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The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

China Power Grid is actively building a new energy-based ultra-high voltage grid system. Therefore, the researches on fire safety of power grid are of great importance. This paper firstly investigates the fire accident characteristics in the substation system. With the focuses on the transformer oil fires, the early detection and early warning, modification, fire monitoring and extinguishing systems of transformer oil are reviewed. It is found that the researches on flowing and jet fires should be reinforced while modified oil and pyrolysis gas detection can be applied for reducing the fire probability. Secondly, the fire risks and characteristics of cables are summarized for the transmission and distribution lines, and the methods of early warning, fire prevention and rescue are analyzed. For the wildfire threatening the transmission and distribution cables, the characteristics of wildfire and corresponding firefighting methods are reviewed. The water mist and liquid nitrogen are identified as the most effective ways of extinguishing cable fires and advanced fire detection and long-range drone fire extinguishing technologies should be improved for wildfires. Finally, the thermal runaway mechanism and fire characteristics of LIB in the energy storage system are summarized, and the difficulties in fire extinguishing are discussed. The application of the existing fire detection system in the field of LIB is proposed, and the early warning indicators for intelligent fire protection are introduced. In the future, the intelligent fire protection systems will improve the safety of energy storage systems, and efficient test platforms and reliable test standards will continue to be demanded to reduce the likelihood of thermal runaway and fire severity. [ABSTRACT FROM AUTHOR]

In response to global climate change, China has committed to peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, commonly known as the "30–60 Dual Carbon". Under the background of "30–60 Dual Carbon", this article takes the electric power industry, which is the main industry contributing to China's carbon emission, as the research object, explores the time and peak value of the carbon peak of the electric power industry, and analyzes whether carbon neutrality can be realized under the peak method, so as to get the carbon neutrality path of the electric power industry and serve as the theoretical basis for the formulation of relevant policies. The Environmental Kuznets Curve inspection and the relationship analysis are carried out, then the system dynamics model is constructed, the carbon emissions from 2020 to 2040 are simulated, and the peak time is predicted. Three different scenarios are set to explore the path of electricity carbon neutralization under the premise of a fixed peak. It is shown that Gross Domestic Product per capita index factors have the largest positive contribution, and thermal power share index factors have the largest negative contribution to electricity carbon emissions. Based on the current efforts of the new policy, carbon emissions can achieve the peak carbon emissions' target before 2030, and it is expected to peak in 2029, with a peak range of about 4.95 billion tons. After the power industry peaks in 2029, i.e., Scenario 3, from coal 44%, gas 9% (2029) to coal 15%, gas 7% (2060), where the CCUS technology is widely used, this scenario can achieve carbon neutrality in electricity by 2060. Adjusting the power supply structure, strictly controlling the proportion of thermal power, optimizing the industrial structure, and popularization of carbon capture, utilization, and storage technology will all contribute to the "dual carbon" target of the power sector. [ABSTRACT FROM AUTHOR]

Summary: Traditional power grid investment forecasting models often ignore the cyclical characteristics of historical investment data, leading to one‐sided investment allocation results and insufficient model generalization ability. This article proposed a power network investment forecasting method based on particle swarm optimization‐gate recurrent unit (PSO‐GRU) neural network. First, the temporal attention mechanism is introduced into the traditional GRU network, which improves the ability of the network to extract temporal features. Then, in order to avoid the adverse effects of unreasonable parameter configuration on model training, an optimized particle swarm optimization algorithm was proposed to optimize the parameter set of GRU and improve the training accuracy of the model. The data provided by an electric power company in China is used for experimental analysis, and the predicted results are compared with other electric power investment models. The RMSE of the PSO‐GRU model proposed in this article is 0.1223, which is superior to other algorithms and has certain effectiveness. [ABSTRACT FROM AUTHOR]

The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China's embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China's embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of "carbon peaking and carbon neutrality". [ABSTRACT FROM AUTHOR]

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

The geomagnetically induced current (GIC) produced during extreme geomagnetic storms can easily lead to large‐scale blackouts in China due to the increase in the scale of its electric power grid. A power grid's resilience is its capability to resist various natural hazards, withstand primary failures, and quickly resume normal operation. To avoid power grid damages, this study developed a resilient power grid, incorporating failure, power flow calculation and recovery models under a uniform induced geoelectric field. We chose a system's performance loss as the resilience evaluation indicator, which intuitively reflected a system's loss under GIC. In addition, the recovery model was optimized using a genetic algorithm, and two resilience improvement measures were proposed. The IEEE‐RTS‐79 system, consisting of 10 generators, 24 buses and 5 transformers, was chosen as an example to verify the feasibility of this study. The results show that the genetic algorithm and optimization measures effectively enhanced the system's resilience indicator and provided a reference for preventing system damages under GIC and quick recovery after possible failures. Plain Language Summary: Extreme space weather produces large geomagnetic field disturbances; these disturbances propagate down to Earth, inducing secondary geomagnetically induced currents (GICs) in earthed electric power grids. GICs increase transformers' reactive power loss and raise their temperatures; this affects a power system's normal operation, and in extreme cases causes major blackouts. Therefore, it is vital to study power grids' resilience under GIC events. In this study, we calculated the GIC level using a uniform geoelectrical conductivity model. Based on this, we proposed a resilient power grid model consisting of the failure model, power flow calculation model and recovery model, and evaluated optimization strategies. Our results show that the proposed model can improve a power system's recovery performance after possible failure due to GICs and effectively avoid GIC‐related large‐scale blackouts. Key Points: We proposed a resilience assessment method for transmission systems under extreme space weatherWe calculated a resilience indicator and identified multiple effective methods to improve a system's resilienceWe chose the IEEE‐RTS‐79 system as an example to verify the effectiveness of a genetic algorithm and optimization measures [ABSTRACT FROM AUTHOR]

