After analyzing the working condition of the conventional diesel forklift,an energy recovery system in hybrid forklift is considered and its simulation model is built.Then,the control strategy for the proposed energy ...After analyzing the working condition of the conventional diesel forklift,an energy recovery system in hybrid forklift is considered and its simulation model is built.Then,the control strategy for the proposed energy recovery system is discussed,which is validated and evaluated by simulation.The simulation results show that the proposed control strategy can achieve balance of the power and keep the state of charge(SOC) of ultra capacitor in a reasonable range,and the fuel consumption can be reduced by about 20.8% compared with the conventional diesel forklift.Finally,the feasibility of the simulation results is experimentally verified based on the lifting energy recovery system.展开更多
According to the Energy Information Administration, average retail gasoline prices tend to typically be higher in certain states than in others. Aside from taxes, the factors shown to contribute to regional and even l...According to the Energy Information Administration, average retail gasoline prices tend to typically be higher in certain states than in others. Aside from taxes, the factors shown to contribute to regional and even local differences in gasoline prices include proximity of supply, supply disruptions, competition in the local market and environmental programs. Of interest in this paper is proximity of supply. It has been hypothesized that areas farthest from the Gulf Coast （the source of nearly half of the gasoline produced in the United States and, thus, a major supplier to the rest of the country） tend to have higher prices. To test this hypothesis, the paper assembles state level monthly retail gasoline data for the period 1983 to 2007 for five states with oil refineries （Alabama, Georgia, Texas, Mississippi and Louisiana） and five states without refineries （Arkansas, Tennessee, North Carolina, South Carolina and Florida）. The analysis employs dynamic correlation, regression, cointegration and vector autoregressive methods. Overall, the results show that retail gas prices in states with refineries and those without refineries tend to move in the same direction over time. The small differences observed over time may suggest that price shocks take a short time to be felt nationwide.展开更多
Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroe...Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.展开更多
基金Project(2013BAF07B02)supported by National Science and Technology Support Program of China
文摘After analyzing the working condition of the conventional diesel forklift,an energy recovery system in hybrid forklift is considered and its simulation model is built.Then,the control strategy for the proposed energy recovery system is discussed,which is validated and evaluated by simulation.The simulation results show that the proposed control strategy can achieve balance of the power and keep the state of charge(SOC) of ultra capacitor in a reasonable range,and the fuel consumption can be reduced by about 20.8% compared with the conventional diesel forklift.Finally,the feasibility of the simulation results is experimentally verified based on the lifting energy recovery system.
文摘According to the Energy Information Administration, average retail gasoline prices tend to typically be higher in certain states than in others. Aside from taxes, the factors shown to contribute to regional and even local differences in gasoline prices include proximity of supply, supply disruptions, competition in the local market and environmental programs. Of interest in this paper is proximity of supply. It has been hypothesized that areas farthest from the Gulf Coast （the source of nearly half of the gasoline produced in the United States and, thus, a major supplier to the rest of the country） tend to have higher prices. To test this hypothesis, the paper assembles state level monthly retail gasoline data for the period 1983 to 2007 for five states with oil refineries （Alabama, Georgia, Texas, Mississippi and Louisiana） and five states without refineries （Arkansas, Tennessee, North Carolina, South Carolina and Florida）. The analysis employs dynamic correlation, regression, cointegration and vector autoregressive methods. Overall, the results show that retail gas prices in states with refineries and those without refineries tend to move in the same direction over time. The small differences observed over time may suggest that price shocks take a short time to be felt nationwide.
文摘Reliable forecasts of the price of oil are of interest for a wide range of applications. For example, central banks and private sector forecasters view the price of oil as one of the key variables in generating macroeconomic projections and in assessing macroeconomic risks. Of particular interest is the question of the extent to which the price of oil is helpful in predicting recessions. This paper presents a statistical learning method （SLM） based on combined fuzzy system （FS）, artificial neural network （ANN）, and support vector regression （SVR） to cope with optimum long-term oil price forecasting in noisy, uncertain, and complex environments. A number of quantitative factors were discovered from this model and used as the input. For verification and testing, the West Texas Intermediate （WT1） crude oil spot price is used to test the effectiveness of the proposed learning methodology. Empirical results reveal that the proposed SLM-based forecasting can model the nonlinear relationship between the input variables and price very well. Furthermore, in-sample and out-of-sample prediction performance also demonstrates that the proposed SLM model can produce more accurate prediction results than other nonlinear models.
