Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to p...Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand.In addition,proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network.As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman,new opportunities may arise considering the efficiency and reliability of the power system;like price-based demand response programs.These programs could either be a large scale for household,commercial or industrial users.However,excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure.Consequently,in this paper,an overview of the Oman regulatory regime,financial mechanism,price control,and distribution system security standard were presented.More so,the energy demand forecast in Oman was analysed,using the econometric model to forecasts its energy peak demand.The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters(by region,and by tariff),considering a case study of Mazoon Electricity Distribution Company(MZEC),which is one of the major power distribution companies in Oman,for effective energy demand in the power grid.展开更多
A large amount of waste liquids containing methanol/acetone/water mixtures are produced in the synthesis of methyl methacrylate(MMA).Under the advocacy of green chemical industry,it is urgent to develop an efficient,e...A large amount of waste liquids containing methanol/acetone/water mixtures are produced in the synthesis of methyl methacrylate(MMA).Under the advocacy of green chemical industry,it is urgent to develop an efficient,economic and energy-saving mixture separation process.Through thermodynamic azeotropic behavior and pressure sensitivity analysis,pressure-swing distillation was determined and the optimal separation pressure of each column in the process was obtained.Due to the composition of waste liquids produced were quite different in MMA production,the pressure-swing distillation separation process was designed to fully achieve the accurate waste liquids treatment.Taking the total annual cost(TAC)as the target,the sequential iteration method was used to optimize the process,and the impact of composition on economy was compared.In order to further realize the energy-saving of the separation process,the pervaporation membrane module was introduced to pretreat the waste liquid in the pressure-swing distillation.The results showed that the TAC of the coupling process was 46% higher than that of the pressure-swing distillation process,and the thermodynamic efficiency was 30% higher.This study provides waste liquid treatment technology for enterprises and analyzes its economic and energy efficiency,which has reference significance for the development of coupled separation technology.展开更多
This study focuses on a national regional coordinated development strategy and adopts China Multi-Regional Computable General Equilibrium model to analyze the economic and social development, energy demand, and carbon...This study focuses on a national regional coordinated development strategy and adopts China Multi-Regional Computable General Equilibrium model to analyze the economic and social development, energy demand, and carbon emissions of the provinces during the 14th Five-Year Plan (FYP, 2021 2025) period based on the economic development and energy demand since the New Normal. The main conclusions are the following: 1) Under the guidance of the regional coordinated development strategy, 13 provinces/municipalities are expected to have a per capita gross domestic product (GDP) of more than US$15,000, and 16 provinces/municipalities will have a per capita GDP of US$10,000 15,000. All provincial economies are expected to achieve steady and rapid development by the end of the 14th FYP. 2) The total energy consumption of the provinces is expected to reach 5.45 Gtce (excluding Tibet) in 2025, and the average annual growth rate is approximately 1.5%. The growth of energy demand will remain in low speed. The key point of energy demand will gradually shift from the eastern to the middle area, while the proportion of energy use in the western provinces will remain stable, which is consistent with the economic development stage and regional coordinated development strategy. 3) The annual average carbon intensity (mainly considering carbon emissions from energy use) of the provinces will approximately with most provinces dropping by over 4.0%. The trend of a considerable decline in carbon intensity, as observed in recent years, is expected to continue.展开更多
In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the mod...In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).展开更多
An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting result...An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization,and technological progress as the input variables. On the basis of historical annual data from1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.展开更多
"Economic transformation"has become the main path to promote China's social and economic development,and many regions have increased the importance and attention to"economic transformation",and..."Economic transformation"has become the main path to promote China's social and economic development,and many regions have increased the importance and attention to"economic transformation",and the Southwest region is no exception.Many cities in Southwest China are developing new energy sources to promote economic development and economic transformation.Economic transformation and economic development in Southwest China are mutually influencing and interacting,while energy development in Southwest China and its local economic development are mutually promoting and influencing,so economic transformation also affects energy demand and development in Southwest China.The importance of economic transformation should be taken into consideration.展开更多
A quantitative model was applied to analyze the energy demand and CO2 emissions in China following the Energy Production and Consumption Revolution Strategy(2016e2030)and long-term economic and social development targ...A quantitative model was applied to analyze the energy demand and CO2 emissions in China following the Energy Production and Consumption Revolution Strategy(2016e2030)and long-term economic and social development target China Dream.Results showed that 1)toward the 2050 China Dream target,total final energy consumption is expected to peak at 3.9 Gtce in 2030 and remain stable until 2050,whereas total primary energy consumption is expected to reach an upper platform by 2040 and around 5.8 Gtce by 2050;2)the proportion of non-fossil fuels is expected to reach approximately 50%and that of natural gas to reach more than 16%by 2050;3)CO2 emissions from energy use are expected to peak at 9.6 Gt by no later than 2030 and then gradually decline to 6.7 Gt by 2050.展开更多
