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Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China's logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of space weather on China's electricity market. Based on data products provided by NOAA and the National Energy Administration in China, this paper uses solar wind velocity as a solar weather indicator and the disturbance storm time index as a magnetospheric weather indicator to match monthly Chinese electricity market data over 10 years. Based on a VAR model, we found that (1) space weather increases the demand for electricity in China, and solar wind speed and the geomagnetic index increase the electricity consumption of the whole of Chinese society, as space weather mainly increases the electricity consumption of the secondary and industrial sectors. (2) The geomagnetic index significantly promotes power station revenue. (3) Space weather is associated with increased energy consumption. The geomagnetic index significantly increases the coal consumption rate of fossil power plants in China, but the solar wind speed has nothing to do with the coal consumption rate of fossil power plants. [ABSTRACT FROM AUTHOR]

In the context of low-carbon constrained development, in order to avoid the risk brought by climate change, more and more companies choose to disclose carbon information, respond to the national policy of carbon emission reduction and focus on the sustainable development of enterprises. This paper will investigate the impact of carbon disclosure on financial performance based on the 2011–2018 CDP report, taking the Fortune 500 companies as a sample. The study finds that for carbon-intensive industries, carbon disclosure cannot significantly contribute to the improvement of financial performance in the current period, but for carbon-non-intensive industries, carbon disclosure can significantly contribute to the improvement of financial performance in the current period, and the positive impact of carbon disclosure on financial performance in the current period can be extended to the next period. Finally, based on the findings of the empirical study, this paper puts forward policy recommendations for the construction of China's carbon disclosure system. [ABSTRACT FROM AUTHOR]

Chinese wind power policies have productively promoted the development of wind power and also promoted the process of wind power participation in electricity market transactions. However, with policy emphasis on investment and neglect of utilization, there have been some difficulties in the development of Chinese wind power. To highlight the guiding role of policy and improve the wind power policy system, an analysis of Chinese wind power policies is conducted in this paper. First, aiming at the main components of wind power chain, including wind power construction, grid connection, transmission, and sales, a comprehensive and systematic frame of Chinese wind power policy system is proposed from the three aspects of development planning, administrative management and market transactions. Second, the indicator system of Chinese wind power development effectiveness is extracted, including installed capacity, power generation, power utilization hours, carbon emission reduction, investment, on-grid power price, wind curtailment rate, etc., and the effectiveness of policy implementation is verified. Third, new policy recommendations are proposed from parts of transmission, consumption, and market, for the development of Chinese wind power industry in the 14th Five-Year Plan period and the goal to reach the crest value of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. In this paper, advice to supplement and improve the Chinese wind power policy system is provided, which may it promote better development of Chinese wind power in the following decade from the policy point of view. [ABSTRACT FROM AUTHOR]

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces' URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China's policymakers. [ABSTRACT FROM AUTHOR]

Dissolved gas analysis (DGA) based in insulating oil has become a more mature method in the field of transformer fault diagnosis. However, due to the complexity and diversity of fault types, the traditional modeling method based on oil sample analysis is struggling to meet the industrial demand for diagnostic accuracy. In order to solve this problem, this paper proposes a probabilistic neural network (PNN)-based fault diagnosis model for power transformers and optimizes the smoothing factor of the pattern layer of PNN by the improved gray wolf optimizer (IGWO) to improve the classification accuracy and robustness of PNN. The standard GWO easily falls into the local optimum because the update mechanism is too single. The update strategy proposed in this paper enhances the convergence ability and exploration ability of the algorithm, which greatly alleviates the dilemma that GWO is prone to fall into local optimum when dealing with complex data. In this paper, a reliability analysis of thirteen diagnostic methods is conducted using 555 transformer fault samples collected from Jiangxi Power Supply Company, China. The results show that the diagnostic accuracy of the IGWO-PNN model reaches 99.71%, which is much higher than that of the traditional IEC (International Electrotechnical Commission) three-ratio method. Compared with other neural network models, IGWO-PNN also has higher diagnostic accuracy and stability, and is more applicable to the field of transformer fault diagnosis. [ABSTRACT FROM AUTHOR]

The development of renewable clean energy such as hydropower can not only ensure energy security, but also help achieve the United Nation's Sustainable Development Goals. This paper uses the annual data of 30 provinces in China from 2000 to 2017, and constructs a dynamic spatial Durbin model and a geographically weighted regression model to empirically test the dynamic impact of hydropower on haze pollution and economic growth at the national and provincial levels. The empirical results show that the promoting effect of hydropower on economic growth in Western China is less than that in Eastern China, which further aggravates the economic development gap between the eastern and western regions. In addition, the suppression effect of hydropower on the haze pollution in the western region is greater than that in the eastern region, where the haze pollution is serious. From the national level, hydropower can promote regional economic growth and inhibit haze pollution, and the spatial spillover effects of these two effects are greater than the local effects, and the long-term impact is greater than the short-term impact. The research conclusions of this paper will help China realize the sustainable development goals of energy saving and emission reduction. [ABSTRACT FROM AUTHOR]

Deep and even ultra-deep petroleum resources play a gradually increasing and important role with the worldwide continuous advancement of oil and gas exploration and development. In China, the deep carbonate reservoirs in the Tarim Basin are regarded as the key development areas due to their huge reserves. However, due to the unreasonable design of production pressure differential, some production wells suffered from severe borehole collapse and tubing blockage. Therefore, the main purpose of this paper is to optimize a more practical method for predicting the critical production pressure differential. The commonly used analytical methods with different failure criteria for predicting production pressure differential were summarized. Furthermore, their advantages and disadvantages were analyzed. A new numerical model is established based on the finite element theory in order to make the prediction of production pressure differential more accurate. Additionally, both analytical and numerical methods were applied to evaluating the production pressure differential of deep carbonate reservoirs in the Tarim Basin, and the results were discussed compared with field data. In addition, a series of laboratory tests, including porosity and permeability measurements, electron microscope scanning, XRD for mineral analysis, uniaxial and triaxial compressive strength test, etc., were carried out by using the collected carbonate cores from formations deeper than 7000 m to obtain the input parameters of the simulation such as the rock properties. The experimental results showed that the carbonate rocks exhibited a remarkable brittleness and post-peak strain softening. The calculation results revealed that the Mogi-Coulomb criterion is slightly conservative; however, it is more suitable than other criteria to evaluate pressure differential. Furthermore, it has been confirmed by the field data that the finite element numerical method can not only reveal the instability mechanism of the wellbore but also predict the critical production pressure differential accurately. Unfortunately, the on-site operators sometimes require a more convenient way, such as an analytical method, to figure out the pressure differential, even though the evaluation of the numerical method is more accurate. Therefore, the discussion in this paper can provide a basis for the operators to determine the production pressure differential flexibly. [ABSTRACT FROM AUTHOR]

