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In the context of China's new power system, various regions have implemented policies mandating the integration of new energy sources with energy storage, while also introducing subsidies to alleviate project cost pressures. Currently, there is a lack of subsidy analysis for photovoltaic energy storage integration projects. In order to systematically assess the economic viability of photovoltaic energy storage integration projects after considering energy storage subsidies, this paper reviews relevant policies in the Chinese photovoltaic energy storage market. It analyzes the cost and revenue composition of photovoltaic energy storage integration projects, and constructs a system dynamics model for the levelized cost of electricity (LCOE) of such projects. Taking a specific photovoltaic energy storage project as an example, this paper measures the levelized cost of electricity and the investment return rate under different energy storage scenarios. Combining energy storage allocation ratios and internal rate of return indicators, this paper analyzes the net present value of photovoltaic energy storage integration projects under different subsidy standards. The results indicate that, while the current energy storage subsidy policies positively stimulate photovoltaic energy storage integration projects, they exhibit a limited capacity to cover energy storage investment costs, thereby failing to incentivize capital market participation in the construction of such projects. Rational allocation of energy storage capacity and optimization of corresponding subsidy policies are crucial prerequisites for enhancing the economic viability and widespread adoption of photovoltaic energy storage integration projects. This study not only aids in investment decision making for photovoltaic power stations but also contributes to the formulation of energy storage subsidy policies. [ABSTRACT FROM AUTHOR]

Despite the pressure of carbon emissions and clean energy, coal remains the economic backbone of many developing countries due to its abundant resources and widespread distribution. The stable supply of coal is also vital for the global economy and remains irreplaceable in the future global energy structure. China has been a major contributor to annual coal output, accounting for nearly 50% worldwide since 2014. However, despite implementing intelligent coal mining technology, China's coal mining industry still employs over 1.5 million underground miners, posing significant safety risks associated with underground mining operations. Therefore, the introduction of coal mining robots in underground mines is an urgently needed scientific and technological solution for upgrading China's and even the world's coal energy industry. The working face needs a shearer, hydraulic support, a scraper conveyor, and other equipment for coordination. The deep integration of intelligent technology with factors such as "humans, machines, the environment, and management" in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for robot technology systems in coal mining, including single robots, robotized equipment, robot crowds, and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and the cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve the customized research and development and standardized production of various types of robot. A specific analysis is conducted on the research progress of common key technologies such as the explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mining robot research and development is proposed. Robotic mining systems should be promoted to enhance the overall intelligence level and efficiency of mining equipment. To develop human–machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots, the digital twinning of the entire mine robot system should be accelerated; the normalized operation level of coal mine robots should be improved; research on coal mining robots, shield support robots, and transportation robots should be performed; intelligence should be achieved in fully mechanized mining faces; and equipment shield support for fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization is summarized in this paper, and the technical and engineering feasibility of the coal mining machine population is verified. [ABSTRACT FROM AUTHOR]

Due to the serious problems with energy efficiency, carbon emissions, and thermal comfort of rural residences in northern China, an optimization of active and passive heating technologies for rural residences is necessary. In this paper, an optimization for rural residences in northern China is conducted with four objectives: the whole life cycle carbon emission; the annual energy consumption through heating, ventilation, and air conditioning systems; the annual cost; and thermal comfort. In addition, the optimization model with active–passive heating technology synergy is resolved by NSGA-II genetic algorithm. The active and passive design variables, including the type of air source heat pump, orientation, the type and thickness of envelope insulation, the layer of window glass, the window-to-wall area ratio, as well as sunspace parameters are preferred to obtain the optimal solution. The results indicate that the optimal solution obtained by the ideal point method gives the most outstanding performance. Compared with the prototype, the optimized carbon emissions in severe cold and cold regions decreased by 56.1% and 54.6%, respectively. The annual energy consumption decreased by 59.7% and 62.2%. Finally, the roof insulation thickness is the most sensitive design variable in Pareto-optimal solution sets. This paper offers significant guidance in the application of the optimization method of active–passive technology synergy to the energy-saving design of buildings. [ABSTRACT FROM AUTHOR]

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]

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants' thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants' comfort. [ABSTRACT FROM AUTHOR]

Photovoltaic power generation prediction constitutes a significant research area within the realm of power system artificial intelligence. Accurate prediction of future photovoltaic output is imperative for the optimal dispatchment and secure operation of the power grid. This study introduces a photovoltaic prediction model, termed ICEEMDAN-Bagging-XGBoost, aimed at enhancing the accuracy of photovoltaic power generation predictions. In this paper, the original photovoltaic power data initially undergo decomposition utilizing the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm, with each intrinsic mode function (IMF) derived from this decomposition subsequently reconstructed into high-frequency, medium-frequency, and low-frequency components. Targeting the high-frequency and medium-frequency components of photovoltaic power, a limiting gradient boosting tree (XGBoost) is employed as the foundational learner in the Bagging parallel ensemble learning method, with the incorporation of a sparrow search algorithm (SSA) to refine the hyperparameters of XGBoost, thereby facilitating more nuanced tracking of the changes in the photovoltaic power's high-frequency and medium-frequency components. Regarding the low-frequency components, XGBoost-Linear is utilized to enable rapid and precise prediction. In contrast with the conventional superposition reconstruction approach, this study employs XGBoost for the reconstruction of the prediction output's high-frequency, intermediate-frequency, and low-frequency components. Ultimately, the efficacy of the proposed methodology is substantiated by the empirical operation data from a photovoltaic power station in Hebei Province, China. Relative to integrated and traditional single models, this paper's model exhibits a markedly enhanced prediction accuracy, thereby offering greater applicational value in scenarios involving short-term photovoltaic power prediction. [ABSTRACT FROM AUTHOR]