Carbon emissions from the electricity industry (CEEI) account for a large proportion of China's total carbon emissions, and it is important to study the spatial correlation between CEEI and the influencing factors to promote cross-regional synergistic emission reduction and low-carbon development of the power system. In this paper, the quasi-input-output (QIO) model is applied to assess the transfer of carbon emissions generated by electricity trading based on the consideration of electricity carbon transfer, and the exploratory spatial data analysis (ESDA) method is applied to analyze the spatial correlation effect of carbon emissions from China's electric power sector from 2001 to 2020, analyzes its distribution pattern in both spatial and temporal dimensions, and applies the improved logarithmic mean Divisia index (LMDI) two-stage decomposition model to decompose the changes in CEEI into 11 influencing factors from the perspective of the whole industrial chain of power production, transmission, trade, and consumption. The research results show that (1) the spatial distribution of CEEI has obvious unevenness and aggregation characteristics, with high-high aggregation areas and hot spot aggregation areas generally concentrated in the North China Power Grid and the East China Power Grid, but the aggregation trend is gradually decreasing, while low-low aggregation areas and cold spot aggregation areas are concentrated in the Northwest China Power Grid and the Central China Power Grid, but the area is very limited. (2) The direction of carbon emission diffusion in China's electricity industry is gradually transitioning from southwest-northeast to northwest-southeast, and the east-west diffusion trend is stronger than the north-south diffusion trend and carbon emissions are gradually shifting to the northwest grid. (3) The total amount of electricity production is the most influential factor in the change of CEEI, driving the cumulative growth of CEEI by 4495.34 Mt, followed by GDP per capita and electricity consumption intensity. Coal consumption for power generation, the share of thermal power, and net electricity exports were the main factors inhibiting the increase in carbon emissions from the power sector, with cumulative contributions of −797.74 Mt, −619.99 Mt, and −47.76 Mt, respectively. [ABSTRACT FROM AUTHOR]

Electric charge service and management is an important part of electric power work. The effective recovery of the electric charge relates to the smooth development of daily work and continuous improvement of the operation and management of power supply enterprises. With the large-scale implementation of the card prepayment system, the problem of electricity customers defaulting on electricity charges has been solved to a large extent, but some large electricity users still fail to pay electricity charges on time. Therefore, under the current situation of power grid development, it is still necessary to strengthen the service and management of electricity charges to promote efficient recovery of electricity charges. Speech recognition technology has increasingly become the focus of research institutions at home and abroad. People are committed to enabling machines to understand human speech instructions and hope to control the machine through speech. The research and development of speech recognition will greatly facilitate people's lives shortly. The development of 5G technology and the proposal of 6G technology make the interconnection of all things not only a hope but also a reality. To realize the interconnection of all things, one of the key technical breakthroughs is the development of a new human–computer interaction sensing system. Under the guidance of relevant theories and methods, this paper systematically analyzes the user structure, electricity charge recovery management and service system, existing problems and causes in South China, and clarifies the necessity of design and application of electricity charge service system in South China power supply companies. The experimental data and empirical analysis results show that the optimized Bert fusion model can provide more digital support for the power supply companies in South China in terms of electricity charge recovery efficiency, management level system improvement, and electricity charge service. [ABSTRACT FROM AUTHOR]

The metering accuracy and stability of the power grid transformer devices are of great concern to all parties of the power grid, power plants and large users, as well as the relevant government departments, with the further deepening of the electric power system reform and the gradual establishment of the electric power spot trading market. The outcomes demonstrate the viability and efficacy of the employed diagnosis method. The completed research can serve as a reference point for China's development of a capacitive voltage transformer line monitoring system. [ABSTRACT FROM AUTHOR]

Switching between different working modes customarily brings sudden changes in torque and speed, leading to energy wastage for mechatronics‐electro‐hydraulic power coupling electric vehicles. Investigating the effect of vehicle speed thresholds on operating mode switching when working in concert with compound energy sources is timely. Thus, under the constraint of a known reference path, the optimal threshold is determined by weighing the path tracking accuracy and economic performance with the vehicle speed and the accumulator pressure as control variables. Wherein the constraint relationship between the factors is fully elucidated by combining various typical and actual road conditions. The validation results indicate a positive correlation between the starting acceleration capacity and the threshold value for a certain accumulator volume. The optimal speed thresholds under new European driving cycle, China light‐duty vehicle test cycle‐passenger, and actual routes are 4.1, 3.81, and 3.66 m s−1, with state of charge consumption rates of 6.30%, 8.56%, and 4.25%, respectively. More frequent speed switching may lead to excessive hydraulic power wastage, thereby increasing dependence on electrical power. Appropriate threshold setting can effectively enhance path tracking accuracy and hydraulic utilization under unpredictable road conditions. This research may in the future provide theoretical support for the rational control and interconstraint mechanism of energy utilization in hybrid vehicles. [ABSTRACT FROM AUTHOR]

The electric power industry is related to the national livelihood, and regional economic development is closely related to the pillar industry. At present, China's economy continues to develop steadily, and the promotion of domestic industrialization has also increased the demand for electricity. In recent years, the state power industry has made great progress, in order to further adapt to the needs of domestic and foreign market competition, the State Grid has also carried out a systematic reform of its own management system. In the reform process, strengthening the construction of performance appraisal system is a very important change. According to statistics, as of June 2020, the number of employees of State Grid has reached more than 900,000. As the most basic business unit of the state grid, the team is the cell of the state grid. It is the basis for the completion of various production management work and plays an important role in the safe production and stable output of electric power enterprises. Based on the relevant indicators of the work of the team, this paper analyzes the performance of the team through the production cost performance model, and provides suggestions for the optimization of the team for power grid enterprises [ABSTRACT FROM AUTHOR]

With the expansion of the digital information industry, the size of global data centers is exploding. As part of a high-energy-consuming industry, data centers can support sustainable urban development through green transformation. This study uses a quasi-natural experiment of China's national green data center pilot policy implemented in 2015 to examine the impact of data center green transformation on green technology innovation in cities. Using a difference-in-difference (DID) analysis, this study finds that the national green data center pilot policy leads to higher levels of green technology innovation in cities, but the spillover effect of the policy on neighboring cities is insignificant. The mechanism test showed that the national green data center pilot policy could facilitate urban green technological innovation through capital deepening, market competition, and industrial agglomeration. In addition, the policy impact is more pronounced for cities with poorer environments, less civilization, high levels of network infrastructure, and more innovative endowments. The findings can provide new guidance for cleaner regional production from the standpoint of data center green development. [ABSTRACT FROM AUTHOR]

According to the perspective of multimode multimedia data, the protection technology of network information security is mainly discussed. The theoretical basic research is outlined, its meaning, level, reasons, and consequences are expounded, and the future research content and development trend are discussed. With the rapid development of online services and mobile technology, the world has entered the era of multimedia big data. There have been a large number of scientific studies in the multimedia industry, which explain the various fields of big data, including the capture, storage, reference, excavation, and search of multimedia big data. The article expounds the specific concept of power monitoring system network information security, establishes the safety regulations of electric power monitoring system, formulates the corresponding ideas for the safety guarantee level of electric power monitoring system, and promotes the long-term development of China's electric power enterprises. The safe operation of the power monitoring system is directly related to the stable operation of all power supply systems and even the social economy. At this stage, the situation of network security management in China's power monitoring system is still not optimistic. We take the multimode multimedia data, organize the research dynamics of the network security protection technology, and discuss the future research trend. [ABSTRACT FROM AUTHOR]