This paper takes the climate change and low carbon economy development as the study background, based on the analysis of energy demand and carbon emissions status, which is aimed to provide the low carbon development ...This paper takes the climate change and low carbon economy development as the study background, based on the analysis of energy demand and carbon emissions status, which is aimed to provide the low carbon development path in Chinese cities. The method of scenario analysis can be used to predict long-term strategy for the uncertainty future development, and it was introduced to the field of social forecasting and public policy research, such as the environmental strategic planning, policy analysis, and support of decision in resource management, which can be used to explore the possible development trend and target of the results from the macro perspective. Scenario analysis has been gradually applied to the study area on low carbon economy, energy forecasting and other fields in recent years, and there have been many research results in different aspects. This paper takes the scenario analysis as basic study theory, spreading out the present situation of its application in low carbon city and some issues that need further study. As a tool for predicting the future development in low carbon city, the method of scenario analysis has been providing a powerful reference for policies and their executants.展开更多
Based on the modern economic theory and the characteristics of China’s energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China’s energy demand model, and examines the lo...Based on the modern economic theory and the characteristics of China’s energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China’s energy demand model, and examines the long-run relationship between China’s aggregate energy consumption and the main economic variables such as GDP by using the Johansen multivariate approach. It is found that there exists unique long-run relationship among the variables in the model over the sampling period. An error-correction model provides an appropriate framework for forecasting the short-run fluctuations in the aggregate demand of China.展开更多
The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of...The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of energy, economy, environment and social development. The total energy demand in 2050 will reach 4.4~ 5.4 billion tce. It is shown in energy supply analysis that coal is China’s major energy in primary energy supply. The share of CO2 emission in the future Chinese energy system will be out of proportion to its energy consumption share because of the high persentage of coal to be consumed. It will reach about 27%. The nuclear option which would replace 30.7% of coal in the total primary energy supply will reduce the share by 9.8%. So the policy considerations on the future Chinese energy system is of great importance to the global CO2 issues.展开更多
Steel production remains an energy-intensive industry in a world where there is an ever-increasing emphasis on lowering energy costs,reducing greenhouse gas emissions,ensuring environmental compliance,and improving pr...Steel production remains an energy-intensive industry in a world where there is an ever-increasing emphasis on lowering energy costs,reducing greenhouse gas emissions,ensuring environmental compliance,and improving production rates.As the growth in demand for speciality steels continues its steady increase,and new market opportunities for ever higher steel performance appear,significant global attention is focused on secondary steel processing,and on the VD,VOD and RH processes.One new technology is able to address all of these issues and concerns together-the integrated ladle tank vacuum degassing station equipped with the new modular mechanical vacuum pumping systems.This paper will examine the economic and environmental benefits, operational characteristics,and recent results provided by such steel degassing installations.展开更多
Climate change is regarded as the greatest threat to society in the coming years, and directly affects the water industry;with changes in temperature, rainfall intensities and sea levels resulting in increased treatme...Climate change is regarded as the greatest threat to society in the coming years, and directly affects the water industry;with changes in temperature, rainfall intensities and sea levels resulting in increased treatment and subsequent energy costs. As one of the largest global consumers of energy, the water industry has the opportunity to significantly prevent climate change by reducing energy usage and subsequent carbon footprints. Wastewater treatment alone requires an estimated 1% - 3% of a country overall energy output while producing 1.6% of its global greenhouse gas emissions;over 75% of which can be due to the collection system. Gravity flows should therefore be incorporated where possible, reducing pumping requirements and therefore minimizing costs and subsequent carbon footprints. This study has assessed the operational energy usage of the alternative collection systems low pressure and vacuum, for use in situations in which a conventional gravity system is not practicable. This was carried out through hypothetical scenario testing using design parameters derived from literature, generating 60 hypothetical collection mains with variations in population, static head and main length. From this study, it was found that the energy demand of a low pressure system is 3.2 - 4.2 times greater than that of its equivalent vacuum system in the same scenario. Energy demand for both systems increases with population, static head and main length. However, population and therefore flow changes were found to have the greatest effect on the energy usage of both systems. Therefore, flow reduction measures should be adopted if the decarbonization of the water industry is to be achieved.展开更多
