Through more than two months of trial operation,a heat recovery system, called broad-sense heatrecovery system, was put into operation in Shanghai Waigaoqiao Third Power Generation Corporation
Guangdong Province,as one of China’s fast-developing regions,an important manufacturing base,and one of the national first round low-carbon pilots,still faces many challenges in controlling its total energy consumpti...Guangdong Province,as one of China’s fast-developing regions,an important manufacturing base,and one of the national first round low-carbon pilots,still faces many challenges in controlling its total energy consumption.Coal dominates Guangdong’s energy consumption and remains the major source of CO_(2).Previous research on factors influencing energy consumption has lacked a systematic analysis both from supply side(factors related to scale,structure,and technologies)and demand side(investment,consumption,and trade).This paper develops the logarithmic mean Divisia index(LMDI)method that focuses on the supply side and the structural decomposition analysis(SDA)method that focuses on the demand side to systematically identify the key factors driving coal consumption in Guangdong.Results are as follows:(1)Supply side analysis indicates that economic growth has always been the most important factor driving coal consumption growth,while energy intensity is the most important constraining factor.Industrial structure and energy structure have different impacts on coal consumption control during different development phases.(2)Demand side analysis indicates that coal is consumed mainly for international exports,inter-provincial exports,fixed capital formation,and urban household.(3)Industries with the fastest coal consumption growth driven by final demand have experienced significant shifts.Increments in industrial sectors were mainly driven by inter-provincial exports and urban household consumption in recent years.(4)Research on energy consumption in subnational regions under China’s new development pattern of“dual circulation”should not only focus on exports in the context of economic globalization but also pay more attention to inter-provincial exports on the background of strengthened interregional connections.展开更多
In this paper,two wavelet neural network(WNN)frames which depend on Morlet wavelet function and Gaussian wavelet function were established.In order to improve the efficiency of model training,the momentum term was app...In this paper,two wavelet neural network(WNN)frames which depend on Morlet wavelet function and Gaussian wavelet function were established.In order to improve the efficiency of model training,the momentum term was applied to modify the weights and thresholds,and the output of the network was summed up by function transformation of output layer nodes.When the Gaussian Wavelet Neural Networks(GWNN)and Morlet Wavelet Neural Networks(MWNN)were applied to coal consumption rate(CCR)estimation in a thermal power plant,the results confirmed their potency in function approximation.In addition,the influence of learning rate on the models was also discussed through the orthogonal experiment.展开更多
China has rich coal deposits. According to statistics, the calculated deposits of coal in China are 4.4927 trillion tons, including 2.6704 trillion tons within the shallow depth of 1,000m under ground. Up to the end o...China has rich coal deposits. According to statistics, the calculated deposits of coal in China are 4.4927 trillion tons, including 2.6704 trillion tons within the shallow depth of 1,000m under ground. Up to the end of 1991, the proven deposits were 1.0033 trillion tons and the guaranteed deposits were 983.3 billion tons. The coal formed in China covers many periods. It spreads widely with complicated types,展开更多
Coal-fired power is the main power source and the biggest contributor to energy conservation in the past several decades in China.It is generally believed that advanced technology should be counted on for energy conse...Coal-fired power is the main power source and the biggest contributor to energy conservation in the past several decades in China.It is generally believed that advanced technology should be counted on for energy conservation.However,a review of the decline in the national average net coal consumption rate(NCCR)of China's coal-fired power industry along with its development over the past few decades indicates that the upgradation of the national unit capacity structure(including installing advanced production and phasing out backward production)plays a more important role.A quantitative study on the effect of the unit capacity structure upgradation on the decline in the national average NCCR suggests that phasing out backward production is the leading factor for the decline in the NCCR in the past decade,followed by the new installation,whose sum contributes to approximately 80%of the decline in the national average NCCR.The new installation has an effective affecting period of about 8 years,during which it would gradually decline from a relatively high value.Since the effect of phasing out backward production may remain at a certain degree given a continual action of phasing out backward capacity,it is suggested that the organized action of phasing out backward production should be insisted on.展开更多