As an important part of the global ecosystem, wetlands and their dynamics greatly influence regional eco-environment systems. To understand the distributions, change processes and temporal-spatial characteristics of the wetlands of the inland river basin in an arid region (Heihe River Basin, HRB), this paper employed multi-source remote sensing data to facilitate multi-temporal monitoring of the HRB wetland using a wetland information extraction method. First, we performed monitoring of these wetlands for the years 2000, 2007, 2011 and 2014; then, we analyzed the variation characteristics of the spatial-temporal dynamics of the wetlands in the HRB over the last 15 years via the landscape dynamic change model and the transformation matrix. In addition, we studied the possible driving mechanisms of these changes. The research results showed that the total area of the HRB wetlands had decreased by 2959.13 hectares in the last 15 years (Since 2000), and the annual average loss was 1.09%. The dynamics characterizing the HRB wetlands generally presented a trend of slow increase after an initial decrease, which can be classified into three stages. From 2000 to 2007, the total wetland area rapidly decreased; from 2007 to 2011, the area slowly decreased; and from 2011 to 2014, the area gradually increased. The dynamic changing processes characterizing the wetland resources were ascribed to a combination of natural processes and human activities. The main driving mechanisms of wetland dynamic changes include climatic conditions, upper reach water inflows, population, water resources, cultivated area, and policy. The findings of this study can served as reference and support for the conservation and management of wetland resources in the HRB. [ABSTRACT FROM AUTHOR]

In this paper we develop an agent-based model to explore a feasible way of simultaneously providing sufficient food and bioenergy feedstocks in China. Concerns over the competition for agricultural land resources between food and bioenergy supply hinder the further development of bioenergy, especially in China, the country that needs tofeed the world's largest population. Prior research has suggested the introduction of energy crops and reviewed the resulting agricultural land use change in China. However, there is a lack of quantitative studies which estimate the value, contribution, and impact of bioenergy for specific conditions at the county level and provide adequate information to guide local practices. Tofill this gap, we choose the Jiangsu Province in China as a case study, build up a spatial-agent dynamic model of agricultural land use, and perform a sensitivity analysis for important parameters. The simulation results show that straw from conventional crops generally dominates Jiangsu's biomass supply with a contribution above 85%. The sensitivity analyses reveal severe consequences of bioenergy targets for local land use. For Jiangsu Province, reclaimed mudflats, an alternative to arable lands for energy crop plantation, help to secure the local biomass supply and to alleviate the land use conflict between food and biomass production. [ABSTRACT FROM AUTHOR]

In China, the power sector is currently the largest carbon emitter and the transportation sector is the fastest-growing carbon emitter. This paper proposes a model of solar-powered charging stations for electric vehicles to mitigate problems encountered in China's renewable energy utilization processes and to cope with the increasing power demand by electric vehicles for the near future. This study applies the proposed model to Shenzhen City to verify its technical and economic feasibility. Modeling results showed that the total net present value of a photovoltaic power charging station that meets the daily electricity demand of 4500 kWh is $3,579,236 and that the cost of energy of the combined energy system is $0.098/kWh. In addition, the photovoltaic powered electric vehicle model has pollutant reduction potentials of 99.8%, 99.7% and 100% for carbon dioxide, sulfur dioxide, and nitrogen oxides, respectively, compared with a traditional gasoline-fueled car. Sensitivity analysis results indicated that interest rate has a relatively strong influence on COE (Cost of Energy). An increase in the interest rate from 0% to 6% increases COE from $0.027/kWh to $0.097/kWh. This analysis also suggests that carbon pricing promotes renewable energy only when the price of carbon is above $20/t. [ABSTRACT FROM AUTHOR]

Coal-fired thermal power plants, which represent the largest proportion of China's electric power system, are very sluggish in responding to power system load demands. Thus, a reasonable and feasible scheme for the medium-term optimal commitment of thermal units (MOCTU) can ensure that the generation process runs smoothly and minimizes the start-up and shut-down times of thermal units. In this paper, based on the real-world and practical demands of power dispatch centers in China, a flexible mathematical model for MOCTU that uses equal utilization hours for the installed capacity of all thermal power plants as the optimization goal and that considers the award hours for MOCTU is developed. MOCTU is a unit commitment (UC) problem with characteristics of large-scale, high dimensions and nonlinearity. For optimization, an improved progressive optimality algorithm (IPOA) offering the advantages of POA is adopted to overcome the drawback of POA of easily falling into the local optima. In the optimization process, strategies of system operating capacity equalization and single station operating peak combination are introduced to move the target solution from the boundary constraints along the target isopleths into the feasible solution's interior to guarantee the global optima. The results of a case study consisting of nine thermal power plants with 27 units show that the presented algorithm can obtain an optimal solution and is competent in solving the MOCTU with high efficiency and accuracy as well as that the developed simulation model can be applied to practical engineering needs. [ABSTRACT FROM AUTHOR]