This research highlights an interesting finding comparing energy use in the residential sector in the United Kingdom and Australia. Energy consumed per capita is largely similar, however the energy available is manife...This research highlights an interesting finding comparing energy use in the residential sector in the United Kingdom and Australia. Energy consumed per capita is largely similar, however the energy available is manifestly different. Australia is blessed with a greater abundance of energy than the United Kingdom. Particularly, in the main area of study in Australia, Victoria state, Brown coal is easy and cheap to access. It is therefore politically more difficult to argue that the population affords more expensive sustainable energy resources even though Australia is one of the countries that can readily produce this type of energy. Britain, however, is a net importer of energy. A large proportion of this energy is natural gas which is a fossil fuel, and therefore contributes to the negative effects of climate change. The findings of this research focus on what motivates residential users of energy to use energy more sustainably. It presents the conclusions of previous research as a backdrop, and reveals the complexity of occupant behaviour. Key drivers are financial incentives and the role of large organisations such as governments in influ-encing behaviour. This may take significant time.展开更多
The building sector is one of the main energy-consuming sectors in Morocco.In fact,it accounts for 33%of the final consumption of energy and records a high increase in the annual consumption of energy caused by furthe...The building sector is one of the main energy-consuming sectors in Morocco.In fact,it accounts for 33%of the final consumption of energy and records a high increase in the annual consumption of energy caused by further planned large-scale projects.Indeed,the energy consumption of the building sector is experiencing a significant acceleration justified by the rapid need for the development of housing stock,wich is estimated at an average increase of 1,5%per year;furthermore,tant is an estimated increase of about 6,4%.In this sense,building constitutes an important potential source for rationalizing both energy consumption and energy savings through the adoption of energy efficiency measures.Energy consumption control efforts in the residential building sector involve socio-economic,technological,and environmental concerns that require sophisticated research.Indeed,different types of quantitative models have been developed and examined so as to find a solution for the optimizing energy consumption.In this work,we have highlighted the importance of using solar heaters to reduce energy demand in terms of the use of domestic hot water.To do this,we have defined the needs and characteristics of a solar installation of a residential building located in Casablanca through a calculating tool“SOLO 2000”in addition to the use of multiple linear regression analysis to deduct the impact of irradiation and solar contributions on the energy demand of the solar installation.展开更多
Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model establishe...Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model established in the paper. The energy consumptions in Germany, Japan and other developed countries are analyzed and compared with the energy consumption in China. Environmental friendly scenario of energy demand and CO2 emissions for sustainable China has been formed based on the results of comparison. Under environmen- tal friendly scenario, the primary energy consumption will be 4.31 billion ton coal equivalence (tce) and CO2 emissions will be 1.854 billion t-c in 2050; energy per capital will be 3.06 tce that is 1.8 times of energy consumed in 2005 in China and 51% of consumed energy per capital in Japan in 2003. In 2050, the energy requirement of unit GDP will be 20% lower than that of Germany in 2003, but will be still 37% higher than that in Japan in 2003. It is certain that to fulfill the environmental friendly Scenario of energy demand and CO2 emissions is a difficult task and it needs long term efforts of the whole so- ciety, not only in production sectors but also in service and household sectors.展开更多
Household energy demand is among the prime problems that cause deforestation. The use of fuel wood in the developing countries of Africa, Asia and Latin America is be-lieved to play a key role for the razing of forest...Household energy demand is among the prime problems that cause deforestation. The use of fuel wood in the developing countries of Africa, Asia and Latin America is be-lieved to play a key role for the razing of forests and the degradation of associated biodiversity and other land resources. High population growth, increased energy demand, urbanization, infrastructure development, etc. are among the factors that exacerbate the current rate of deforestation in Ethiopia. This growing demand is also posing a threat to the remaining natural capital and associated wildlife of the country’s national parks. NechSar national park, a jewel in the Rift Valley of Ethiopia is not in different to this threat. The issue is calling for an urgent interference in the provision of environment friendly energy sources, afforestation programmes, raising the level of awareness on climate change, etc. This study is therefore, aimed at exploring the level of household energy demand interference on the woody vegetation of NechSar Park and promoting the use of environment friendly and energy saving technologies in the vicinity of the park area and beyond.展开更多
With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Eva...With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).展开更多
With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage co...With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.展开更多
In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a sma...In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.展开更多
文摘Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand.In addition,proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network.As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman,new opportunities may arise considering the efficiency and reliability of the power system;like price-based demand response programs.These programs could either be a large scale for household,commercial or industrial users.However,excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure.Consequently,in this paper,an overview of the Oman regulatory regime,financial mechanism,price control,and distribution system security standard were presented.More so,the energy demand forecast in Oman was analysed,using the econometric model to forecasts its energy peak demand.The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters(by region,and by tariff),considering a case study of Mazoon Electricity Distribution Company(MZEC),which is one of the major power distribution companies in Oman,for effective energy demand in the power grid.