Sustainable development of energy and electric power is the primary task to support China’s high-quality economic and social development. Therefore, talent cultivation in the electric power industry is indispensable. Under the background of emerging engineering education, North China Electric Power University, as the cradle of the cultivation of outstanding talents in the electric power industry, took the lead in proposing and constructing the cultivation mode of compound applied chemistry talents based on the concept of “green power”, and successfully applied it to the reform and practice of undergraduate teaching. The practice enables students not only to master the application background and engineering practical skills of electric power environmental protection technology, but also to have the innovative ability of collaborative analysis and solving complex multi-pollutant control problems. The cultivation of high-quality applied chemistry talents in the new era would serve the development of the country. [ABSTRACT FROM AUTHOR]

China has pledged that it will strive to achieve peak carbon emission by 2030 and realize carbon neutrality by 2060, which has spurred renewed interest in hydrogen for widespread decarbonization of the economy. Hydrogen energy is an important secondary clean energy with the advantage of high density, high calorific value, rich reserves, extensive sources and high conversion efficiency that can be widely used in power generation, transportation, fuel and other fields. In recent years, with the guidance of policies and the progress of technology, China's hydrogen energy industry has developed rapidly. About 42% of China's carbon emissions comes from the power system and Shenzhen has the largest urban power grid in China. Bringing the utilization of hydrogen energy into Shenzhen's power system is an important method to achieve industry transformation, achieve the "double carbon" goal and promote sustainable development. This paper outlines the domestic and international development status of hydrogen energy, introduces the characteristics of Shenzhen new power system, the industrial utilization of hydrogen energy and the challenges of further integrating hydrogen energy into Shenzhen new power system and, finally, suggests on the integration of hydrogen energy into Shenzhen new power system in different dimensions. [ABSTRACT FROM AUTHOR]

Building a new type of power system is an important guarantee to support China's "dual carbon" goal. Due to the inseparable relationship between industrial and agricultural production and electric energy utilization, there must be interdisciplinary integration to achieve the goal of "dual carbon". The disciplines of horticulture and electric power are taken as examples in this paper to analyze the feasibility of carbon emission reduction through coordinating agricultural photovoltaic (PV) greenhouse and electric vehicle (EV) energy storage. Firstly, the mechanism of carbon emission difference caused by electric energy supplementing during EV charging is analyzed. Secondly, in the context of the contradiction between the reduction of battery life caused by discharging (increasing carbon emission) and the increase in PV output consumption by orderly charging and discharging (reducing carbon emission), an optimization model for the synergistic operation of EV clusters and greenhouse PVs (with the objective of minimizing carbon emissions) is proposed. Finally, the effectiveness of the proposed model is verified through simulation cases. The energy storage characteristics of EVs is capable of realizing the transfer of PV power generation in the time dimension, and the coordinated operation of greenhouse PVs and EVs' charging and discharging can effectively reduce carbon emission during the EV operation period. In a typical summer scenario of PV output, the carbon emission of EVs in V2G (vehicle to grid) mode was reduced by 69.13% compared to disorderly charging. It is shown that the adequacy of PV generation and the orderly dispatching of the charging and discharging of EVs are the key factors in reducing carbon emission throughout the life cycle of EVs. [ABSTRACT FROM AUTHOR]

Under the background of the deepening reform of China's electric power industry, how to make use of existing resources, keep existing employees, and identify and distinguish the influencing factors of turnover have become major problems faced by companies. At the same time, the identification of influencing factors also provides a reference for relevant enterprises to do a good job in talent reserve and recruitment. The influencing factors of employee turnover are numerous and interrelated. Identifying and distinguishing the influencing factors are the focus of academic research. Meanwhile, it provides a reference for relevant enterprises to do an excellent job in personnel reserve and recruitment. Aiming at the limitation of constructing a direct matrix based on experts' scoring method in the traditional DEMATEL model, a model combining random forest and DEMATEL is proposed, applied to identify the influencing factors of employee turnover in electric power enterprises in Qinghai Province. Based on the employee turnover data set of Qinghai Electric Power Company from 2012 to 2020, the empirical analysis is conducted to analyze the influencing factors of employee turnover from two perspectives of the degree of centrality and the degree of causal. The research results show that marital status, household registration, political status, type of job, and the location of the work unit are the key influencing factors, providing a theoretical basis for the early warning of employee turnover and confirming the feasibility of the random forest-DEMATEL method proposed by us. [ABSTRACT FROM AUTHOR]

Early microbial gas has been sealed in reservoirs in the Miquan region of NW China, with little or no supply of current microbial gas. To date, the environmental conditions and mechanisms restricting microbial methanogenesis are still unclear in the Miquan region. Thus, in this study, a series of gas and water samples from coalbed methane (CBM) exploitation wells and in situ coal samples were collected and analyzed to determine the potential for current microbial gas generation, the methanogenic pathways, the source of nutrients, the influence of the environmental conditions on in situ microbial communities and their methanogenesis, and the mechanisms restricting microbial methanogenesis. The gas-production simulation experiments revealed that the existing microbes in the coalbed water were less efficient at converting coal into methane under the approximate in situ conditions, which further verified that there was little or no supply of current microbial gas. The stable isotope compositions of the gas samples suggested that carbon dioxide (CO2) reduction was the dominant metabolic pathway for generating CBM, whereas the methanogenic communities contained a mixture of acetoclastic and methylotrophic methanogens in local areas. The nutrients available for the microbes mainly included the total dissolved nitrogen (TDN) and total dissolved carbon (TDOC), and the in situ dissolution of the coals was a significant source of the TDN, whereas the TDOC was mainly supplied by surface water. The microbes in the different tectonic settings were significantly controlled by different combinations of environmental factors, and there was no single environmental factor that completely dominated the spatial variability of the microbial communities. The gradual stagnation of the water environment led to an increase in salinity and a decrease in nutrients, which were likely the main factors restricting microbial methanogenesis under in situ conditions. Combined with the results of the rate-limiting stages of the anaerobic fermentation, the mechanisms restricting microbial methanogenesis can be finally determined in the Miquan region. These discoveries presented in this case study provide a significant supplement to the geological theory of CBM accumulation, and have a guiding significance for CBM development in the Miquan region. [ABSTRACT FROM AUTHOR]