Large-scale offshore wind farms (OWF) are under construction along the southeastern coast of China, an area with a high typhoon incidence. Measured data and typhoon simulation model are used to improve the reliability of extreme wind speed (EWS) forecasts for OWF affected by typhoons in this paper. Firstly, a 70-year historical typhoon record database is statistically analyzed to fit the typhoon parameters probability distribution functions, which is used to sample key parameters when employing Monte Carlo Simulation (MCS). The sampled typhoon parameters are put into the Yan Meng (YM) wind field to generate massive virtual typhoon in the MCS. Secondly, when typhoon simulation carried out, the change in wind field roughness caused by the wind-wave coupling is studied. A simplified calculation method for realizing this phenomenon is applied by exchanging roughness length in the parametric wind field and wave model. Finally, the extreme value theory is adopted to analyze the simulated typhoon wind data, and results are verified using measured data and relevant standards codes. The EWS with 50-year recurrence of six representative OWF is predicted as application examples. The results show that the offshore EWS is generally stronger than onshore; the reason is sea surface roughness will not keep growing accordingly as the wind speed increases. The traditional prediction method does not consider this phenomenon, causing it to overestimate the sea surface roughness, and as a result, underestimate the EWS for OWF affected by typhoons. This paper's methods make the prediction of EWS for OWF more precise, and results suggest the planer should choose stronger wind turbine in typhoon prone areas. [ABSTRACT FROM AUTHOR]

Densified Biomass Solid Fuel (DBSF) is a typical solid form of biomass, using agricultural and forestry residues as raw materials. DBSF utilization is considered to be an alternative to fossil energy, like coal in China, associated with a reduction of environmental pollution. China has abundant biomass resources and is suitable to develop DBSF. Until now, a number of policies aimed at fostering DBSF industry have been proliferated by policy makers in China. However, considering the seasonality and instability of biomass resources, these inefficiencies could trigger future scarcities of biomass feedstocks, baffling the resilience of biomass supply chains. Therefore, this review paper focuses on DBSF policies and strategies in China, based on the supply chain framework. We analyzed the current developing situation of DBSF industry in China and developed a framework for policy instruments based on the supply chain steps, which can be used to identify and assess the deficiencies of current DBSF industry policies, and we proposed some suggestions. These findings may inform policy development and identify synergies at different steps in the supply chain to enhance the development of DBSF industry. [ABSTRACT FROM AUTHOR]

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified. [ABSTRACT FROM AUTHOR]

Construction land expansion significantly affects energy-related carbon emissions. This paper analyzed the effect of construction land expansion on energy-related carbon emissions in China and its provinces from 2001 to 2011 by using the logarithmic mean Divisia index method. We divided the study into two intervals (2001-2006 and 2006-2011) and categorized the 30 provinces of China into eight zones. Results indicated that construction land expansion exerted the second largest positive effect on carbon emission growth in China and in the 30 provinces from 2001 to 2011. The north, east, and south coastal regions as well as the middle Yellow River region, were the highly affected regions in the same period. Between the two study intervals, the effect of construction land expansion on carbon emissions decreased in China and in the coastal regions, but increased in inland regions. The Hebei, Shandong, Jiangsu, Zhejiang, Fujian, Guangdong, Yunnan, Chongqing, Ningxia, and Xinjiang provinces, which are concentrated in the north, east, and south coastal regions, were selected for the reduction of carbon emissions by controlling construction land expansion. [ABSTRACT FROM AUTHOR]

With the development of the smart grid in China, new opportunities for responsive industrial loads to participate in the provision of ancillary services (AS) will become accessible. This paper summarizes AS in China and analyzes the necessary characteristics and advantages of industrial users to provide AS according to their response mechanism. Cement manufacturing and aluminum smelter processes are selected as two representatives of responsive industrial loads. An agent-based model that includes generation, industrial user, and grid agents is proposed. Using two case studies, we analyze the integrated power management of conventional units and industrial loads in day-ahead and real-time AS scheduling based on real device parameters, price mechanisms and production data. The simulation results indicate that the participation of responsive industrial loads in the provision of AS, in China, can improve the coal consumption rate and the system-wide load factor as well as reduce the total system cost for the provision of AS significantly. [ABSTRACT FROM AUTHOR]

China's emissions continue to rise rapidly in line with its mounting energy consumption, which puts considerable pressure on China to meet its emission reduction commitments. This paper assesses the impacts of CO2 mitigation measures in China during the period from 2010 to 2050 by using a computable general equilibrium method, called AIM/CGE. Results show that renewable energy makes a critical difference in abating emissions during the period from 2010 to 2020. The scenarios with emission trading would drive more emission reductions, whereby the emission-cutting commitment for 2020 would be achieved and emission reductions in 2050 would be more than 57.90%. Meanwhile, the share of non-fossil energy increases significantly and would be more than doubled in 2050 compared with the BAU scenario. A carbon tax would result in a significant decline in emissions in the short term, but would have an adverse effect on economic growth and energy structure improvements. It is also observed that the integrated measures would not only substantially decrease the total emissions, but also improve the energy structure. [ABSTRACT FROM AUTHOR]

Based on the international community's analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI) decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China's contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a) economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China's current actual policy; (b) the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c) considering the regional protectionism, regional actual situation need to be considered at the same time; (d) in the study of the industrial structure, the contribution value of industry is the most prominent factor for China's carbon productivity, while the industrial restructuring has not been done well enough. [ABSTRACT FROM AUTHOR]

This paper extends prior research on energy inefficiency in China by utilizing a unique shadow price framework allocation in 30 Chinese provinces. We estimate the shadow price for energy input using the framework of production, and use the ratio of the shadow price to the market price to describe energy utilization. Using Chinese provincial-level data from 1998 to 2011, the results of the analysis reveal that shadow prices in China have grown rapidly during the sample period, which signifies that China has improved its performance in energy utilization since 1998. However, there are eighteen provinces whose shadow prices are lower than market prices. This result suggests that energy utilization is at a low level in these provinces and can be improved by a reallocation of inputs. [ABSTRACT FROM AUTHOR]