In order to achieve the ambitious goal of "carbon neutrality", countries around the world are striving to develop clean energy. Against this background, this paper takes China and Italy as representatives of developing and developed countries to summarize the energy structure composition and development overview of the two countries. The paper analyzes the serious challenges facing the future energy development of both countries and investigates the possibilities of energy cooperation between the two countries, taking into account their respective advantages in energy development. By comparing the policies issued by the two governments to encourage clean energy development, this paper analyzes the severe challenges faced by the two countries' energy development in the future and combines their respective energy development advantages to look forward to the possibility of energy cooperation between the two countries in the future. This lays the foundation for China and Italy to build an "Energy Road" after the "Silk Road". [ABSTRACT FROM AUTHOR]

Since the power generation structures and load characteristics in each province in China are quite different, the distribution of peak regulating resources and demands are extremely imbalance. Restricted by a low power marketization degree, peak regulating resource shortages, and transmission channel blocks, the efficient utilization of new energy is facing greater pressures. In order to improve the mutual aid in regional power grids and to obtain more precise simulation results, this paper proposes a two-layer optimization dispatching model, considering the mutual aid of peak regulation resources between each province. It determines the optimal startup mode and the units' power output in each province and obtains the power output arrangements for all the units and the technical and economic indicators. The model and the solution method are original and innovative. And it effectively solved the unequal distribution problem between the peak regulating demands and resources of each provincial power grid. Finally, taking an actual regional power grid in China as an example, the simulation results show that the proposed model can significantly improve the utilization rate of new energy, which verifies the effectiveness and feasibility of the proposed model and methods presented in this paper. [ABSTRACT FROM AUTHOR]

A reasonable allocation of production schedules and savings in overall electricity costs are crucial for large manufacturing conglomerates. In this study, we develop an optimization model of off-site industrial production scheduling to address the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's power supply, and the difficulty in promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and variations in electricity prices in different places to optimize the scheduling of industrial production in various locations. The model is embedded with two sub-models, i.e., an electricity price prediction model and a distributed photovoltaic power cost model to complete the model parameters, in which the electricity price prediction model utilizes a Long Short-Term Memory (LSTM) neural network. Then, the particle swarm optimization algorithm is used to solve the optimization model. Finally, the production data of two off-site pharmaceutical factories belonging to the same large group of enterprises are substituted into the model for example analysis, and it is concluded that the optimization model can significantly reduce the electricity consumption costs of the enterprises by about 7.9%. This verifies the effectiveness of the optimization model established in this paper in reducing the cost of electricity consumption on the demand side. [ABSTRACT FROM AUTHOR]

Ensuring optimal building performance is vital for enhancing student activity comfort and fostering energy-saving initiatives toward low-carbon objectives. This paper focuses on university student centers in China, aiming to diminish building energy consumption while enhancing indoor thermal comfort. Parametric modeling of typical cases is executed using the Grasshopper 1.0.0007 software package, and the simulation of building energy consumption and indoor thermal comfort relies on the Ladybug and Honeybee plug-in. Employing a multi-objective optimization design method and the Octopus multi-objective optimization algorithm, this study integrates numerical simulations and on-site surveys to analyze how factors like building form, orientation, envelope structure, and others impact the indoor and outdoor environment. A comprehensive optimization design approach is implemented for the building's exterior components, including the walls, windows, roof, and shading system. After conducting a comparative analysis of the annual comprehensive energy consumption and indoor thermal comfort before and after the optimization plan, it is determined that implementing these measures reduces the annual comprehensive energy consumption of the building under study by 58.8% and extends the duration of indoor thermal comfort by 53.0%. This study presents a practical optimization design methodology for university student center architecture in China, aiding architects in decision making and advocating for energy-efficient building designs. [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]

This paper takes a low-energy building in Changchun, China, as an object to test and study the characteristics of two heating modes, AC/DC (Alternative current/Direct current) switching and AC/DC synthesis, from the perspectives of temperature change, irradiation intensity, power generation, electricity consumption, etc. Firstly, the experimental research was conducted under two heating cable modes by establishing mathematical models and a test rig, and it was found that the photoelectric conversion efficiency on sunny, cloudy, and overcast days was 18%, 14.5%, and 12%, respectively. A simulation model was established by TRNSYS to run an ultra-low-energy building throughout the year. It was found that the highest and lowest monthly power generation occurred in February and July, respectively. The annual power generation of the system was 6614 kWh, and the heating season power generation was 3293.42 kWh. In the current research, the DC electricity consumption was slightly higher than the AC electricity consumption. Under conditions of similar radiation intensity and power generation, the indoor temperature of the AC/DC synthesis cable heating mode were 1.38% higher than the AC/DC switching heating able mode, and the electricity consumption were 10.9% and 4.76% higher, respectively, than those of the AC switching heating cable mode. This is of great significance for clean-energy heating, energy savings, and emissions reduction in northern China. [ABSTRACT FROM AUTHOR]

Amid China's pursuit of a green and low-carbon transition, corporate social responsibility (CSR) is facing new challenges. Our research delves into the influencing factors and mechanisms for CSR reputation under green and low-carbon transition and provides practical enlightenment for enterprises to achieve sustainable development. This paper constructs a comprehensive index system of CSR from five dimensions (innovation, coordination, sustainability, openness, and sharing), and CSR reputation of China's A-share listed companies is comprehensively estimated by using an entropy method and data from 2013 to 2021. Then, from the perspective of external supervision and internal governance, we discuss the influence factors of CSR reputation, with an emphasis on the impact of public environmental concerns. Finally, the realization mechanism of CSR is further revealed. It is found that public environmental concern and the expansion of the enterprise scale boost the enhancement of CSR reputation. However, a higher proportion of female managers tends to hinder CSR reputation. Furthermore, public environmental concern plays a more prominent role in improving CSR reputation of non-state-owned and eastern enterprises. Additionally, public environmental concern significantly enhances CSR reputation through green technology innovation and executive environmental awareness. This research provides valuable insights for improving CSR reputation and optimizing regulatory compliance and governance practices. [ABSTRACT FROM AUTHOR]