As the technical demand-supply text information increases rapidly in electric power technology transfer, traditional matching methods could no longer meet the need. To solve this problem, this paper proposed a new technical demand-supply matching method based on electric power technical field feature. First, the improved TF-IDF algorithm was used to extract technical field feature, then scientific and technological achievements with higher relevancy were retrieved based on technical field feature to build a background library of electric power technological achievements, and the matching degree of electric power technological achievements based on word vector was used to verify the matching efficiency of this method. We adopted the China smart grid technical transaction service platform and the text message of electric power technical demand and technological achievements on Keyi net for application, and the results indicate this method has raised the matching efficiency by 23.4% compared to traditional methods. In this paper, a new idea of taking technical field feature as the demand-supply matching basis of electric power technology transfer platform was proposed, which opens a new perspective for the research of demand-supply matching efficiency on electric power technology transfer platform, helps to promote the matching efficiency of technical demand and technological achievements, and further raises the success rate of electric power technology transfer. [ABSTRACT FROM AUTHOR]

This paper searches and combs the achievements of grey system theory in the past nearly 40 years based on databases of China national knowledge internet (CNKI) and ISI Web of Science. More than 227 thousands literatures were found by inputting 10 phrases such as grey system‑grey number and sequence operator etc. in CNKI. After entering the 21st century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year, and more than 15 thousands papers have been included per year since 2014. The grey system method and model are widely used in natural science fields such as physics, chemistry, and biology, as well as engineering technology fields such as transportation, electric power and machinery, and a large number of valuable results have been achieved. From the large number of documents applying the grey system method and model, which are published by the project team undertaking important national science and technology plans and the double first‑class universities in China, it can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development, and high-level talent training. [ABSTRACT FROM AUTHOR]

China’s electric utility industry is among the country’s main polluters. Increasing the efficiency of China’s power supply chain is therefore essential to promote more environmentally sustainable power generation. This paper assesses the performance of China’s regional power supply chains that include electric utilities and power grid companies. We rely on the notion of sustainable supply chains to propose a multi-stage model that accounts for negative externalities such as harmful emissions, power transmission line loss, and increased mortality caused by pollution. Different from the existing studies of power supply chains, our approach is based on the exponential directional distance function defined with respect to a multiplicative production technology that can help mitigate the impact of data outliers. We use a panel of 30 Chinese provinces covering the period 2008–2018 to measure the efficiency improvement potential within regional supply chains and assess the efficiency-enhancing role of digital innovation. Our results provide evidence of considerable regional disparities and suggest that China’s eastern provinces outperform other regions due to the relatively advanced state of their technology. Furthermore, we demonstrate that the efficiency improvement potential from better management or technological innovation remains significant across the majority of provinces. Finally, our results provide evidence of a significant role of digitalization in promoting the efficiency of power supply chains. Our findings offer important perspectives on the strategies policymakers can use to promote sustainable performance of electric utilities and power grid companies. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China's electricity consumption, this paper analyzes the data characteristics of China's electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China's power demand from 2004 to 2019, the ARMA time series model is used to analyze China's future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China's electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China's power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China's power. [ABSTRACT FROM AUTHOR]

A life-cycle assessment of bio-jet fuel from waste cooking oil (WCO) produced by hydrotreatment was performed and compared with petroleum-derived jet fuel. This study aimed to evaluate the sustainability and find out the bottleneck restricting the development of WCO-based jet fuel production. The carbon intensity of the WCO-based bio-jet fuel was 63.7% lower compared to the conventional jet fuel, and the proportion of greenhouse gas (GHG) emissions caused by hydrogen in the WCO was 18.7%. The feedstock stage proportion of GHG emissions of first-, second-, and third-generation biofuels increased. A sensitivity analysis found that the transportation distance of WCO was more sensitive to GHG emissions, and it is important to develop a detailed plan for feedstock collection. A scenario analysis was also performed according to China's energy structure and hydrogen sources. Although the electric power structure derived from renewable energy will increase GHG emissions in the immediate future, it will eventually reduce emissions due to technical progress by 2050. The preparation of jet fuel from WCO can not only recycle waste but can also contribute to emission reduction for the aviation industry, which is a potential sustainable and feasible aviation fuel route. [ABSTRACT FROM AUTHOR]

This study examines the carbon reduction investment decisions of the electric power energy supply chain considering carbon trading and carbon subsidy policies in China's "dual carbon" context. By building a three-level supply chain system including electric power producers, retailers, and consumers, we discuss the optimal decision-making problem of the supply chain for three models of decentralized supply chain decision making without government subsidies, centralized supply chain decision making with government subsidies, and centralized supply chain decision making with government subsidies and carbon emission reduction cost sharing. Through model solving and further numerical simulations, the results showed that the increase in carbon emission reduction investment cost has a significant negative impact on power price and the total expected income of the supply chain. However, a reasonable level of government carbon emission reduction subsidy can effectively alleviate the increase in power price and improve the total expected income of supply chain. In addition, carbon mission reduction investment and supply chain cost allocation can effectively improve the carbon emission reduction level of the power supply chain, improve the income and enthusiasm of electric power producers, and realize the sustainable development of electric power energy consumption and the environment. [ABSTRACT FROM AUTHOR]

People's daily life heavily depends on energy. The core business of electric power enterprises is commercial energy sales. In the daily work of power enterprises, energy marketing is the most important field which will directly affect the development of enterprises. Although national macro-control exists as a useful way to control the energy market, it also increases the risk of the energy market. Nowadays, the development of the energy market is affected with the adjustment of industrial structure. In the energy market, China's power companies are state-owned enterprises and have their unique advantages for developing, but there are still some problems in risk awareness, which require us to take measures to control and prevent the impact risk. [ABSTRACT FROM AUTHOR]

The relationship between resource misallocation and productivity has become a hot topic in recent years, but few studies examined the impact of spatial misallocation of electric power resources (SMEPRs) on economic efficiency and carbon emissions. Here, we constructed a calculation model of SMEPRs that can measure both the misallocation degree and direction and uncovered the spatiotemporal evolvement mechanism of SMEPRs. On this basis, we explored the impact of SMEPRs on regional economic efficiency and carbon emissions using panel data from 29 provinces in China from 1988 to 2017. The results demonstrate that the high level of SMEPRs in China shows complex spatiotemporal characteristics and significantly affects the regional economic efficiency and carbon emissions. Specifically speaking, first, SMEPRs present the characteristics of the coexistence of excessive and insufficient allocation among provinces and regions, the increasing extent of misallocation in the eastern and western regions, and the gradual decline in the central region; second, SMEPRs have a strong negative effect on the regional economic efficiency and carbon emissions by affecting regional industrial structures, which indicates that SMEPRs are an important factor restricting the high-quality development of regional economies. The research is conducive to the development of resource misallocation theory. Moreover, the research observations offer fresh insights to upgrading the high-quality and green development of China's power sector and promoting regional economic transformation and ecological sustainability. [ABSTRACT FROM AUTHOR]