In 2009, the implementation of feed-in tariff (FIT) and attractive public subsidies for onshore wind farms aroused great investment enthusiasm and spurred remarkable development of wind power in China. Meanwhile, rapid learning-by-doing has significantly cut down the cost of wind turbines and the capital cost of wind farms as well. Therefore, it is the right time to examine the appropriateness of the existing FIT policy for wind power in China. In this paper, we employ the analytical framework for levelized cost of electricity (LCOE) to model the generation cost of wind power. Results show that the existing FIT policy is attractive to investors, but serious curtailment and turbine quality issues could make wind power unprofitable. Meanwhile, rapid substantial decreases in the cost of wind power have made it competitive to coal power in 2013, implying that it is possible and necessary to reform the FIT policy for new wind farms. In the future, energy policies for onshore wind power in China could be concentrated on reducing the integration cost, so as to reduce the overall system cost. [ABSTRACT FROM AUTHOR]

Accurate forecasting of fossil fuel energy consumption for power generation is important and fundamental for rational power energy planning in the electricity industry. The least squares support vector machine (LSSVM) is a powerful methodology for solving nonlinear forecasting issues with small samples. The key point is how to determine the appropriate parameters which have great effect on the performance of LSSVM model. In this paper, a novel hybrid quantum harmony search algorithm-based LSSVM (QHSA-LSSVM) energy forecasting model is proposed. The QHSA which combines the quantum computation theory and harmony search algorithm is applied to searching the optimal values of σ and C in LSSVM model to enhance the learning and generalization ability. The case study on annual fossil fuel energy consumption for power generation in China shows that the proposed model outperforms other four comparative models, namely regression, grey model (1, 1) (GM (1, 1)), back propagation (BP) and LSSVM, in terms of prediction accuracy and forecasting risk. [ABSTRACT FROM AUTHOR]

Currently, there are considerable discrepancies between China's central government and some local governments in attitudes towards coal to liquids (CTL) technology. Energy return on investment (EROI) analysis of CTL could provide new insights that may help solve this dilemma. Unfortunately, there has been little research on this topic; this paper therefore analyses the EROI of China's Shenhua Group Direct Coal Liquefaction (DCL) project, currently the only DCL commercial project in the world. The inclusion or omission of internal energy and by-products is controversial. The results show that the EROIstnd without by-product and with internal energy is 0.68-0.81; the EROIstnd (the standard EROI) without by-product and without internal energy is 3.70-5.53; the EROIstnd with by-product and with internal energy is 0.76-0.90; the EROIstnd with by-product and without internal energy is 4.13-6.14. Furthermore, it is necessary to consider carbon capture and storage (CCS) as a means to control the CO2 emissions. Considering the added energy inputs of CCS at the plant level, the EROIs decrease to 0.65-0.77, 2.87-3.97, 0.72-0.85, and 3.20-4.40, respectively. The extremely low, even negative, net energy, which may be due to high investments in infrastructure and low conversion efficiency, suggests CTL is not a good choice to replace conventional energy sources, and thus, Chinese government should be prudent when developing it. [ABSTRACT FROM AUTHOR]

This paper presents a model for the projection of Chinese vehicle stocks and road vehicle energy demand through 2050 based on low-, medium-, and high-growth scenarios. To derive a gross-domestic product (GDP)-dependent Gompertz function, Chinese GDP is estimated using a recursive dynamic Computable General Equilibrium (CGE) model. The Gompertz function is estimated using historical data on vehicle development trends in North America, Pacific Rim and Europe to overcome the problem of insufficient long-running data on Chinese vehicle ownership. Results indicate that the number of projected vehicle stocks for 2050 is 300, 455 and 463 million for low-, medium-, and high-growth scenarios respectively. Furthermore, the growth in China's vehicle stock will increase beyond the inflection point of Gompertz curve by 2020, but will not reach saturation point during the period 2014–2050. Of major road vehicle categories, cars are the largest energy consumers, followed by trucks and buses. Growth in Chinese vehicle demand is primarily determined by per capita GDP. Vehicle saturation levels solely influence the shape of the Gompertz curve and population growth weakly affects vehicle demand. Projected total energy consumption of road vehicles in 2050 is 380, 575 and 586 million tonnes of oil equivalent for each scenario. [ABSTRACT FROM AUTHOR]

Support vector machine (SVM), which serves as one kind of artificial intelligence technique, has been widely employed in transformer fault diagnosis when involving dissolved gas analysis (DGA). However, when using SVM, it is easy to misclassify samples which are located near the decision boundary, resulting in a decrease in the accuracy of fault diagnosis. Given this issue, this paper proposed a genetic algorithm (GA) optimized probabilistic SVM (GAPSVM) integrated with the fuzzy three-ratio (FTR) method, in which the GAPSVM can judge whether a sample is near the decision boundary according to its output probabilities and diagnose the samples which are not near the decision boundary. Then, FTR is used to diagnose the samples which are near the decision boundary. Combining GAPSVM and FTR, the integrated model can accurately diagnose samples near the decision boundary of SVM. In addition, to avoid redundant and erroneous features, this paper also used GA to select the optimal DGA features. The diagnostic accuracy of the proposed GAPSVM integrated with the FTR fault diagnosis method reached 86.80% after 10 repeated calculations using 118 groups of IEC technical committee (TC) 10 samples. Moreover, the robustness is also proven through 30 groups of DGA samples from the State Grid Co. of China and 15 practical cases with missing values. [ABSTRACT FROM AUTHOR]

As a component of China's strategic emerging industries, green lighting is an important industry supporting the high-quality and high-efficiency development of China's economy, and is also an important way to achieve energy conservation and emission reduction. At present, China has basically established a policy framework to promote the development of green lighting industry, but there is no empirical evidence on the performance of existing policies on energy conservation and emission reduction. Based on the development status of China's green lighting industry, this paper sorts out the milestones of China's green lighting industry policy and the current status of the framework of the existing green lighting industry development policies, constructs a policy performance evaluation model for China's green lighting industry based on the difference-in-difference (DID) model, and evaluates the implementation effects of green lighting industry policies in China from the perspective of energy conservation and emission reduction. The empirical results of China's 85 cities show that the implementation of green lighting industry policies has significantly promoted regional energy conservation and emission reduction. Finally, this paper puts forward targeted policy recommendations to provide policy support for the transformation of China's green lighting industry from "large" to "strong". [ABSTRACT FROM AUTHOR]