Heating buildings with solar energy is challenged by the seasonal mismatch between solar availability and heating demand. Thermochemical energy storage is a promising technology to overcome this challenge because of its high energy density. In building applications, space requirement is also an important consideration. Therefore, both the storage space and collector areas are important considerations, with only the latter often being neglected in previous studies. This paper proposes a novel two-stage thermochemical heat pump heating system based on the working pair of NaOH/H2O. We demonstrate that this system can work with a concentration difference (70% wt–30% wt) for the climate in hot summer and cold winter regions in China. The energy storage density based on the discharged solution is 363 kWh/m3. With this solar-driven thermochemical heat pump heating system, 35.13 m2 of collectors and 10.48 tons of 70% wt NaOH solution are sufficient to complete a full charge–discharge cycle and meet the heating demand of a single-family house (winter space heating + DHW: 9370 kWh, summer DHW: 2280 kWh). The theoretical maximum storage for solution (discharged + water tank) is 32.47 m3. Compared with the sensible seasonal storage alternative, the collector area is reduced by 12.5% and the storage space is reduced by 59%, with a possible further reduction through optimization. With the potential to be further optimized for space saving, the two-stage solar–NaOH heat pump heating system is an energy-efficient and space-efficient heating system for buildings in the hot summer and cold winter regions of China. [ABSTRACT FROM AUTHOR]

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [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]

In recent years, atmospheric composite pollution has become increasingly serious, and accelerating VOC governance has become the focus of and difficulty in atmospheric governance. Volatile organic compounds (VOCs) come from a wide range of sources, and industrial sources are the main source of anthropogenic VOC emissions in China. Chemicals, oil refining, and solvents are three typical VOC-emitting industries, and their control is an important part of accelerating and optimizing VOC governance. It can be controlled by source control, process control, and pipe end treatment; among these, pipe end treatment is divided into recovery technology and destruction technology. In pipeline end treatment, with the key materials of adsorption, absorption, catalytic oxidation, and catalytic combustion, the research and development of adsorbents, absorbents and catalysts has become a hot spot in recent years. This paper summarizes the chemical materials used in typical VOC pipe end-treatment technology (including adsorbents used in the adsorption method, absorbents used in the adsorption method, and catalysts used in the catalytic oxidation and catalytic combustion methods), summarizes the advantages and disadvantages of various materials and their application range, and looks forward to the direction of future developments. [ABSTRACT FROM AUTHOR]

This paper investigates whether and how tax and fee support policies at the firm level in China influence the total factor energy productivity of enterprises. Using panel data from Chinese public trading companies for the period 2004–2020, this study employs a panel model for estimation. The findings suggest that tax rebates contribute to the improvement of the total factor energy productivity of enterprises. Specifically, a 1% increase in tax refunds leads to a growth of approximately 0.008% in total factor energy productivity. Robustness tests and endogeneity checks confirm the validity of the results. Heterogeneity analysis reveals that tax rebates have a significant impact on state-owned enterprises, small- and medium-sized enterprises, and non-technology firms in terms of enhancing their total factor energy productivity. Mechanism analysis indicates that tax rebates facilitate firms in alleviating financing constraints and enhancing their innovation capabilities, thereby improving energy efficiency. The research findings of this paper provide empirical support for optimizing policy supply, improving energy usage efficiency, and promoting the development of a globally sustainable economy. [ABSTRACT FROM AUTHOR]

The highlighted energy consumption of Internet data center (IDC) in China has become a pressing issue with the implementation of the Chinese dual carbon strategic goal. This paper provides a comprehensive review of cooling technologies for IDC, including air cooling, free cooling, liquid cooling, thermal energy storage cooling and building envelope. Firstly, the environmental requirements for the computer room and the main energy consumption items for IDC are analyzed. The evaluation indicators and government policies for promoting green IDC are also summarized. Next, the traditional cooling technology is compared to four new cooling technologies to find effective methods to maximize energy efficiency in IDC. The results show that traditional cooling consumes a significant amount of energy and has low energy efficiency. The application of free cooling can greatly improve the energy efficiency of IDC, but its actual implementation is highly dependent on geographical and climatic conditions. Liquid cooling, on the other hand, has higher energy efficiency and lower PUE compared to other cooling technologies, especially for high heat density servers. However, it is not yet mature and its engineering application is not widespread. In addition, thermal energy storage (TES) based cooling offers higher energy efficiency but must be coupled with other cooling technologies. Energy savings can also be achieved through building envelope improvements. Considering the investment and recovery period for IDC, it is essential to seek efficient cooling solutions that are suitable for IDC and take into account factors such as IDC scale, climate conditions, maintenance requirements, etc. This paper serves as a reference for the construction and development of green IDC in China. [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]

In pursuit of China's goals for carbon peak and carbon neutrality, wind turbines are continually evolving to achieve a lower levelized cost of energy. The primary technological focus in the wind power industry is on large-scale, lightweight designs for entire turbines to enhance cost competitiveness. However, this advancement has led to an increased risk of blade fractures under extreme operating conditions. This paper addresses this challenging issue by using geometrically exact beam theory to develop a nonlinear simulation model for long, flexible blades. The model accounts for sudden changes in blade properties at the moment of failure, covering both the extensive motions and deformations of the fractured blade. The validation of the proposed model is carried out by comparing the results from power production cases with bladed simulations and further validating the simulations of blade fracture load cases against measurement data. The methodologies and findings presented in this study offer valuable insights for diagnosing faults in wind turbines. [ABSTRACT FROM AUTHOR]

This paper presents an empirical investigation into the effects of energy transition and digitization on carbon dioxide emissions, serving as a proxy for environmental sustainability, across 28 Chinese provinces from 2000 to 2021. Utilizing both static and dynamic regression analyses, the study reveals a significant driving effect of the energy transition on environmental sustainability, primarily through a reduction in carbon dioxide emissions. Notably, this influence is more pronounced in the eastern region of China, followed by the central and western regions, indicating regional heterogeneity in the impact of the energy transition. Furthermore, digitization is found to have a substantial moderating effect, enhancing energy conservation and emission reductions. As digitization progresses, its capability to diminish the impact of energy transitions on carbon dioxide emissions becomes more apparent, particularly in the eastern region, while this effect is less marked in central and western China. The study also delves into the nonlinear relationship between energy transitions and carbon dioxide emissions, discovering that increased levels of digitization can exacerbate the negative effects of energy transitions on emissions. These findings offer valuable insights into the dynamics of energy transition and digitalization, highlighting their crucial roles in shaping environmental sustainability in China. [ABSTRACT FROM AUTHOR]