基金supported by the National Natural Science Foundation of China(22078166)。
文摘A large amount of waste liquids containing methanol/acetone/water mixtures are produced in the synthesis of methyl methacrylate(MMA).Under the advocacy of green chemical industry,it is urgent to develop an efficient,economic and energy-saving mixture separation process.Through thermodynamic azeotropic behavior and pressure sensitivity analysis,pressure-swing distillation was determined and the optimal separation pressure of each column in the process was obtained.Due to the composition of waste liquids produced were quite different in MMA production,the pressure-swing distillation separation process was designed to fully achieve the accurate waste liquids treatment.Taking the total annual cost(TAC)as the target,the sequential iteration method was used to optimize the process,and the impact of composition on economy was compared.In order to further realize the energy-saving of the separation process,the pervaporation membrane module was introduced to pretreat the waste liquid in the pressure-swing distillation.The results showed that the TAC of the coupling process was 46% higher than that of the pressure-swing distillation process,and the thermodynamic efficiency was 30% higher.This study provides waste liquid treatment technology for enterprises and analyzes its economic and energy efficiency,which has reference significance for the development of coupled separation technology.
基金s This work was supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology (2016YFA0602601), Science and Technology Project of the State Grid Corporation of China Headquarters ''Research and Development of China Multi-regional Compre hensive Analysis and Forecast Mcxlel System for Energy Sup ply and Demand Fourth National Climate Assessment Report: Mitigation of Climate Change’’, and National Natural Science Foundation of China Program (71573145, 71573062).
文摘This study focuses on a national regional coordinated development strategy and adopts China Multi-Regional Computable General Equilibrium model to analyze the economic and social development, energy demand, and carbon emissions of the provinces during the 14th Five-Year Plan (FYP, 2021 2025) period based on the economic development and energy demand since the New Normal. The main conclusions are the following: 1) Under the guidance of the regional coordinated development strategy, 13 provinces/municipalities are expected to have a per capita gross domestic product (GDP) of more than US$15,000, and 16 provinces/municipalities will have a per capita GDP of US$10,000 15,000. All provincial economies are expected to achieve steady and rapid development by the end of the 14th FYP. 2) The total energy consumption of the provinces is expected to reach 5.45 Gtce (excluding Tibet) in 2025, and the average annual growth rate is approximately 1.5%. The growth of energy demand will remain in low speed. The key point of energy demand will gradually shift from the eastern to the middle area, while the proportion of energy use in the western provinces will remain stable, which is consistent with the economic development stage and regional coordinated development strategy. 3) The annual average carbon intensity (mainly considering carbon emissions from energy use) of the provinces will approximately with most provinces dropping by over 4.0%. The trend of a considerable decline in carbon intensity, as observed in recent years, is expected to continue.
基金supported by the Fundamental Research Funds for the Central Universities[Grant No.JBK1507159]
文摘In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).
文摘An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization,and technological progress as the input variables. On the basis of historical annual data from1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.
文摘"Economic transformation"has become the main path to promote China's social and economic development,and many regions have increased the importance and attention to"economic transformation",and the Southwest region is no exception.Many cities in Southwest China are developing new energy sources to promote economic development and economic transformation.Economic transformation and economic development in Southwest China are mutually influencing and interacting,while energy development in Southwest China and its local economic development are mutually promoting and influencing,so economic transformation also affects energy demand and development in Southwest China.The importance of economic transformation should be taken into consideration.