As a component of China's strategic emerging industries, green lighting is an important industry supporting the high-quality and high-efficiency development of China's economy, and is also an important way to achieve energy conservation and emission reduction. At present, China has basically established a policy framework to promote the development of green lighting industry, but there is no empirical evidence on the performance of existing policies on energy conservation and emission reduction. Based on the development status of China's green lighting industry, this paper sorts out the milestones of China's green lighting industry policy and the current status of the framework of the existing green lighting industry development policies, constructs a policy performance evaluation model for China's green lighting industry based on the difference-in-difference (DID) model, and evaluates the implementation effects of green lighting industry policies in China from the perspective of energy conservation and emission reduction. The empirical results of China's 85 cities show that the implementation of green lighting industry policies has significantly promoted regional energy conservation and emission reduction. Finally, this paper puts forward targeted policy recommendations to provide policy support for the transformation of China's green lighting industry from "large" to "strong". [ABSTRACT FROM AUTHOR]

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings. [ABSTRACT FROM AUTHOR]

With the continuous increase of China's foreign-trade dependence on crude oil and the accelerating integration of the international crude oil market and the Chinese finance market, the spillover effect of international oil price fluctuation on China's stock markets increasingly attracts the attention of the public. In order to explore the impact of international oil price fluctuation on China's stock markets and the time-varying spillover differences of industry sectors, this study proposes three research hypotheses and constructs a multi-time scale analysis framework based on wavelet analysis and a time-varying t-Copula model. In this paper, we use the Shanghai Composite Index as the representative of a general trend of the stock market, and we use the stock index of the China Securities Industry as the counterpart of industrial sectors. Based on the data from 5 January 2005 to 31 May 2020, this paper measures and analyzes the spillover effect of international oil price fluctuation on China's stock markets, under different volatility periods. The results show that, firstly, the spillover effect of international oil price fluctuation on the Chinese stock markets is different. In the short and medium volatility period, the changes in international oil price are ahead of the changes in the Chinese stock markets, while the latter is ahead of the former under long-term fluctuations. Secondly, the spillover effect of international oil price fluctuation on China's industry stock indexes is persistent. As the time scale increases, the tail dependency will increase. Finally, the impact of risk events aggravates the volatility of the stock markets in the short-term, while the mid- to long-term impact mainly affects the volatility trend. Investment risk control can make overall arrangement on the basis of the characteristics of oil price impact under different fluctuation stages. [ABSTRACT FROM AUTHOR]

Wind energy has been widely used in renewable energy systems. A probabilistic prediction that can provide uncertainty information is the key to solving this problem. In this paper, a short-term direct probabilistic prediction model of wind power is proposed. First, the initial data set is preprocessed by a box plot and gray correlation analysis. Then, a generalized method is proposed to calculate the natural gradient and the improved natural gradient boosting (NGBoost) model is proposed based on this method. Finally, blending fusion is used in order to enhance the learning effect of improved NGBoost. The model is validated with the help of measured data from Dalian Tuoshan wind farm in China. The results show that under the specified confidence, compared with the single NGBoost metamodel and other short-term direct probability prediction models, the model proposed in this paper can reduce the forecast area coverage probability while ensuring a higher average width of prediction intervals, and can be used to build new efficient and intelligent energy power systems. [ABSTRACT FROM AUTHOR]

After the implementation of the ultra-low emissions regulation on the coal-fired power plants in China, the problem of the excessive ammonia-slipping from selective catalytic reduction (SCR) seems to be more severe. This paper analyzes the operating statistics of the coal-fired plants including 300 MW/600 MW/1000-MW units. Statistics data show that the phenomenon of the excessive ammonia-slipping is widespread. The average excessive rate is over 110%, while in the small units the value is even higher. A field test data of nine power plants showed that excessive ammonia-slipping at the outlet of SCR decreased following the flue-gas process. After most ammonia reduced by the dust collector and the wet flue-gas desulfurization (FGD), the ammonia emission at the stack was extremely low. At same time, a method based on probability distribution is proposed in this paper to describe the relationship between the NH3/NOX distribution deviation and the De–NOX efficiency/ammonia-slipping. This paper also did some original work to solve the ammonia-slipping problem. A real-time self-feedback ammonia injection technology using neural network algorithm to predict and moderate the ammonia distribution is proposed to decrease the NH3/NOX deviation and excessive ammonia-slipping. The technology is demonstrated in a 600-MW unit and works successfully. The excessive ammonia-slipping problem is well controlled after the implementation of the technology. [ABSTRACT FROM AUTHOR]

Wind power technology is developing rapidly in China. Especially in the north of China, decentralized wind power (DWP) has developed rapidly. However, wind curtailment exceeds 4% of the gross generation, which has become an important obstacle restricting the development of DWP in 2019. Technical schemes are effective solutions to promote decentralized wind power consumption (DWPC). Moreover, there are few economic analyses of DWP projects with key technologies. This paper summarizes the typical technical schemes and analyzes the economy of a DWP grid-connected project with typical technical schemes by combining methods of the net present value (NPV) and real options (RO). It appears that the DWP project can be profitable with an NPV of about CNY 4.3721 million and an option value of CNY 16.6022 million in the case of a feed-in tariff of 0.34 CNY/kWh. Feed-in tariff and equipment investment costs are the most relevant parameters for economic feasibility according to the sensitivity analysis. Furthermore, 30.73 million kWh connects to the Mengxi grid each year. The project has an annual maximum CO2 emission reduction of about 31 thousand tons and an SO2 of about 0.1 thousand tons. In addition, it also realizes fine social benefits, including the support of local residents and the improvement of local new urbanization levels. Finally, this paper puts forward policy suggestions for the development of DWP mainly from an economic point of view. [ABSTRACT FROM AUTHOR]