As the global demand for renewable energy continues to rise, biogas production has emerged as a promising solution for sustainable energy generation. This review article presents the advantages of biogas technologies (mainly agricultural, based on waste of animal and plant origin) and extensively discusses the main principles of biogas production in the anaerobic digestion (AD). In this respect, the main parameters of the process, which require monitoring and decisive for its efficiency are described, therefore: temperature, pH value, retention time and organic loading rate (OLR). The principles of substrate selection are also discussed and the necessity and advantages of the use of organic waste according to the model of a circular economy and the concept of sustainable development, are indicated. It is emphasized that according to the new European regulations, the crops classified as food cannot be considered energy crops. The part on biogas production is summarised with an explanation of the necessity to treat and purify biogas. Biogas purification is important from the point of view of the efficiency of its conversion into electricity. A special place in this paper is devoted to the design, construction, functioning and operation of biogas plants, based on both scientific and practical aspects. In conclusion of this chapter, the economic aspects and profitability of operating biogas plants are discussed. Cost and benefit analyses are the major tool used for the systematic evaluation of the financial costs and potential benefits associated with the operation of biogas plants. The important fact is that the return on investment can be achieved within a few years, provided the activities are well-planned and executed. In addition to the fundamental issues of the operation of biogas plants, this article presents the global situation regarding the development of biogas plants, discussing in detail the specific needs and limitations on different continents. It is a interesting and extensive part of this article. The global agricultural biogas market is at very different levels of development. Most such installations are located in Asia and Europe. China has the highest number of biogas plants, with more than 100,000 biogas plants, followed by Germany with over 10,000 plants. In addition to the 100,000 biogas plants, China also has a large number of household biogas units, which gives a total of approx. 40 million operating units. The article concludes with a discussion of opportunities and barriers to the development of biogas plants, pointing to: financial issues, access to feedstock, political regulations, public awareness and the geopolitical situation. The most frequently cited reasons for investment failure include economic problems, lack of professional knowledge. [ABSTRACT FROM AUTHOR]

The complexity and strong spatial and temporal characteristics of municipal solid waste (MSW) have made resource utilization a major challenge in establishing the life-cycle model of MSW. Based on the planning of the domestic "dual-carbon" target and the current status of the structural transformation of resource utilization, this paper summarizes the physicochemical properties of MSW in China by component, species, and region. The aim is to identify the physicochemical components of MSW in different regions of China, drawing on the research findings of various scholars. A total of 159 sets of MSW data were collected, including 90 sets of physical composition and 69 sets of elemental composition. These data were used to calculate the calorific value of MSW and determine the energy-recovery and power-generation potentials before and after MSW classification. The analysis estimates the volume of MSW requiring removal in different regions of China in 2021 and assesses the effectiveness of the energy-recovery potential (ERP) and power-generation potential (PGP) before and after MSW classification in these regions. The aim is to offer insightful guidance and recommendations for municipal waste-treatment strategies tailored to the diverse regions of China. [ABSTRACT FROM AUTHOR]

The unconventional tight oil and gas resources in the Xinzhao East belt of the Hangjinqi Prospect area in the Ordos Basin of China are abundant. However, the reservoir's internal storage space is complex, and the microscopic pore throat structural features are not well recognized, which has led to some trouble in the deployment of oil and gas exploration. To reveal the microscopic characteristics of the dense sandstone gas layer in the first member of the Lower Stone Box Formation of the D-well Zone in the Xinzhao East belt of the Hangjinqi Prospect area, a three-dimensional space digital core was built, and the stored set spatial data were extracted, based on rock sheet and coring data and X-CT scanning technology. Quartz grain size was segmented and analyzed based on an adaptive approach. The microscopic characteristics of the gas layer in the studied section and the factors influencing its development were studied, combining the use of a field emission scanning electron microscope, helium porosimeter, and gas permeability meter. We found that in the studied section, the porosity is relatively high, the pore throat size is large, and the pore permeability correlation is good. The reservoir space, which consists of intergranular pores, intragranular pores, and microcracks at the grain edges in the study area, is characterized by a complex distribution pattern. Within the gas layer, isolated pores are connected by microcracks to form a network of reservoir spaces, which increases the pore throat size, enhances the connectivity of the pore throat, and makes the microscopic characteristics of the reservoir space better. The first member of the Lower Stone Box Formation could be an advantageous reservoir. Hole–throat connectivity is poor because of the gas layer having underdeveloped primary pores, the blockage of pores by unstable minerals (kaolinite, etc.), and poorly connected pore throats based on insoluble mud cementation. The high content of quartz brittle minerals and the development of natural microcracks within the gas formation are favorable conditions for fracking development. The quartz grain size within the gas layer is positively correlated with the pore throat size, which suggests that the quartz grain size somewhat influences the microscopic characteristics of the reservoir space. This comprehensive study shows that the methodology of the study is more advantageous than traditional methods in the fine and three-dimensional spatial characterization of the microstructure of dense sandstone reservoirs. The research results of this paper have certain guiding significance for further reservoir evaluation and advantageous reservoir prediction in the Hangjinqi Prospect area in the Ordos Basin. We also provide the basis for the subsequent efficient development of the gas reservoir. [ABSTRACT FROM AUTHOR]