Research on the supply and demand of ecosystem services is related to human well-being. The sustainability of the supply of ecosystem services is also the basis for sustainable social, economic and natural environments. Research on supply and demand can provide theoretical guidance for the rational utilization and allocation of natural resources,which helps to improve the ecological compensation mechanism and coordinate the relationship between various stakeholders. We analyze the degree of correspondence between socioeconomic system demand and natural ecosystem supply by analyzing the research results of supply and demand of ecosystem services. It also strengthens our understanding of different factors influencing ecosystem services, which has important reference value for current land spatial planning systems. We systematically summarize the research status of ecosystem services in China and abroad through literature reviews. The literature publication status of supply and demand examines the conceptual connotation of ecosystem service supply and demand, and it distinguishes between the primary connotation and relationship of potential supply, actual supply, potential demand and actual demand. We summarize and compare the research methods related to the supply and demand of ecosystem services, summarizes the practical applications of evaluating the supply and demand of ecosystem services in China and abroad, as well as the problems and limitations in the current research on the supply and demand of ecosystem services. Further, it outlines the scope for future research to provide a reference for the research and application of supply and demand of ecosystem services. [ABSTRACT FROM AUTHOR]

Alternative energy sources, derived from biomass feedstocks, are important for China's energy security. To evaluate China's capacity for bioenergy in the future, Geographic Information System (GIS) techniques were adopted to identify potentially productive marginal areas for the growth of 16 energy crops and to comprehensively estimate their biomass and bioenergy production potential under three scenarios. The results showed that a total of 267.23 Mha (i.e., million hectare) of marginal land was available for energy crop production. When assessing the suitability of individual environments for each type of energy crop, the largest total land area of a lignocellulosic energy crop, an oil energy crop, and a lignocellulosic energy tree were 3.64 Mha (Miscanthus spp.), 45.44 Mha (Jatropha curcas L.), and 63.55 Mha [Haloxylon ammodendron (C. A. Mey.) Bunge], respectively. In addition, the proposed production of bioethanol [Sorghum bicolor (L.) Moench], biodiesel [Swida wilsoniana (Wanger.) Sojak], and bio-electricity [H. ammodendron] in the baseline scenario met 31.83%, 26.08%, and 9.2% of ethanol demand for E10, diesel, and electricity in 2016, respectively. Furthermore, if upland and forest land could be used to produce bioenergy, the bioethanol substitution rates of ethanol for E100, diesel, and electric power were calculated as 62.63%, 153.94%, and 60.47%, respectively, for 2040. The results indicated that China's future energy demands could not be satisfied by simply depending on energy crops in most situations. Future bioenergy should be developed based on reliable supplies of several types of biomass materials and dedicated biochemical or thermochemical conversion processes, among other renewable energy sources. [ABSTRACT FROM AUTHOR]

With the expansion of the scale of industrial land, China's industrial economy continues to grow at a high speed, but the long-term homogeneous land supply policy has led to low land use efficiency. Exploring differentiated industrial land supply policy (DILSP) innovations can effectively address this issue. However, due to the limited practical cases, there are few studies on the policy innovations of industrial land supply. Based on the life cycle management (LCM) of industrial land (LCMIL), this study uses the policy analysis method to reform and innovate industrial land supply policy to solve the disadvantages of the current industrial land supply policy and proposes the DILSP as its basis. The research shows the following: (1) there are many problems in China's current land supply policy, but policy innovation in some economically developed cities has achieved positive results, indicating that an effective institutional supply is the best way to solve these problems; (2) the process of industrial land utilization has obvious cyclical characteristics, and a complete process and differentiated supply policy framework based on "differentiated access evaluation, differentiated supply method, differentiated supply period, differentiated supply price, differentiated post-supply supervision" has a certain rationality and feasibility. This study provides an innovative solution to the shortcomings of China's existing industrial land supply policy, and the idea of applying LCM theory to government policy-making also has a certain reference significance. [ABSTRACT FROM AUTHOR]

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

The KBQA (Knowledge-Based Question Answering) system is an essential part of the smart customer service system. KBQA is a type of QA (Question Answering) system based on KB (Knowledge Base). It aims to automatically answer natural language questions by retrieving structured data stored in the knowledge base. Generally, when a KBQA system receives the user's query, it first needs to recognize topic entities of the query, such as name, location, organization, etc. This process is the NER (Named Entity Recognition). In this paper, we use the Bidirectional Long Short-Term Memory-Conditional Random Field (Bi-LSTM-CRF) model and introduce the SoftLexicon method for a Chinese NER task. At the same time, according to the analysis of the characteristics of application scenario, we propose a fuzzy matching module based on the combination of multiple methods. This module can efficiently modify the error recognition results, which can further improve the performance of entity recognition. We combine the NER model and the fuzzy matching module into an NER system. To explore the availability of the system in some specific fields, such as a power grid field, we utilize the power grid-related original data collected by the Hebei Electric Power Company to improve our system according to the characteristics of data in the power grid field. We innovatively make the dataset and high-frequency word lexicon in the power grid field, which makes our proposed NER system perform better in recognizing entities in the field of power grid. We used the cross-validation method for validation. The experimental results show that the F1-score of the improved NER model on the power grid dataset reaches 92.43%. After processing the recognition results by using the fuzzy matching module, about 99% of the entities in the test set can be correctly recognized. It proves that the proposed NER system can achieve excellent performance in the application scenario of a power grid. The results of this work will also fill the gap in the research of intelligent customer-service-related technologies in the power grid field in China. [ABSTRACT FROM AUTHOR]

This study performed a multi - scale error analysis of the mean surface downward shortwave radiation flux product ERA5 (0. 25° X 0. 25°) of the European Centre for Medium - Range Weather Forecasts ( ECMWF) using 93 pieces of solar radiation hourly data in 2013 of China. Subsequently, this study revised and analyzed the total radiation product ERA5 by training the random forest model using various relevant elements such as meteorological and geographic ones. Finally, the model was used to obtain the map of revised hourly radiation spatial distribution. As a result, the reanalyzed data can be beter applied in industries such as agriculture, electric power, and urban construction. The results are as follows. $ The MAE, RMSE, and R values between the ERA5 solar radiation and the measured values of stations in 2013 were 27.60 W/m2, 29. 87 W/m2, and 0. 97 respectively. Moreover, the ERA5 values were higher than the measured values of stations. % The accuracy was improved after the revision using the random forest model. After revision, the MAE, RMSE, and R values between the ERA5 solar radiation and the measured values of stations were 3. 34 W/m2, 3.85 W/m2, and 1. 00, respectively, indicating that correlation was significantly improved. © The spatial macroscopic distribution paUerns of radiation before and after revision were consistent, but the ERA5 radiation value significantly decreased in local areas. [ABSTRACT FROM AUTHOR]

