comparing the consumption rate; as an example, we conducted a case study. The results show that the quota in the transmission section has higher sensitivity; a larger quota indicates a greater sensitivity to the consumption rate. The results also show that a larger quota is more suitable for maintenance in February or November, since the consumption rate is higher regardless of if it is in a single-transmission-section maintenance strategy or in a two-section simultaneous maintenance strategy. [ABSTRACT FROM AUTHOR]

Accurately measuring carbon dioxide (CO2) emissions is critical for effectively implementing carbon reduction policies, and China's increased investment in reducing CO2 emissions is expected to significantly impact the world. In this study, the potential of shallow learning for predicting CO2 emissions was explored. Data included CO2 emissions, renewable energy consumption, and the share of primary, secondary, and tertiary industries in China from 1965 to 2021. These time-series data were converted into labeled sample data using the sliding window method to facilitate a supervised learning model for CO2 emission prediction. Then, different shallow learning models with k-fold cross-validation were used to predict China's short-term CO2 emissions. Finally, optimal models were presented, and the important features were identified. The key findings were as follows. (1) The combined model of RF and LASSO performed best at predicting China's short-term CO2 emissions, followed by LASSO and SVR. The prediction performance of RF was very fragile to the window width. (2) The sliding window method is used to convert time series predictions into supervision learning problems, and historical data can be used to predict future carbon dioxide emissions. To ensure that the feature data are real, the model can predict CO2 emissions for up to six years ahead. (3) Cross-validation and grid search were critical for optimizing China's CO2 emissions prediction with small datasets. (4) By 2027, carbon dioxide emissions will continue to grow and reach 10.3 billion tons. It can be seen that the task of China to achieve its carbon peak on schedule is very heavy. The results indicate that an increase in renewable energy consumption and adjustments in industrial structure will continue to play an important role in curbing China's CO2 emissions. [ABSTRACT FROM AUTHOR]

The decarbonisation targets of the People's Republic of China are ambitious. Their achievement relies on the large-scale deployment of variable renewable energy sources (VRES), such as wind and solar. High penetration of VRES may lead to balancing problems on the grid, which can be compensated by increasing the shifting flexibility capacity of the system by integration with energy storage, e.g., by installing additional electricity storage. Pumped Hydro Storage (PHS) is the most diffused electricity storage technology at the global level and the only fully mature solution for long-term electricity storage. China already has the highest PHS capacity installed worldwide and plans to increase it strongly before 2030. The present study, based on the data from the "Pumped Storage Tracking Tool" of the International Hydropower Association, investigates the potential for technological improvement of the existing and future PHS fleet in China. The aims of adopting advanced PHS solutions allow China to better cope with the task of balancing the VRES production. The potential for adopting advanced PHS solutions is evaluated through five different intervention possibilities (here referred to as scenarios). These scenarios consider revamping part of the operational Pumped Storage Plant (PSP) fleet and redesigning future installations that are already planned. As a result, considering all the major technical and authorisation process constraints, 4.0% (5.2 GW) of the 132 GW fleet expected to be commissioned before 2035 could additionally adopt advanced PHS in a high-potential scenario. Meanwhile in the medium and low potential scenarios, the quota can reach 11.1% (14.6 GW) and 26.2% (34.5 GW), respectively. Furthermore, policy recommendations are elaborated to promote, facilitate, and support the adoption of these advanced PHS solutions. [ABSTRACT FROM AUTHOR]