Siliceous minerals of the Dengying Formation in the Gaoshiti–Moxi area in the central Sichuan Basin exhibit four types of quartz crystals (cryptocrystalline quartz, chalcedony, microcrystalline quartz, and megacrystalline quartz) and three structural types: cryptocrystalline, microcrystalline, and mosaic (laminated mosaic, window-hole interrupted mosaic, and arc-laminated mosaic). Siliceous minerals have a great influence on the storage performance of the reservoirs in the Dengying Formation. According to the petrophysical parameters of the Dengying Formation and porosity intersection diagrams, the siliceous dolomite and the reservoirs have low impedance characteristics, which makes it difficult to distinguish between them and leads to difficulties in the characterization and prediction of the reservoirs. The transverse wave velocity is favorable for reservoir characterization. Currently, the main method used to estimate the transverse wave velocity is petrophysical modeling, which establishes a relationship between the elastic and physical parameters of the reservoir. In this paper, the siliceous minerals in the dolomite in the study area are regarded as solid inclusions, and the calculation method of the rock matrix modulus is improved by using solid replacement. Then, an improved petrophysical model is constructed by combining the KT (Kuster–Toksöz) model, the DEM (Discrete Element Method) model, the Gassmann equation, and the Wood equation. The transverse wave velocity is estimated using the improved model under the constraint of the longitudinal wave velocity. The shapes of the transverse wave velocity curves obtained by the improved model and the deviations from the measured velocities are significantly better than those of the Xu–Payne model and other models. The results show that the improved model can effectively estimate the transverse wave velocity of the reservoir in this area, which provides a basis for future reservoir predictions in this area. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of typhoon weather has posed a significant threat to the stable operation of the distribution network in the southeastern coastal areas of China. Ensuring the safety of distribution lines is crucial for the normal functioning of the distribution network. Therefore, this paper proposes a risk assessment method for distribution lines in typhoon weather. Firstly, the risk assessment system for distribution lines is constructed by considering three perspectives: line structure, line state, and social economic factors. Secondly, the weight of each evaluation index is calculated using the analytic hierarchy process and CRITIC weight method. The cooperative game method is then employed to combine the calculation results, and the results are further optimized using variable weight theory. Finally, a cloud model-based risk assessment model for distribution lines is established. The analysis and calculation of distribution network data in a specific area indicate that the risk assessment level, which takes into account social and economic factors, is more accurate compared to other methods discussed in this paper. It is observed that the multi-model approach yields higher accuracy than the single-model approach. Therefore, the proposed method holds significant reference value for evaluating the risk level of distribution lines. [ABSTRACT FROM AUTHOR]

Since their inception with Bitcoin in the late 2000s, cryptocurrencies have grown exponentially, reshaping traditional financial paradigms. This transformative journey, while innovative, brings forth pressing concerns about their energy consumption and carbon footprint. While many studies tend to zoom in on Bitcoin, this paper broadens the perspective by evaluating energy consumption across various cryptocurrencies. We analyze nine cryptocurrency projects, chosen for their market value, technology, and data availability. These span a spectrum from pioneering to emerging digital coins, offering a holistic view of the crypto realm. To contextualize, we juxtapose the energy usage of these digital currencies with traditional payment means like Visa and Mastercard. Our analysis shows vast differences in energy use among cryptocurrencies, largely tied to their consensus algorithms. Notably, while Bitcoin stands out as highly energy-intensive, several newer digital currencies have energy footprints mirroring those of conventional payment methods. Additionally, CO2 emissions estimation presents challenges due to variances in miner locations and regional energy sources, with potential higher emissions if concentrated in carbon-intensive regions like China. Nonetheless, the silver lining emerges as many cryptocurrencies, especially those beyond Bitcoin, register considerably lower CO2 emissions. By moving the lens beyond Bitcoin, this paper paints a more nuanced picture of the environmental ramifications of the crypto world. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation is booming in rural areas, not only to meet the energy needs of local farmers but also to provide additional power to urban areas. Existing methods for estimating the spatial distribution of PV power generation potential either have low accuracy and rely on manual experience or are too costly to be applied in rural areas. In this paper, we discuss three aspects, namely, geographic potential, physical potential, and technical potential, and propose a large-scale and efficient PV potential estimation system applicable to rural rooftops in China. Combined with high-definition map images, we proposed an improved SegNeXt deep learning network to extract roof images. Using the national standard Design Code for Photovoltaic Power Plants (GB50797-2012) and the Bass model, computational results were derived. The average pixel accuracy of the improved SegNeXt was about 96%, which well solved the original problems of insufficient finely extracted edges, poor adhesion, and poor generalization ability and can cope with different types of buildings. Leizhou City has a geographic potential of 1500 kWh/m2, a physical potential of 25,186,181.7 m2, and a technological potential of 442.4 MW. For this paper, we innovatively used the Bass Demand Diffusion Model to estimate the installed capacity over the next 35 years and combined the Commodity Diffusion Model with the installed capacity, which achieved a good result and conformed to the dual-carbon "3060" plan for the future of China. [ABSTRACT FROM AUTHOR]

With the goal of achieving "carbon peak in 2030 and carbon neutrality in 2060", as clearly proposed by China, the transportation sector will face long–term pressure on carbon emissions, and the application of hydrogen fuel cell vehicles will usher in a rapid growth period. However, true "zero carbon" emissions cannot be separated from "green hydrogen". Therefore, it is of practical significance to explore the feasibility of renewable energy hydrogen production in the context of hydrogen refueling stations, especially photovoltaic hydrogen production, which is applied to hydrogen refueling stations (hereinafter referred to "photovoltaic hydrogen refueling stations"). This paper takes a hydrogen refueling station in Shanghai with a supply capacity of 500 kg/day as the research object. Based on a characteristic analysis of the hydrogen demand of the hydrogen refueling station throughout the day, this paper studies and analyzes the system configuration, operation strategy, environmental effects, and economics of the photovoltaic hydrogen refueling station. It is estimated that when the hydrogen price is no less than 6.23 USD, the photovoltaic hydrogen refueling station has good economic benefits. Additionally, compared with the conventional hydrogen refueling station, it can reduce carbon emissions by approximately 1237.28 tons per year, with good environmental benefits. [ABSTRACT FROM AUTHOR]

