Abstract: Energy consumption of a hotel can be a hot topic in
smart city; it is difficult to evaluate the contribution of impact factors
to energy consumption of a hotel. Therefore, grasping the key impact
factors has great effect on the energy saving management of a hotel.
Based on the SPIRTPAT model, we establish the identity with the
impact factors of occupancy rate, unit area of revenue, temperature
factor, unit revenue of energy consumption. In this paper, we use the
LMDI (Logarithmic Mean Divisia Index) to decompose the impact
factors of energy consumption of hotel from Jan. to Dec. in 2001. The
results indicate that the occupancy rate and unit area of revenue are the
main factors that can increase unit area of energy consumption, and the
unit revenue of energy consumption is the main factor to restrain the
growth of unit area of energy consumption. When the energy
consumption of hotel can appear abnormal, the hotel manager can
carry out energy saving management and control according to the
contribution value of impact factors.
Abstract: The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.
Abstract: This paper presents a method of economic factorial analysis of the CO2 emissions based on the extension of the Divisia index to interconnected factors. This approach, contrary to the Kaya identity, considers three main factors of the CO2 emissions: gross domestic product, energy consumption, and population - as equally important, and allows for accounting of all of them simultaneously. The three factors are included into analysis together with their carbon intensities that allows for obtaining a comprehensive picture of the change in the CO2 emissions. A computer program in R-language that is available for free download serves automation of the calculations. A case study of the U.S. carbon dioxide emissions is used as an example.