Ming Meng

A Small-Sample Adaptive Hybrid Model for Annual Electricity Consumption Forecasting

Annual electricity consumption forecasting is one of the important foundations of power system planning. Considering that the long-term electricity consumption curves of developing countries usually present approximately exponential growth trends and linear and accelerated growth rate trends may also appear in certain periods, this paper first proposes a small-sample adaptive hybrid model (AHM) to extrapolate the above curves. The iterative trend extrapolation equation of the proposed model can simulate the linear, exponential, and steep trends adaptively at the same time. To estimate the equation parameters using small samples, the partial least squares (PLS) and iteration starting point optimization algorithms are suggested. To evaluate forecasting performance, the artificial neural network (ANN), grey model (GM), and AHM are used to forecast electricity consumption in China from 1991 to 2014, and then the results of these models are compared. Analysis of the forecasting results shows that the AHM can overcome stochastic changes and respond quickly to changes in the main electricity consumption trend because of its specialized equation structure. Overall error analysis indicators also show that AHM often obtains more precise forecasting results than the other two models.

Sensitivity and trend analysis of carbon emissions embodied in China's international trade with input-output technique and nonhomogeneous exponential growth model

This paper provides a quantitative analysis of the sensitivity, amount, and the development trend of carbon emissions embodied in Chinas international trade. With the input-output technique, nonhomogeneous exponential growth model, and carbon transmission-relative data, the following conclusions were drawn: (a) The total (direct and indirect) carbon intensity of each industrial sector was measured. Of all the 27 industrial sectors, Production and Supply of Electric Power and Heat Power ranks first. Because of the large consumption of electric power by nearly all the industrial sectors, encouraging the electric power sectors to utilize non-fossil energy (especially wind and photovoltaics), to improve the generation efficiency, and to import electric power overseas is crucial for decreasing the overall level of Chinas carbon intensity. (b) The amount of carbon transmission embodied in exports and imports of each industrial sector was also measured. Owing to its enormous international trade values, the sector of Manufacture of Electrical Machinery and Equipment ranks first, with absolute predominance in both exports and imports. Adjusting Chinas industrial policy to decrease the net export of this sector would significantly reduce the amount of net carbon transmission in the country. (c) The future net carbon transmission of each industrial sector was forecasted. Trend analysis indicates that changes in the overall international trade situation would cause the carbon transmission amount embodied in exports in China to become less than that embodied in imports since 2015.