Coal is the main energy source in China. As flat and shallow coal seams are being depleted, adverse coal seams such as inclined and steeply inclined coal seams account for larger proportion of seams that are mined. For these coal seams, instability such as slip and tipping of mining equipment due to the large inclination is a significant challenge for the productive operation of intelligent or smart mines. Therefore, this paper serves to provide some insights into improving their stability. In this paper, research on the anti-tipping and anti-slip technology of shields is carried out on an intelligent working face with a large dip angle. A mechanical model of "support-surrounding rock" was established. Through the analysis of the influence of the self-weight of the support on its stability and through theoretical analysis and field practice, it was found that the critical tipping angle of the support in the free state is 27.8, the critical slip angle is 16, and the support is more prone to slip in the free state; the shields in the middle of the working face are the key area for stability control. Suitable technical measures are taken to ensure the stability of the supports, which provides the management and practical basis for safe and efficient mining in the intelligent working face with a large dip angle. [ABSTRACT FROM AUTHOR]

New-energy vehicles (NEV), particularly electric vehicles, are globally popular with political and financial support from governments, which aim at reducing energy consumption and environmental pollution in the transportation sector. This paper designs a matrix model which identifies the factors influencing the decision-making process on purchasing NEVs, and applies the model on a Chinese case to investigate the impact of influencing factors on Chinese consumers' purchase behavior to NEVs. The influencing factors are divided into five groups: economic, political, social, technological and environmental. Through a detailed questionnaire survey of 526 consumers in China, this paper conducts a correlation and difference analysis between these consumers' status and the influencing factors on the purchase decision-making of NEVs through SPSS software. The results indicate that economic, technological and political factors have a strong influence on purchase behavior, while social and environmental factors have a weaker influence. Additional principal component analysis on influencing factors' preference reveals that consumers' preferences have two tendencies: practicability or appearance, with the former is attracting far more attention. Rather than practicability or appearance, consumers care more about economic and political factors. According to these results, this paper suggests several policy implications on enhancing the consumers' willingness to purchase NEVs. [ABSTRACT FROM AUTHOR]

The launch of the national carbon emissions trading (CET) market has resulted in a closer relationship between China's CET market and its electricity market, making it easy for risks to transfer between markets. This paper utilizes data from China's CET market and electric power companies between 2017 and 2023 to construct the spillover index model of Diebold and Yilmaz, the frequency-domain spillover approach developed by Barun'ik and Křehl'ik, and a minimum spanning tree model. The comparison is made before and after the launch of the national CET market. Subsequently, this paper examines the market spillover effects, as well as the static and dynamic properties of network structures, considering both the time domain and frequency-domain perspectives. The research findings suggest the following: (1) There is a strong risk spillover effect between China's CET market and the stock prices of electric power companies; (2) There is asymmetry in the paired spillover effects between carbon trading pilot markets and the national CET market, and differences exist in the impact of risk spillovers from power companies between the two; (3) The results of the MST model indicate that the risk contagion efficiency is higher in the regional CET pilot stage compared to the national CET market launch stage, with significant changes occurring in key nodes before and after the launch of the national CET market; (4) Both the dynamic spillover index and the standardized tree length results demonstrate that crisis events can worsen the risk contagion between markets. Besides offering a theoretical foundation and empirical evidence for the development of China's CET and electricity markets, the findings of this paper can provide recommendations for financial market participants as well. [ABSTRACT FROM AUTHOR]

Solar-heating technology is a promising solution to help China achieve the "3060 double carbon" target as soon as possible. Seasonal thermal storage (STS) can effectively solve the mismatch problem of solar-heating systems between the supply and demand of thermal energy. Due to the instability of solar radiation resources and the heat demand, it is necessary to analyze the dynamic response characteristics and operation strategy optimization of the system in different operation stages. Yet, related studies are still scarce. The aim of this paper is to study the switching mechanism of the operation modes and the transitive relation of the system energy in different operation stages based on a pilot solar-heating system with STS in Huangdicheng, northern China. The impacts of different heating strategies on the system performance were also analyzed with a dynamic simulated method in TRNSYS. The results showed that the solar fraction of the system reached 89.4% in the third year, which was 3.6% higher than that in the first year. The quality–quantity heating operation strategies are effective ways to improve the discharge efficiency of the STS and the system performance without a heat pump. The electricity consumption of the pump on the heating side could be significantly reduced by 44.6% compared with the quality control. Ultimately, the findings in this paper are valuable for the optimization of the operation of solar-heating systems. [ABSTRACT FROM AUTHOR]

The pore-throat radius of the shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil–water two-phase relative permeability of the actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on a pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore-throat parameters, absolute permeability, and oil–water two-phase permeability curves were calculated, respectively. The results show that the pore-throat distribution of the Gulong shale reservoir is mainly concentrated in the nanometer scale; the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97. The calculated permeability considering diffusion is 0.000124 mD, which is approximately twice the permeability calculated without considering diffusion. The irreducible water saturation of the Gulong shale reservoir is approximately 0.4, and the residual oil saturation is approximately 0.35. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs. [ABSTRACT FROM AUTHOR]

The gas flow in shale reservoirs is controlled by gas desorption diffusion and multiple flow mechanisms in the shale matrix. The treatment of hydraulic fracturing injects a large amount of fracturing fluids into shale reservoirs, and the fracturing fluids can only be recovered by 30~70%. The remaining fracturing fluid invades the reservoir in the form of a water invasion layer. In this paper, by introducing the concept of a water invasion layer, the hydraulic fracture network is di-vided into three zones: major fracture, water invasion layer and stimulated reservoir volume (SRV). The mathematical model considering gas desorption, the water invasion layer and gas–water two-phase flow in a major fracture is established in the Laplace domain, and the semi-analytical solution method is developed. The new model is validated by a commercial simulator. A field case from WY shale gas reservoir in southwestern China is used to verify the utility of the model. Several key parameters of major fracture and SRV are interpreted. The gas–water two-phase flow model established in this paper provides theoretical guidance for fracturing effectiveness evaluation and an efficient development strategy of shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Regional trade leads to carbon transfer, which in turn raises the issue of carbon inequality. However, less existing research has focused on carbon inequality within megaregions. Combining multi-regional input-output analysis, carbon Gini coefficients and carbon deviation coefficients, this paper presents a comprehensive analysis of carbon equity in inter-provincial trade in the Yangtze River Economic Belt (YEB) from the perspective of economic benefits and environmental pressure. The results show that: (1) Carbon emissions from the production and consumption sides of the 11 provinces in the YEB vary considerably. (2) Significant carbon inequality exists in the YEB region. This is manifested in the unequal relationship between the transfer of embodied carbon emissions and economic benefits, as well as the difference in carbon deviation coefficients. Based on the results of our research, this paper can help provide theoretical support and decision-making reference for implementing a differentiated carbon emission reduction responsibility mechanism and establishing a coordinated carbon emission reduction responsibility system. [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]