This paper aims to comprehensively analyze the relationship between energy price and green energy innovation in China, and first studies the impact of energy price on China's green energy innovation, then further investigates the moderating role of energy price distortion in the price–innovation relationship, especially in the context of lagging energy marketization level in the process of China's transition from planned economy to the market economy. Based on the data of 30 provinces in China from 2003 to 2017, this paper provides a measurement of green energy innovation capacity through the number of "alternative energy production" and "energy conservation" patents. Our results show that energy price has a significantly positive impact on China's green energy innovation, no matter the number of green energy patent applications or the number of green energy patent grants is used as the proxy of green energy innovation capacity. However, there exists heterogeneity related to the influence of energy price on green energy innovation. Specifically, energy price has a noticeable role in promoting green energy innovation in central and western China, but not in eastern China. Further research results show that energy price distortion significantly reduces the inducing effect of energy price on green energy innovation. Meanwhile, the distortion degrees of energy price in the central and western regions of China are significantly lower than that in the eastern region, which explains to a large extent why the inducing effect of energy price on innovation is more prominent in the central and western regions. [ABSTRACT FROM AUTHOR]

Air pollution has become an increasingly serious environmental problem in China. Especially in winter, the air pollution in northern China becomes even worse due to winter heating. The "coal to gas" policy, which uses natural gas to replace coal in the heating system in winter, was implemented in Beijing in the year 2013. However, the effects of this policy reform have not been examined. Using a panel dataset of 16 districts in Beijing, this paper employs a first difference model to examine the impact of the "coal to gas" policy on air quality. Strong evidence shows that the "coal to gas" policy has significantly improved the air quality in Beijing. On average, the "coal to gas" policy reduced sulfur dioxide ( SO 2 ), nitrogen dioxide ( NO 2 ), particulate matter smaller than 10 µm (PM10), particulate matter smaller than 2.5 µm (PM2.5) and carbon monoxide (CO) by 12.08%, 4.89%, 13.07%, 11.94% and 11.10% per year, respectively. We find that the "coal to gas" policy is more effective in areas with less energy use efficiency. The finding of this paper suggests that the government should continue to implement the "coal to gas" policy, so as to alleviate the air pollution in Beijing, China. [ABSTRACT FROM AUTHOR]

Interior decorating coatings (IDCs) are the heat-transfer medium between indoor air and building walls, which mainly form the cooling load and are important in an indoor built environment. To explore the impacts of the precooling process of IDCs on indoor thermal environment of occupants during intermittent air conditioning, this paper investigated the dynamic thermal response of IDCs. Three representative coating materials were integrated to the external insulation wall and internal insulation wall, and their interior surface temperatures were experimentally tested under intermittent air conditioning operation in southern China. Moreover, a heat transfer model was established and verified to analyze the influences of IDC on the thermal response of the interior surface. During the pull-down process, the cold was accumulated in the IDC layer with small thermal diffusivity and could not be transferred into the wall inside, so that the largest temperature reduction was obtained, meaning that the indoor thermal environment could meet the setpoint in a short time. According to modelling calculations, the thick IDC with volumetric specific heat capacity less than 1 × 105 J/(m3·K) and small thermal conductivity integrated to the internal insulation wall was beneficial to increase the thermal response rate and had the better energy-saving efficiency. [ABSTRACT FROM AUTHOR]

To cope with huge carbon emission pressure, China has implemented a carbon emissions trading pilot policy that aims to provide reasonable suggestions for the smooth operation of the national carbon market. This paper selects the provincial panel data in China from 2005 to 2019 and uses the propensity score matching-difference in difference (PSM-DID) method to evaluate the carbon emission policy's reduction effect. Based on carbon emissions (CE) and carbon emission intensity (CI), provinces and cities are divided into four regions, and each region is verified by spatial difference analysis. Furthermore, the mediating effects of carbon emission reduction through the dual aspects of technological progress and industry structure are also discussed. Results verified that, (1) under the carbon emission trading policy, regional carbon emissions and carbon emission intensity are both significantly reduced. (2) Technological progress helps to reduce carbon emissions, while industrial structure shows no obvious contribution. (3) The four regions all show ideal emission reduction effects, of which the High CE-High CI region shows the best, but is greatly restricted by techniques. The industrial structure of the High CE-Low CI region needs to be further optimized for carbon reduction. In the Low CE-High CI region, the carbon emissions brought by economic development fail to effectively improve per capita GDP. The Low CE-Low CI region contributes greatly to carbon emission reduction with technical advantages. [ABSTRACT FROM AUTHOR]

The demand for heating in cold regions drives up carbon emissions every year. In order to achieve China's carbon neutrality target by 2060, CO2 emissions in the cold regions must be reduced. In this paper, using Design Builder software, a simulation model of residential buildings in severe cold regions was created, and the most appropriate parameter design scheme for carbon emission reduction of residential buildings in severe cold regions was derived by simulating the experimental data of the original parameter design scheme and the changed parameter design scheme, as well as the calculation of carbon dioxide emission reduction rate. In order to make the comparison of the results easier, no change was made in the selection of the changed scheme for the external insulation material, foamed polystyrene panels. The results show that the most suitable parameter scheme for houses in severe cold regions is 85 mm thick foamed polystyrene panels for exterior walls, 200 mm thick foamed polystyrene panels for roofs, and exterior windows should use semi-tempered plastic steel frame and triple glass 6 mm glass + vacuum + 6 mm low-e glass + 12 mm air + 6 mm glass composed of windows. This technique saves 30.32% of energy as compared to the original parameter design approach. The efficiency of energy conservation is 33.03%. The emission reduction effect is significant. The best parametric design plan has a static payback period of 5 years. The best parametric design plan has a discounted payback period of 7 and a net present value of USD 65,413.39. This scheme can provide a great economic return while also increasing the performance of the building. [ABSTRACT FROM AUTHOR]