A critical method of ensuring grain production is to increase the total factor productivity (TFP), and the key measure to increase the TFP of grain production lies in the construction of agricultural public infrastructure. For this topic, existing literature lacks systematic and empirical analysis. Therefore, research on the influence of agricultural public infrastructure on the TFP of China's grain production has relatively strong policy implications and theoretical value. For this study, we collected panel data for grain inputs and outputs as well as for agricultural public infrastructure in China's provinces (autonomous regions/municipalities) from 1990 to 2017, and adopted the stochastic frontier function (SFF) approach to measure the TFP of provincial-level grain production. Through this empirical study, we analyzed the influence of agricultural public infrastructures, such as irrigation, roads, and electric power facilities on the TFP of China's agriculture. We found that such facilities have a positive influence on the TFP of grain production. Specifically, when the input for irrigation facilities is increased by 1 percent, the TFP of grain production will rise by 5.74 percent. Based on this finding, policy recommendations are proposed for enhancing grain TFP through agricultural public infrastructure construction. [ABSTRACT FROM AUTHOR]

With the increase of fire problems of new energy vehicles (EVs), more and more attention has been paid to charging safety. Firstly, the charging safety problems and protection strategies in the power grid are summarized from the grid side, the charging equipment side, the vehicle side, and the operation platform side, and a solution for the vehicle side charging safety protection is proposed. Secondly, with regards to building a charging early warning protection system architecture, a real-time protection strategy for EV charging is proposed; a battery temperature difference, battery voltage ramp rate, and current ramp rate are proposed; and a double-layer protection model of an active protection layer and a big data protection layer is established based on the real-time monitoring of 27 parameters. Finally, by building a physical simulation platform of the early warning system, the simulation and verification are carried out based on the BYD Han model. The system was demonstrated in the State Grid Tianjin Electric Power Company of China. The results show that the system can realize the charging real-time early warning and deal with it in time when the battery charging is abnormal, which has practical application value for the popularization and development of EVs. [ABSTRACT FROM AUTHOR]

As a common natural disaster, drought can significantly affect the agriculture productivity and human life. Compared to Southeast China, Northwest China is short of water year-round and is the most frequent drought disaster area in China. Currently, there are still many controversial issues in drought monitoring of Northwest China in recent decades. To further understand the causes of changes in drought in Northwest China, we chose Shaanxi, Gansu, and Ningxia provinces (SGN) as our study area. We compared the spatiotemporal characteristics of drought intensity and frequency in Northwest China from 2003 to 2020 showed by the Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Vegetation Supply Water Index (NVSWI), Soil Moisture Condition Index (SMCI), and Soil Moisture Agricultural Drought Index (SMADI). All of these indices showed a wetting trend in the SGN area from 2003 to 2020. The wetting trend of the VCI characterization is the most obvious (R2 = 0.9606, p < 0.05): During the period 2003–2020, the annual average value of the VCI in the SGN region increased from 28.33 to 71.61, with a growth rate of 153.57%. The TCI showed the weakest trend of wetting (R2 = 0.0087), with little change in the annual average value in the SGN region. The results of the Mann–Kendall trend test of the TCI indicated that the SGN region experienced a non-significant (p > 0.05) wetting trend between 2003 and 2020. To explore the effectiveness of different drought indices, we analyzed the Pearson correlation between each drought index and the Palmer Drought Severity Index (PDSI). The PDSI can not only consider the current water supply and demand situation but also consider the impact of the previous dry and wet conditions and their duration on the current drought situation. Using the PDSI as a reference, we can effectively verify the performance of each drought index. SPI-12 showed the best correlation with PDSI, with R values greater than 0.6 in almost all regions and p values less than 0.05 within one-half of the study area. SMADI had the weakest correlation with PDSI, with R values ranging −0.4~−0.2 and p values greater than 0.05 in almost all regions. The results of this study clarified the wetting trend in the SGN region from 2003 to 2020 and effectively analyzed the differences in each drought index. The frequency, duration, and severity of drought are continuously reduced; this helps us to have a more comprehensive understanding of the changes in recent decades and is of significance for the in-depth study of drought disasters in the future. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization and storage (CCUS), a water resource-intensive technology, has been projected to be restricted by water resources in the future. However, the water-saving effects resulting from technology progress and CO 2 -Enhanced water recovery (CO 2 -EWR) process are not been fully considered. Based on the learning curve theory, this study proposes a new water accounting system for CCUS retrofitting of coal-fired power plants (CFPPs) from a dynamic perspective considering power generation, carbon capture, and CO 2 -EWR technology. The results show that the total water withdrawal per unit of CCUS retrofitting with the first-generation capture technology will decrease by 66.89 %, and the total water consumption per unit of that will decrease by 74.70 % from 2021 to 2050. By contrast, the water withdrawal and consumption per unit with the second-generation capture technology will decrease by 74.12 % and 82.51 %, with the overall unit water consumption below 0.5 m3/MWh. Moreover, the water usage caused by CCUS retrofitting will be greatly relieved through the progress of geological sequestration technology (especially the CO 2 -EWR). In addition, the water usage during the capture process for circulation cooling and air-cooling would present an "inverted U" shaped trend affected by the capture scale and technology progress. Remarkably, the water withdrawal and consumption intensity of CFPPs with air-cooling technology is significantly lower than those of the circulation cooling technology for power generation, while the opposite happens if the capture technology is applied. Even so, CCUS retrofitting for the CFPPs with air-cooling technology can save 60 × 104 m3 of water resource after 2040, which is positive for the CCUS deployment in the arid areas of China. [Display omitted] [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Oil Crop Sciences is the property of Oil Crops Research Institute of Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Governments actively encourage renewable energy use to deal with climate change and achieve carbon emission reduction targets. It is crucial to find out the driving factors that affect the utilization of renewable energy. Therefore, based on China's 2010–2016 input–output table, this paper uses the input–output model and structural decomposition analysis (SDA) to analyze the driving factors of renewable energy changes in the production end, household end, and the aggregate economy. The results show that the changes in the consumption structure (F) is the most crucial factor for renewable energy use, followed by technology progress (T) and final demand per capita (V). Sector SEHW (supply of electric power, heat power, and water) and MCRP (manufacture of coke and refined petroleum products) are the two vital sectors to achieve China's energy transition of the production level. However, as for households, the proportion of renewable energy has been declining. Hence, the government should promote renewable energy use and achieve the green transition in production and household levels. [ABSTRACT FROM AUTHOR]