China aims to reduce carbon dioxide emissions and achieve peak carbon and carbon neutrality goals. Natural gas, as a high-quality fossil fuel energy, is an important transition resource for China in the process of carbon reduction, so it is necessary to predict China's natural gas demand. In this paper, a novel natural gas demand combination forecasting model is constructed to accurately predict the future natural gas demand. The Lasso model and the polynomial model are used to build a combinatorial model, which overcomes the shortcomings of traditional models, which have low data dimensions and poor prediction abilities. In the modeling process, the cross-validation method is used to adjust the modeling parameters. By comparing the performance of the combinatorial forecasting model, the single forecasting model and other commonly used forecasting models, the results show that the error (2.99%) of the combinatorial forecasting model is the smallest, which verifies the high accuracy and good stability advantages of the combinatorial forecasting model. Finally, the paper analyzes the relevant data from 1999 to 2022 and predicts China's natural gas demand in the next 10 years. The results show that the annual growth rate of China's natural gas demand in the next 10 years will reach 13.33%, at 8.3 × 1011 m3 in 2033, which proves that China urgently needs to rapidly develop the gas supply capacity of gas supply enterprises. This study integrates the impact of multiple factors on the natural gas demand, predicts China's natural gas demand from 2023 to 2033, and provides decision-making support for China's energy structure adjustment and natural gas import trade. [ABSTRACT FROM AUTHOR]

Understanding the effect of a tradable green certificate (TGC) and renewable portfolio standard (RPS) policy mix is of great importance for sustainable renewable-energy development and carbon neutrality, given that the demand side subjects are the responsible subjects under China's RPSs and studies from the demand-side perspective are relatively limited. To fill this gap, this paper analyzes the coupled relationship between the TGC market and the electricity market as well as the reflexivity of the TGC market. Meanwhile, on the basis of modeling TGC prices and renewable-energy uncertainty, this paper constructs a Markov decision process (MDP) model to simulate the sequential decision-making process of the demand side and further proposes a solution model based on dynamic programming and evolutionary algorithms. The results show that: (1) In addition to policy parameters such as RPS weight, TGC price caps and penalties, a preference for short-term benefits and renewable-energy uncertainty also affect transaction behaviors on the demand side. (2) Increasing RPS weight within an appropriate range can stimulate demand for renewable power and TGC, while excessively low RPS weight will result in accumulation of unsold TGC. In addition, the preference for short-term benefits can stimulate demand for renewable power and curb demand for TGC. (3) An increase in the TGC price cap can stimulate demand for renewable power and restrain demand for TGC, but this phenomenon may not exist when RPS weight is too low or responsible subjects prefer short-term benefits. (4) Setting a penalty of no less than the TGC price cap is of great significance to ensure the operation of the TGC market and RPSs. [ABSTRACT FROM AUTHOR]

Total organic carbon (TOC) and hydrocarbon generation potential (Pg) are essential parameters for the qualitative evaluation of source rock and the basis for evaluating hydrocarbon resources in petroliferous basins. However, there will be some deviations in evaluating hydrocarbon resources of overmature source rock by using TOC and Pg. The super-thick overmature source rock of the Early Cretaceous Laiyang Formation was found in well LK-1, the Riqingwei Basin. To accurately understand the oil and gas potential of the Riqingwei Basin, this paper conducted a systematic organic geochemical analysis of the overmature source rock of the Early Cretaceous Laiyang Formation found in well LK-1. Combined with the results of previous thermal simulation tests on hydrocarbon generation of low-maturity samples in the Jiaolai Basin, the original total organic carbon (TOC0) content of source rock in well LK-1 was recovered and the evaluation criteria of overmature source rock was established. Results: (1) The average TOC content of well LK-1 source-rock samples is 1.25 wt.%, and the average Pg content is 0.11 mg/g. The type of organic matter is mainly type II2, including a small amount of type II1 and type III. The average reflectance of vitrinite (Ro) is 4.35%, which belongs to overmature source rock of a poor–fair level and mixed kerogen. (2) After recovery calculation, these samples' original hydrocarbon generation potential (Pg0) contents ranged from 0.63 to 108.1 mg/g, with an average value of 6.76 mg/g. Furthermore, the TOC0 contents of the analyzed source-rock samples ranged from 0.62 to 30.6 wt.%, with an average value of 2.01 wt.%. It belongs to fair–good source rock, showing better hydrocarbon generation potential. (3) According to the relationship between the Pg0, Pg and TOC content, the evaluation standard for overmature source rock in well LK-1 was established. Under the evaluation standard of overmature source rock, a source rock with a TOC content exceeding 0.6% and a Pg content greater than 0.1 mg/g can be identified as a good source rock. This paper provides a foundation for the fine classification and evaluation of the overmature source rock of the Riqingwei Basin. [ABSTRACT FROM AUTHOR]

Wind turbine energy generators operate in a variety of environments and often under harsh operational conditions, which can result in the mechanical failure of wind turbines. In order to ensure the efficient operation of wind turbines, the detection of any abnormality in the mechanics is particularly important. In this paper, a method for detecting abnormalities in the bearings of wind turbine energy generators, based on the cascade deep learning model, is proposed. First, data on the mechanics of wind turbine generators were collected, and the correlation between the data was studied in order to select the parameters related to the bearing temperature. Then, the logical relationship between the observation parameters and the target parameters was established based on a one-dimensional convolutional neural network (CNN) and a long short-term memory (LSTM) network, and the difference between the predicted temperature and the actual temperature was assessed using the root mean square error evaluation model. Finally, a numerical example was used to verify the operational data from a wind farm unit in northwest China. The results show that the CNN-LSTM model proposed in this paper can detect abnormalities earlier in the state of the main bearing than the LSTM model, and the CNN-LSTM model can detect abnormalities in the main bearing that the LSTM network cannot find. [ABSTRACT FROM AUTHOR]