Energy saving and emission reduction have become common concerns in countries around the world. In China, with the implementation of the new strategy of "carbon peak and neutrality" and the rapid development of the new smart grid infrastructure, the amount of data of actual power grid dispatching and fault analysis show exponential growth, which has led to phenomena such as poor supervision effectiveness and difficulty in handling faults in the process of grid operation and maintenance. Existing research on retrieval recommendation methods has had a lower accuracy rate at cold-start due to a small sample of user interactions. In addition, the cumulative learning of user personalization during general retrieval results in a poor perception of potential interest. By constructing a power knowledge graph, this paper presents a power fault retrieval and recommendation model (PF2RM) based on user-polymorphic perception. This model includes two methods: the power fault retrieval method (PFR) and the user-polymorphic retrieval recommendation method (UPRR). First, we take the power grid fault dispatching business as the core and reconstruct the ontology layer of the power knowledge graph. The PFR method is used to design the graph-neighbor fault entity cluster to enhance the polymerization degree of a fault implementation scenario. This method can solve the search cold-start recommendation problem. At the same time, the UPRR method aims to form user retrieval subgraphs of the past-state and current-state and make a feature matching for the graph-neighbor fault entity cluster, and then realize the accurate prediction of the user's general search intention. The model is compared with other current classical models through the evaluation of multiple recommendation evaluation metrics, and the experimental results show that the model has a 3–8% improvement in the cold-start recommendation effect and 2–10% improvement in regular retrieval. The model has the best average recommendation performance in multiple metrics and has good results in fault analysis and retrieval recommendation. It plays a helpful role in intelligent operation and maintenance of the power grid and auxiliary decision-making, and effectively improves the reliability of the power grid. [ABSTRACT FROM AUTHOR]

It is imperative to use clean energy in order to achieve "carbon neutrality" and "carbon peaking". This research aims to explore the impact of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level on the utilization of high-quality straw energy, and, resultingly, this study aims to help provide suggestions for promoting high-quality straw energy utilization, develop the potential of high-quality straw energy, and alleviate China's energy shortage problem. This paper develops a measurement model using the ridge regression model with panel fixed effects, which overcomes the multi-collinearity problem among the various factors influencing the utilization of high-quality energy from straw. Panel data from 24 provinces and cities, from 2009 to 2017, are used. The results show that the improvements of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level all promote the use of high-quality straw energy. Moreover, the level of rural economic development plays a mediating role in the agricultural mechanization level and the rural infrastructure construction level pertaining to straw-based high-quality energy. Policy implications can be easy to derive based on our findings, and these include strengthening governmental investment in agricultural machinery in rural areas, paying more attention to areas with backward rural energy infrastructure construction, ensuring the steady improvement of economic development in rural areas, providing the necessary economic foundation for agricultural supply, and promoting the use of high-quality energy from straw. [ABSTRACT FROM AUTHOR]

Knowledge learning is a vital pre-factor and the driving force of green enterprise innovation; hence, meriting the numerous academic research and accumulated relevant literature. In this paper, the meta-analysis methodology was used to explore the direction and intensity of the influence of knowledge learning on green enterprise innovation, taking 32 independent documents as research samples. Meta-analysis results showed that the search breadth and the search depth of green resources and the green resources absorption and integration have significant positive effects on the green innovation of enterprises, among which green resources absorption and integration were the most important. Further, the research on the moderating effect found that the measurement method of green innovation affected the relationship between knowledge learning and green enterprise innovation; however, the moderating effect of the research object was not pronounced. [ABSTRACT FROM AUTHOR]

In China, with the increasing permeability of wind power, the power supply capacity is enough overall, but has shortage in partial-time. During peak hours, the capability of wind power consumption is poor and the power balance becomes more difficult. In order to maximize the utilization of wind power, the net loads are chosen as the response objectives, which contain significant uncertainties and have no probabilistic distribution characteristics. Under the traditional day-ahead power dispatch mode with fixed length time intervals and in the regions with insufficient hydroelectricity, the thermal generators take charge of the peak-load shaving. The frequent adjustments of thermal power output affect the system operation safety, economic benefits, and environmental benefits. Thus, a time-interval-varying optimal power dispatch strategy based on net load time-series characteristics is proposed in this paper. The net loads respond differently to intervals. The length of each time interval is determined based on the net load time-series characteristics analyzed by random matrix theory. The dispatch mode in each time interval is determined according to the characteristic quantification index calculated by the empirical modal decomposition and sample entropy. The proposed strategy and method can extend the continuous and stable operation time of the thermal generators, reduce the coal consumption caused by the ramping operation, and improve the safety, stability, and economy of the system. Furthermore, the proposed dispatch mode is environmentally friendly with reduced environmental cost and increased carbon credits. An actual provincial power grid in northeast China is taken as the example to verify the rationality and effectiveness of the proposed method and strategy. [ABSTRACT FROM AUTHOR]

As a major technical route to utilize biomass energy, biomass combustion power generation (BCPG) has been shown to be of environmental and economic significance. According to the operating experience, the installed capacity has a decisive impact on the operation and economic return of BCPG projects. In China, an installed capacity of either 30 MW or 12 MW is often chosen for constructing a BCPG project. To explore which one is more suitable for China, this paper uses actual operating data to compare the operation performance and techno-economics of two representative BCPG projects with an installed capacity of 30 MW and 12 MW. The results show that the operation situation and electricity production of the 30 MW project are better than those of the 12 MW project. The 30 MW project has a lower biomass consumption than the 12 MW project to produce per unit of electricity. The Internal Rate of Return (IRR) of the 30 MW project is greater than the industry benchmark in China and is almost three times the IRR of the 12 MW project. Therefore, it is recommended to construct BCPG projects with installed capacity of 30 MW in China. [ABSTRACT FROM AUTHOR]