文摘Through more than two months of trial operation,a heat recovery system, called broad-sense heatrecovery system, was put into operation in Shanghai Waigaoqiao Third Power Generation Corporation
基金National Key Research and Development Program(2019YFB2103101)Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(GML2019ZD0301)+2 种基金GDAS Special Project of Science and Technology Development(2020GDASYL-20200102002)GDAS Special Project of Science and Technology Development(2020GDASYL-20200301003)National Natural Science Foundation of China(41501144)。
文摘Guangdong Province,as one of China’s fast-developing regions,an important manufacturing base,and one of the national first round low-carbon pilots,still faces many challenges in controlling its total energy consumption.Coal dominates Guangdong’s energy consumption and remains the major source of CO_(2).Previous research on factors influencing energy consumption has lacked a systematic analysis both from supply side(factors related to scale,structure,and technologies)and demand side(investment,consumption,and trade).This paper develops the logarithmic mean Divisia index(LMDI)method that focuses on the supply side and the structural decomposition analysis(SDA)method that focuses on the demand side to systematically identify the key factors driving coal consumption in Guangdong.Results are as follows:(1)Supply side analysis indicates that economic growth has always been the most important factor driving coal consumption growth,while energy intensity is the most important constraining factor.Industrial structure and energy structure have different impacts on coal consumption control during different development phases.(2)Demand side analysis indicates that coal is consumed mainly for international exports,inter-provincial exports,fixed capital formation,and urban household.(3)Industries with the fastest coal consumption growth driven by final demand have experienced significant shifts.Increments in industrial sectors were mainly driven by inter-provincial exports and urban household consumption in recent years.(4)Research on energy consumption in subnational regions under China’s new development pattern of“dual circulation”should not only focus on exports in the context of economic globalization but also pay more attention to inter-provincial exports on the background of strengthened interregional connections.
基金Science and technology development plan of Jilin City(201464061)National Natural Science Foundation of China(51476025)the KEY Scientific and Technological Project of Jilin Province of China(20150203001SF).
文摘In this paper,two wavelet neural network(WNN)frames which depend on Morlet wavelet function and Gaussian wavelet function were established.In order to improve the efficiency of model training,the momentum term was applied to modify the weights and thresholds,and the output of the network was summed up by function transformation of output layer nodes.When the Gaussian Wavelet Neural Networks(GWNN)and Morlet Wavelet Neural Networks(MWNN)were applied to coal consumption rate(CCR)estimation in a thermal power plant,the results confirmed their potency in function approximation.In addition,the influence of learning rate on the models was also discussed through the orthogonal experiment.
文摘China has rich coal deposits. According to statistics, the calculated deposits of coal in China are 4.4927 trillion tons, including 2.6704 trillion tons within the shallow depth of 1,000m under ground. Up to the end of 1991, the proven deposits were 1.0033 trillion tons and the guaranteed deposits were 983.3 billion tons. The coal formed in China covers many periods. It spreads widely with complicated types,
基金China Postdoctoral Science Foundation (No.2017M620758)Special Funds of the National Natural Science Foundation of China(Grant No.L1522032)the Consulting Project of Chinese Academy of Engineering(No.2015-ZCQ-06).
文摘Coal-fired power is the main power source and the biggest contributor to energy conservation in the past several decades in China.It is generally believed that advanced technology should be counted on for energy conservation.However,a review of the decline in the national average net coal consumption rate(NCCR)of China's coal-fired power industry along with its development over the past few decades indicates that the upgradation of the national unit capacity structure(including installing advanced production and phasing out backward production)plays a more important role.A quantitative study on the effect of the unit capacity structure upgradation on the decline in the national average NCCR suggests that phasing out backward production is the leading factor for the decline in the NCCR in the past decade,followed by the new installation,whose sum contributes to approximately 80%of the decline in the national average NCCR.The new installation has an effective affecting period of about 8 years,during which it would gradually decline from a relatively high value.Since the effect of phasing out backward production may remain at a certain degree given a continual action of phasing out backward capacity,it is suggested that the organized action of phasing out backward production should be insisted on.