Electricity has substantial effects on rescue and relief responses after strong earthquakes. Substations are essential components of electric power networks, and their seismic performance has recently attracted the attention of academia and industry, in particular, the recovery capacity from external events. This capacity is referred to as seismic resilience, which is defined as the ability of a system to resist, recover from, and adapt to an earthquake impact. It is quantified as the change in functionality over time. However, it is challenging to quantify the optimum recovery process dynamically due to interrelations between components. In this paper, a new probability-based method is proposed to assess the seismic resilience of complex systems, such as substations. A case study is performed on a typical 220 kV substation in China, and the seismic resilience of the system is investigated focussing on three important issues: (1) definition of system functionality; (2) a system model that considers the interrelations among the components; (3) recovery strategies to restore system functionality. The resilience index of the system with a functionality prioritisation recovery strategy is two to three times higher than that of a pre-determined one at the maximum considered earthquake. [ABSTRACT FROM AUTHOR]

Summary: Sustainable energy production has been one of the contemporary concerns of society. In order to mitigate carbon dioxide emissions while generating the required demand for energy, various energy technologies, and production systems must be considered. In the consideration of different energy technologies, optimization is one of the important tools to optimally design energy systems. This study aims to analyze the progress of current research related to energy and sustainability that utilizes fuzzy optimization approach. Bibliometric methods based on the database of Web of Science core collection are used for the analysis. Of the 96 retrieved publications, 87% were journal articles. Analysis on the patterns for these articles were conducted such as highly cited articles, journals, subject categories, institutions, countries, and impact factor. The articles are evaluated into three categories such as technological, environmental, and economy and are comprehensively reviewed. The results showed a significant increase in publication related to fuzzy optimization in sustainability and energy technologies. The analysis showed China with 26 publications, which has the largest contribution in terms of the number of articles published. North China Electric Power University ranked as the number 1 institution with 10 publications. Based on the comprehensive analysis, fuzzy optimization showed significant results on technological, environmental, and economical factors. These findings help to identify hotspots in energy technology optimization for sustainability research. Similarly, the study gives useful inputs for selecting subtopics and strategy on publication related to fuzzy optimization on energy technologies. [ABSTRACT FROM AUTHOR]

This study investigates the determinants of efficiency in the energy sectors of China and Singapore. It examines three possible futures for the electricity industry in China and Singapore: business as usual, energy efficiency improvement, and regulation and incentive improvement. A panel dataset was subjected to cross-sectional analysis using data envelopment analysis and Tobit regression. In the last 10 years, the electric power sector has reduced carbon dioxide, sulfur dioxide, nitrogen dioxide, and mercury emission rates by 90%, 88%, and 95%, respectively, as a result of imperatives for the closing of small coal-fired power stations, air emissions regulations and the utilisation of renewable energy initiatives. Finally, it is suggested that the maximum capabilities of such expenditures can only be achieved if they are considered and involved in the project discovery process, rather than just as an add-on to initiatives initially planned as demand initiatives. [ABSTRACT FROM AUTHOR]

Background: The energy generation efficiencies of thermal power and hydropower, which are the two main forces of electric power in China, are important factors affecting the energy conservation, emission reduction, and green development of the country's whole power industry. Methods: Considering regional differences and multiple efficient decision-making units (DMUs), this research uses the meta-Frontier super-efficiency slack-based measure (meta-SE-SBM) undesirable model to comprehensively evaluate the efficiencies of hydropower and thermal power generation in China. The CO2 emissions of thermal power generation are taken as the undesirable output. Results: The ranking of the average meta-efficiency of thermal power generation in China is Eastern China > Central China > Western China, and all regions show an upward trend. However, the ranking of the average meta-efficiency of hydropower generation is Western China > Central China > Eastern China, and all these regions present a downward trend. In 2017, the technology gap ratio (TGR) values for the thermal power generation efficiency of the eastern and western regions showed a rising trend, while that for the central region showed a declining trend. The TGR values of the hydropower generation efficiency of the western region continued to increase, while those of the central and eastern regions decreased. The development trends of the TGR values of the thermal power or hydropower generation efficiencies of the three regions were not consistent with each other, indicating that technological convergence has not been achieved. In the three regions, the technology gaps in hydropower have slightly expanded, but the technology gaps in thermal power have gradually narrowed. The undesirable output CO2 of the thermal power energy efficiency of the three regions is in a surplus, and the generation of hydropower in the eastern and central regions is insufficient. Conclusions: The government and power industry managers should fully consider regional heterogeneity in the efficiency of hydropower and thermal power to reduce the technology gap in China. The thermal power industry is relatively mature, but its CO2 emissions should be controlled. The hydropower industry needs further policy support to promote an efficiency improvement in it under the condition of resource endowments. [ABSTRACT FROM AUTHOR]

With the rapid development of new energy sources and the increasing proportion of electric vehicles (EVs) connected to the power grid in China, peak load regulation of power systems will face severe challenges. Therefore, in this study, we analyzed the relationship between the electricity consumption characteristics of EVs and the peak load regulation (PLR) mechanism of power systems, and we proposed an operation mode for virtual power plants with EVs to participate in the auxiliary service market and facilitate deep peak load regulation in the thermal power units. Based on the electricity demand‐side management theory and cost‐benefit analysis method, we constructed a decision model for economic deep peak load regulated operation (DPLR) of the auxiliary thermal power units in a virtual power plant with EVs, aiming to optimize the operation efficiency. The case study showed that a virtual power plant that included EVs can effectively reduce the total PLR cost of the system and the peak valley difference of the net load as well as improve the economic benefits of the thermal power units. The results indicated that the virtual power plant had improved economic efficiency. Therefore, the results of this research can help improve the PLR capacity of the grid and significantly promote the consumption of intermittent renewable energy. [ABSTRACT FROM AUTHOR]