The mining industry plays an extremely important strategic role in China's economic and social development. In the new era of pursuing circular/green/efficient development, the evaluation of the total factor environmental efficiency (TFEE) of China's mining industry is essential for alleviating resource waste and environmental pollution. The Epsilon-Based Measure (EBM) model effectively solves the shortcomings of radial and non-radial DEA models. In addition, the Malmquist–Luenberger (ML) index can measure the dynamic change of efficiency value. Combining the EBM model and the ML productivity index, this paper evaluates the TFEE from the static and dynamic perspective in China's 31 provincial mining industries over the period 2007–2016. The Theil index is employed to reveal the root of the overall provincial TFEE gap (OGTFEE) in China's mining industry. The results show that the average total factor static environmental efficiency (TFSEE) of China's provincial mining industry exhibits a low score of 0.6589 and with significant spatio-temporal differences. The provincial TFEE gap within four major areas (WGTFEE), especially that in east and west areas, is the main cause of the OGTFEE in China's mining industry. Technical change contributes more to the TFEE decline in China's mining industry. There are differences in improving the TFEE among China's 31 provincial mining industries, and corresponding countermeasures can be formulated accordingly. This study provides theoretical and practical basis for the clean and green development of China's mining industry. [ABSTRACT FROM AUTHOR]

In order to implement the national need for the optimal allocation of power resources, power load forecasting, as an important research topic, has important theoretical and practical significance. The purpose of this study is to construct a prediction model considering climate factors based on a large amount of historical data, and to prove that the prediction accuracy is related to both climate factors and load regularity. The results of load forecasting are affected by many climate factors, so firstly the climate variables affecting load forecasting are screened. Secondly, a load prediction model based on the IPSO-Elman network learning algorithm is constructed by taking the difference between the predicted value of the neural network and the actual value as the fitness function of particle swarm optimization. In view of the great influence of weights and thresholds on the prediction accuracy of the Elman neural network, the particle swarm optimization algorithm (PSO) is used to optimize parameters in order to improve the prediction accuracy of ELMAN neural network. Thirdly, prediction with and without climate factors is compared and analyzed, and the prediction accuracy of the model compared by using cosine distance and various error indicators. Finally, the stability discriminant index of historical load regularity is introduced to prove that the accuracy of the prediction model is related to the regularity of historical load in the forecast area. The prediction method proposed in this paper can provide reference for power system scheduling. [ABSTRACT FROM AUTHOR]

In response to extreme climate change, China has set a goal of reaching emission peak by 2030 and achieving carbon neutrality by 2050. Energy conservation and emission reduction of building heating in northern China are key to achieving this goal. Based on building area prediction and energy consumption intensity, this paper establishes a model for calculating heating energy consumption and carbon emissions in northern residential buildings at the macro level, which provides a basis for formulating policies related to heating and emission reduction in northern buildings. Based on the research method of scenario projection, combining the carbon emission subsets and future heating energy mix projections in northern China, the heating energy consumption in northern China decreases to 175, 149 and 135 Mtce in 2050 under the baseline, medium control and strict control scenarios, respectively. The heating energy consumption in the northern region should be controlled at least under the medium control scheme. Under this scenario, building heating carbon emissions in the north could be reduced to 450 MtCO2 by 2050, or 280 MtCO2 if more stringent abatement technologies are adopted. In order to achieve this goal, a combination of energy-saving technologies must be used. The use of biomass and solar technologies should be emphasized in rural heating, while envelope renovation makes the greatest contribution to heating energy savings, with envelope renovation contributing up to 92 Mtce to urban heating. [ABSTRACT FROM AUTHOR]

With the reform of the power system in China, investments in power grid projects across the whole power system are increasing. However, there are various objectives to achieve in the investment decision processes of power grid projects, so the rational investments of a grid project can be seen as a multi-objective optimization problem. Meanwhile, these issues have rarely been studied at home and abroad, and this paper will fill this gap. As a result, this study critically analyzed the application of a multi-objective optimization model to power grid investment. Firstly, the objective factors of grid investments were explored, which were quantified through quantitative methods. Secondly, based on the characteristics of power grid investment, a multi-objective optimization model was established, and the assumptions and constraints of the model were presented. Finally, NSGA-II was used for solving the multi-objective optimization model. The results show that: (1) Multi-objective optimization models are suitable for the study of and deriving solutions for power grid investment by establishing suitable objective functions, assumptions and constraints, (2) According to the conventional steps of NSGA-II, suitable steps can be established to search for an optimal solution to the objective set of a power grid investment and (3) Due to the different concerns of different project scenarios, Pareto frontier solutions can be selected as the practical references of power grid projects. Therefore, the solution set makes the implementation scheme more flexible. [ABSTRACT FROM AUTHOR]

This paper analyzes the macro-economic impact of controlling fossil energy consumption in China by using a social accounting matrix framework. The empirical results show that, first, restricting the exploitation of fossil energy resources will lead to a decline in the output of other production activities, thereby reducing the factor income and the living standards of residents. Second, improving energy efficiency can promote increased output in other production sectors, and raise factor returns and residents' living standards. Third, raising the price of energy products will result in higher costs of the entire society. The stronger the dependence on the energy sector, the greater the increase in the industrial cost. Therefore, the government should increase investment in energy efficiency, keep to energy intensity constraints, restrict the extraction amount of energy resources, and reasonably control energy prices based on market environmental factors. [ABSTRACT FROM AUTHOR]

In this paper, the panel data of 30 provinces in China from 2011 to 2019 are analyzed by the spatial measure model and the threshold regression model. The results show that the air quality level is positively correlated with green finance, but there is no spatial effect. The spatial effect of the three influencing factors, including the degree of openness, the level of infrastructure, and the level of education, is the crowding-out effect. At the same time, variables such as human resource level, air quality, and infrastructure construction level all have threshold effects in the relationship between green finance and economic development. The research conclusions suggested that local governments at all levels should formulate policies according to the actual situation to promote the development of provinces' intensive, intelligent, and green development, and build a regionally-linked green finance development model, thereby promoting the improvement of green finance. [ABSTRACT FROM AUTHOR]

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

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