基金We thank National Key R&D Program of China(2016YFA0602601),National Natural Science Foundation of China(71573062),China Energy Modeling Forum(CEMF),for support of the study.
文摘A quantitative model was applied to analyze the energy demand and CO2 emissions in China following the Energy Production and Consumption Revolution Strategy(2016e2030)and long-term economic and social development target China Dream.Results showed that 1)toward the 2050 China Dream target,total final energy consumption is expected to peak at 3.9 Gtce in 2030 and remain stable until 2050,whereas total primary energy consumption is expected to reach an upper platform by 2040 and around 5.8 Gtce by 2050;2)the proportion of non-fossil fuels is expected to reach approximately 50%and that of natural gas to reach more than 16%by 2050;3)CO2 emissions from energy use are expected to peak at 9.6 Gt by no later than 2030 and then gradually decline to 6.7 Gt by 2050.
文摘This paper takes the climate change and low carbon economy development as the study background, based on the analysis of energy demand and carbon emissions status, which is aimed to provide the low carbon development path in Chinese cities. The method of scenario analysis can be used to predict long-term strategy for the uncertainty future development, and it was introduced to the field of social forecasting and public policy research, such as the environmental strategic planning, policy analysis, and support of decision in resource management, which can be used to explore the possible development trend and target of the results from the macro perspective. Scenario analysis has been gradually applied to the study area on low carbon economy, energy forecasting and other fields in recent years, and there have been many research results in different aspects. This paper takes the scenario analysis as basic study theory, spreading out the present situation of its application in low carbon city and some issues that need further study. As a tool for predicting the future development in low carbon city, the method of scenario analysis has been providing a powerful reference for policies and their executants.
文摘Based on the modern economic theory and the characteristics of China’s energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China’s energy demand model, and examines the long-run relationship between China’s aggregate energy consumption and the main economic variables such as GDP by using the Johansen multivariate approach. It is found that there exists unique long-run relationship among the variables in the model over the sampling period. An error-correction model provides an appropriate framework for forecasting the short-run fluctuations in the aggregate demand of China.
文摘The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of energy, economy, environment and social development. The total energy demand in 2050 will reach 4.4~ 5.4 billion tce. It is shown in energy supply analysis that coal is China’s major energy in primary energy supply. The share of CO2 emission in the future Chinese energy system will be out of proportion to its energy consumption share because of the high persentage of coal to be consumed. It will reach about 27%. The nuclear option which would replace 30.7% of coal in the total primary energy supply will reduce the share by 9.8%. So the policy considerations on the future Chinese energy system is of great importance to the global CO2 issues.
文摘Steel production remains an energy-intensive industry in a world where there is an ever-increasing emphasis on lowering energy costs,reducing greenhouse gas emissions,ensuring environmental compliance,and improving production rates.As the growth in demand for speciality steels continues its steady increase,and new market opportunities for ever higher steel performance appear,significant global attention is focused on secondary steel processing,and on the VD,VOD and RH processes.One new technology is able to address all of these issues and concerns together-the integrated ladle tank vacuum degassing station equipped with the new modular mechanical vacuum pumping systems.This paper will examine the economic and environmental benefits, operational characteristics,and recent results provided by such steel degassing installations.
文摘Climate change is regarded as the greatest threat to society in the coming years, and directly affects the water industry;with changes in temperature, rainfall intensities and sea levels resulting in increased treatment and subsequent energy costs. As one of the largest global consumers of energy, the water industry has the opportunity to significantly prevent climate change by reducing energy usage and subsequent carbon footprints. Wastewater treatment alone requires an estimated 1% - 3% of a country overall energy output while producing 1.6% of its global greenhouse gas emissions;over 75% of which can be due to the collection system. Gravity flows should therefore be incorporated where possible, reducing pumping requirements and therefore minimizing costs and subsequent carbon footprints. This study has assessed the operational energy usage of the alternative collection systems low pressure and vacuum, for use in situations in which a conventional gravity system is not practicable. This was carried out through hypothetical scenario testing using design parameters derived from literature, generating 60 hypothetical collection mains with variations in population, static head and main length. From this study, it was found that the energy demand of a low pressure system is 3.2 - 4.2 times greater than that of its equivalent vacuum system in the same scenario. Energy demand for both systems increases with population, static head and main length. However, population and therefore flow changes were found to have the greatest effect on the energy usage of both systems. Therefore, flow reduction measures should be adopted if the decarbonization of the water industry is to be achieved.