In recent years, the issues related to carbon emissions and environment have attracted extensive attentions. Considering four scenarios (the energy conversion, energy capital savings and loans, energy exports and cement production carbon emissions), this paper adopts the energy consumption method and input-output method to analyze China's carbon emissions structure on the supply-side and demand-side of energy, and finally provides policy recommendations for China's structural emission reduction. The results show that, if the four influencing factors were not considered, the measurement of carbon emissions from the final demand was 44.91% higher than the baseline scenario, 12.36% lower than the baseline scenario from intermediate demand, and 10.23% lower than the baseline scenario from the total. For China's carbon emissions structure on the supply-side of energy, the carbon emissions from high-carbon energy, represented by raw coal, accounted for 66.805% of the total energy-related carbon emissions, while the carbon emissions from low-carbon energy, represented by natural gas, only accounted for 2.485%. For China's carbon emissions structure on the demand-side of energy, the carbon emissions from intermediate demand (enterprise production) accounted for more than 95% of total energy-related carbon emissions, while the carbon emissions from final demand (residents and government use) accounted for less than 5%. For each specific industry in intermediate demand for energy, the heavy industry, electric power, fossil energy, and chemical industry have high carbon emissions and low carbon emissions efficiency. However, the agriculture, construction, light industry, and service are the opposite. Finally, we provide policy recommendations for improving the accuracy of carbon emissions measurement and carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Currently, focus on dry ports in the People's Republic of China (PRC) is growing, and therefore, the number of dry ports in the country is actively increasing. Due to the multifunctionality of dry ports, they meet the modern requirements of China's transport policy, which prioritizes improving the quality of providing transportation services by providing general access to value-added and high-quality services. The purpose of the PRC's transport system is also to facilitate the movement of freight flows within the State's territory, due to a faster modal shift, increased accessibility of transport, development of auxiliary functions, and construction of integrated transport hubs. Dry ports deal with the mentioned tasks; however, with the increase in the number of dry ports in the PRC, the issue of optimizing the interaction between dry ports has become urgent. The purpose of this research is to scientifically substantiate the need for strengthening technological cooperation between dry ports. The problem of determining the optimal structure of the system of interaction of dry ports was solved using the method of discreteevent simulation and the anyLogistix software tool. The results of assessment of the economic efficiency of the interaction between dry ports are presented. The results of experiments with a model of China's dry port system showed the possibility of increasing the total profit of participants of the supply chain by 2.3 times and their profitability by 2.6 times, reducing the cost of container transportation by 1.3 times, and fully meeting the demand for transportation. It has been proven that the cooperation of dry ports in supply chains provides enhanced opportunities for processing cargo flows, as a result of the redirection of cargo consignments from overloaded dry ports to dry ports with reserves with processing capacity. A methodology for optimizing the structure of the system of interaction of dry ports is presented. The methodology is proposed for use as a tool for strategic and current planning of supply chains. [ABSTRACT FROM AUTHOR]

Pumped storage power stations are increasingly constructed around cities to provide electric power and ensure grid stability. However, the upper reservoirs are typically located on mountaintops, and the reservoir leakage, which directly affects the economic benefits, is typically difficult to estimate. Therefore, to calculate the leakage within a short period, a one-dimensional simplified analytical method for estimating the leakage of pumped storage power station reservoir basins is proposed based on the stable seepage theory and Darcy's law. Formulae are derived to calculate the seepage flux of the reservoir basin with different groundwater levels, which can be below or above the bottom of the reservoir basin. The reliability of this analytical method was validated using numerical analysis with regard to a pumped storage power station in China, and the relative errors between the analytical results and the numerical results are less than 5%. The proposed method is beneficial for engineering decision-making and design before the construction of pumped storage power stations. [ABSTRACT FROM AUTHOR]

Mount of embodied carbon emissions flow along industrial chains and form a complex network. In order to reveal the structure and evolution characteristics of embodied carbon emission flow network among China's industrial sectors, this study applies a complex network theory to construct six embodied carbon emission flow networks with 30 sectors on the basis of China's input-output tables from 2002 to 2015. Through the analysis of complex network technology indicators, the overall structural characteristics of the network, the key sectors, and the key flow paths are analyzed. Main results show that six embodied carbon emission flow networks all have the small-world characteristics; there is an industrial cluster phenomenon in the network. During the study period, construction, manufacturing, and service-related industry community are the absorption sites for embodied carbon emissions. Coal- and petroleum-related industry communities are the divergent sites for embodied carbon emissions; moreover, electric and heat power and fuel processing are the important "suppliers" of embodied carbon emissions; construction and other service are the important "consumers" of embodied carbon emissions. Non-metallic products are the important "transmitters" of embodied carbon emissions. Metal smelting and chemical industry are at the core of the network because of their high weighted degree and betweenness centrality. The central effect of key sectors continues to increase over time; furthermore, the distribution of embodied carbon emission flows in the six networks all have long-tail characteristics, and this characteristic became more prominent over time. There are key edge-weights in the networks. About 11 to 15% of the edges carry 80% of the embodied carbon emissions. Further based on edge-weight analysis, this study identifies the key paths of embodied carbon emission flow in the six networks, and most key paths pass through construction. Thus, such key sectors and key flow paths should receive more attention when making carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

With the comprehensive progression of China's electric power reform, the participation of hydropower in the spot market has become inevitable. For hydropower-dominated power grids, the tight hydraulic and electric coupling relationship between cascade hydropower plants and the policy requirement of clean energy consumption greatly increase the challenge of optimal scheduling. Based on the market characteristics and actual demand of the hydropower-dominated power grids, this paper discusses the day-ahead spot market trading mechanism to promote the guaranteed consumption of renewable energy. On this basis, a day-ahead optimal scheduling model is established which aims to minimize the comprehensive power purchase cost of the power system. The nonlinear factors in the scheduling model, such as the relationship between the water level and storage capacity of hydropower plants, the relationship between the water level and water consumption rate, and the constraints on the start-up and shutdown durations of thermal power units, are linearized through multiple linearization techniques. The original nonlinear model is transformed into a mixed integer linear programming (MILP) model and is then solved using a CPLEX solver. The developed model is verified by taking 10 thermal power plants and 22 hydropower plants in Yunnan Power Grid as a case study. The calculation time is 183.6s, the comprehensive power purchase cost of the system is 155.35·million CNY, and no abandoned water is generated in the three basins. The simulation results show that the proposed model has high solution accuracy and efficiency, and maximizes the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost. The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grids. [Display omitted] • A day-ahead spot market trading mechanism to promote consumption of renewable energy. • Day-ahead optimal scheduling of hydropower-dominated power grids under a spot market environment. • A novel MILP approach is employed to solve the model. • Proposed model has high solution accuracy and efficiency. [ABSTRACT FROM AUTHOR]