With the proposal of China's "carbon peak, carbon neutral" strategy, the increasing awareness of low carbon production among consumers, and the government's introduction of carbon trading mechanism and low carbon consumption subsidy policies, enterprises are facing good opportunities for development. However, how the government can reasonably formulate low carbon policies and how enterprises can implement optimal low-carbon production decisions are still key issues in China's low-carbon transition development. In this context, this paper is based on the carbon trading mechanism and carbon consumption subsidies. In this context, based on the carbon trading mechanism, this paper focuses on green production and green consumption, considers the impact of low-carbon consumer preferences and government subsidies on enterprises' low-carbon production decisions, and uses the optimal theory to study the optimal pricing strategy and the optimal carbon reduction strategy. The study shows that the increase in carbon price has a positive effect on the increase in enterprise profit; the increase of carbon emission has a negative effect on the increase of enterprise profit and the high carbon price will intensify this effect. In addition, changing the intensity of government subsidies to consumers will lead to the change of enterprise carbon emission strategy. The study of this paper provides a certain reference for the government to reasonably formulate carbon trading prices and consumer low-carbon subsidies. In addition, considering consumer low-carbon preferences is also conducive to promoting green production practices of enterprises, thus promoting the realization of the carbon neutral strategy. [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]

The southern Junggar Basin, Xinjiang, has abundant coalbed methane (CBM) resources. Currently, the Baiyang River development pilot test area (BYR block for short) in the Fukang east block has achieved large-scale CBM development, but the productivity characteristics and its controlling factor are still unclear. Based on the field production data of the BYR block and experimental tests, this paper summarizes the gas and water production characteristics and presents the analysis results of the geological and geochemical responses to the productivity of CBM wells. The productivity of CBM wells in the BYR block was generally characterized as medium-to-low yield. The productivity was jointly controlled by the burial depth, structure condition, thickness and number of co-production coal seams, and hydrogeological conditions. The gas production first increased and then decreased with the increase in the burial depth of the coal seam, and a burial depth between 750 and 1000 m was the most beneficial to increasing the gas production due to the good gas preservation conditions and suitable permeability and stress conditions. The total thickness of the co-production coal seams had a positive effect on the productivity of gas wells, but the productivity was also affected by the number of co-production coal seams and interlayer interference. In the BYR block, the co-production of the nos. 41 and 42 coal seams was the most favorable combination form for CBM drainage. The productivity of CBM wells had a good response to the Na+, K+ and HCO3− concentrations but a poor response to δD-H2O and δ18O-H2O. Based on the concentrations of the main ions and TDSs of the coal seam water, a productivity response index δ* was established, and there was a good positive correlation between the productivity and δ*. [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]

Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great importance to the application of the new energy industry in urban transportation. Commuting is an important part of urban life, and the choice of travel behavior has an important impact on traffic and environmental protection. Taking the Xi'an metropolitan area as an example, this paper expounds on the integrated development path of the industrial chain of new energy + travel in the metropolitan area and clarifies the energy transformation model of the integrated development of low-carbon transportation and energy. From the perspective of green and low-carbon, 1000 commuters were interviewed using a questionnaire survey, and the cumulative prospect model was used to verify the internal mechanism affecting commuters in metropolitan areas to choose new energy commuting. The results of the study show that new energy transportation modes play an important role in the low-carbon economy, and under different scenarios and assumptions, there are significant differences in the cumulative prospect values of the subway, new energy buses and fuel private cars, and corresponding optimization measures are proposed to increase the proportion of new energy commuting trips. The results will help further promote the development of a low-carbon economy and energy integration in the field of transportation and provide a reference for the sustainable development of public transportation. [ABSTRACT FROM AUTHOR]

The research and application of CO2 storage and enhanced oil recovery (EOR) have gradually emerged in China. However, the vast unconventional oil and gas resources are stored in reservoir pores ranging from several nanometers to several hundred micrometers in size. Additionally, CO2 geological sequestration involves the migration of fluids in tight caprock and target layers, which directly alters the transport and phase behavior of reservoir fluids at different scales. Micro- and nanoscale fluidics technology, with their advantages of in situ visualization, high temperature and pressure resistance, and rapid response, have become a new technical approach to investigate gas–liquid interactions in confined domains and an effective supplement to traditional core displacement experiments. The research progress of micro–nano fluidics visualization technology in various aspects, such as CO2 capture, utilization, and storage, is summarized in this paper, and the future development trends and research directions of micro–nano fluidics technology in the field of carbon capture, utilization, and storage (CCUS) are predicted. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in China's manufacturing sector, the low-carbon transition of the steel industry is urgent. CO2 capture, utilization, and storage (CCUS) technology is one of the effective measures to reduce carbon emissions in steel industry. In this paper, a comprehensive assessment model of source–sink matching-levelized cost in China's steel industry is constructed to evaluate the potential, economy, and spatial distribution of CCUS retrofits of blast furnaces in the BF-BOF steel industry. The results show that, if no extra incentive policy is included, the levelized cost of carbon dioxide (LCOCD) of 111 steel plants with a 420.07 Mt/a CO2 abatement potential ranges from −134.87 to 142.95 USD/t. The levelized cost of crude steel (LCOS) range of steel plants after the CCUS retrofits of blast furnaces is 341.81 to 541.41 USD/t. The incentives such as carbon market and government subsidies will all contribute to the early deployment of CCUS projects. The CCUS technology could be prioritized for deployment in North China, Northwest China, and East China's Shandong Province, but more powerful incentives are still needed for current large-scale deployment. The research results can provide references for the early deployment and policy formulation of CCUS in China's steel industry. [ABSTRACT FROM AUTHOR]