文摘This research highlights an interesting finding comparing energy use in the residential sector in the United Kingdom and Australia. Energy consumed per capita is largely similar, however the energy available is manifestly different. Australia is blessed with a greater abundance of energy than the United Kingdom. Particularly, in the main area of study in Australia, Victoria state, Brown coal is easy and cheap to access. It is therefore politically more difficult to argue that the population affords more expensive sustainable energy resources even though Australia is one of the countries that can readily produce this type of energy. Britain, however, is a net importer of energy. A large proportion of this energy is natural gas which is a fossil fuel, and therefore contributes to the negative effects of climate change. The findings of this research focus on what motivates residential users of energy to use energy more sustainably. It presents the conclusions of previous research as a backdrop, and reveals the complexity of occupant behaviour. Key drivers are financial incentives and the role of large organisations such as governments in influ-encing behaviour. This may take significant time.
文摘The building sector is one of the main energy-consuming sectors in Morocco.In fact,it accounts for 33%of the final consumption of energy and records a high increase in the annual consumption of energy caused by further planned large-scale projects.Indeed,the energy consumption of the building sector is experiencing a significant acceleration justified by the rapid need for the development of housing stock,wich is estimated at an average increase of 1,5%per year;furthermore,tant is an estimated increase of about 6,4%.In this sense,building constitutes an important potential source for rationalizing both energy consumption and energy savings through the adoption of energy efficiency measures.Energy consumption control efforts in the residential building sector involve socio-economic,technological,and environmental concerns that require sophisticated research.Indeed,different types of quantitative models have been developed and examined so as to find a solution for the optimizing energy consumption.In this work,we have highlighted the importance of using solar heaters to reduce energy demand in terms of the use of domestic hot water.To do this,we have defined the needs and characteristics of a solar installation of a residential building located in Casablanca through a calculating tool“SOLO 2000”in addition to the use of multiple linear regression analysis to deduct the impact of irradiation and solar contributions on the energy demand of the solar installation.
文摘Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model established in the paper. The energy consumptions in Germany, Japan and other developed countries are analyzed and compared with the energy consumption in China. Environmental friendly scenario of energy demand and CO2 emissions for sustainable China has been formed based on the results of comparison. Under environmen- tal friendly scenario, the primary energy consumption will be 4.31 billion ton coal equivalence (tce) and CO2 emissions will be 1.854 billion t-c in 2050; energy per capital will be 3.06 tce that is 1.8 times of energy consumed in 2005 in China and 51% of consumed energy per capital in Japan in 2003. In 2050, the energy requirement of unit GDP will be 20% lower than that of Germany in 2003, but will be still 37% higher than that in Japan in 2003. It is certain that to fulfill the environmental friendly Scenario of energy demand and CO2 emissions is a difficult task and it needs long term efforts of the whole so- ciety, not only in production sectors but also in service and household sectors.
文摘Household energy demand is among the prime problems that cause deforestation. The use of fuel wood in the developing countries of Africa, Asia and Latin America is be-lieved to play a key role for the razing of forests and the degradation of associated biodiversity and other land resources. High population growth, increased energy demand, urbanization, infrastructure development, etc. are among the factors that exacerbate the current rate of deforestation in Ethiopia. This growing demand is also posing a threat to the remaining natural capital and associated wildlife of the country’s national parks. NechSar national park, a jewel in the Rift Valley of Ethiopia is not in different to this threat. The issue is calling for an urgent interference in the provision of environment friendly energy sources, afforestation programmes, raising the level of awareness on climate change, etc. This study is therefore, aimed at exploring the level of household energy demand interference on the woody vegetation of NechSar Park and promoting the use of environment friendly and energy saving technologies in the vicinity of the park area and beyond.
基金supported by The Indian Institute of Technology-Bombay(Institute Postdoctoral Fellowship-AO/Admin-1/Rect/33/2019).
文摘With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).
基金supported by Science and Technology Project of SGCC(SGSW0000FZGHBJS2200070)。
文摘With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.
文摘In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.
