Economia
& Energia
No 24 - Janeiro - Fevereiro 2000
ISSN 1518-2932
English Version Support:
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Economia
& Energia |
English Version |
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Energy Demand for the Domestic Sector Emission of Greenhouse Effect Gases in the Domestic Sector e&e’s methodology for the Energy Matrix Projection Emission Coefficients Matrix Calculation e&e
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PROJECTION OF ENERGY USE IN THE RESIDENTIAL SECTOR (Suite)ENERGY VIEW OF THE RESIDENTIAL SECTOR.The use of final; energy in the Sector has developed as shown in graphic 4. Both curves (M toe and M toe/ inhab) show the effect of the Country’s financial crisis that started in 1982 as well as the apparent recovery from 1994 on. The drop in use per capita shows a small elevation when compared to the GNP drop, which reflects, according to our interpretation, the way in which electricity is converted to ton equivalent oil (toe) in the National Energy Balance, as if all electricity were converted to motion force through a thermodynamic cycle. The adoption of substitution equivalent energy corrects this distortion, preventing as well the inconvenient of considering the calorific equivalent used by the International Energy Agency, which would also lead to inadequate interpretations.
Graphic 4 – Development of final energy in Residential Sector. The configuration of the energy vectors used in the Residential Sector has varied considerably in the studied period with the substitution of traditional fuels as wood and charcoal for cooking and illuminating kerosene by liquefied petroleum gas and electricity. Considering the projection methodology proposed for the present study, based on the concept of equivalent energy, the energy sources having the same efficiency are grouped in the graphic below, while electricity is still accounted for using BEN’s method.
Graphic 5 – Energy offer configuration. Natural gas, whose use is expected to grow in all consuming sectors, presents now a demand complementary to that of pipelined gas, suggesting that so far it is only substituting the latter in the existing residential distribution network (graphic below).
PROJECTIONS FOR THE RESIDENTIAL SECTOR. Total Final Energy. From 1970 until the start of the nineties, final energy demand has developed according to a logistic curve as shown in the graphics below.
The first graphic shows the average rate for three years of the demand variation and permits to foresee the maximum demand as being 45.3 Mtoe, assuming that the conditions prior to 1992 are maintained, specially the energy price. Using the estimated maximum value above, it is possible to sketch the demand logistic curve in its linear form, shown in the second graphic and to project the future demand. It should be noted that, in spite of the fact that the correlation coefficients are good, what would suggests the trend to maintain the observed development pattern, from 1994 on it is observed a demand anomalous growth resulting from the exchange rate conditions, favoring imports, and petroleum’s low price but that could also be due to the methodology used.
In what regards the projection using the logistic curve, the demand registered for 1999 would be one decade ahead, which recommends the use of another methodology for estimating the final energy demand, and this will be carried out in terms of substitution equivalent energy. SUBSTITUTION EQUIVALENT ENERGY IN THE RESIDENTIAL SECTOR. According to what was presented in the model for Calculating the Equivalent Energy Balance, the equivalent energy calculation consists essentially in expressing the quantity of a given energy source used in the sector by the quantity of a reference energy source , namely (Equivalent E.)elet-motion = FEelcetric.sector x destination factor electr.-motion x ( conversion efficiency)electric.-motion, / ( conversion efficiency of natural gas in motion energy)NG-motion. Numerically, the example would be for 1,993 : (Equivalent E.)motion = 4.230 toe (electricity) x 0,418 x 0,780 / 0,27 = 5.108 toeNG It should be noticed that electricity is accounted for by the calorific equivalent in BEN. One difficulty encountered in the application of this methodology originates from the fact that the two BEN’s edited by the MME are far apart in time, the first one was edited in 1983 while the second one, in 1993 resulting in a step variation of the destination coefficient and of the efficiency when changing from 1992 (BEN 83) to 1993 (BEN 93) which can be overcome by smoothing the distribution coefficient x efficiency product using a geometric progression which is tantamount to assuming a continuous variation along the interval. The function so obtained is called in the present work the “smoothed equivalent energy”. It is obvious that the smoothing does not affect the fundamental historical data, namely the quantity of final energy. The calculation of equivalent energy for the Residential Sector is facilitated by the small number of energy sources used, with well defined physical-chemical characteristics and by grouping the energy sources with the same efficiencies (biomass = wood and charcoal, gases = LPG, natural gas and pipelined gas) according to BEN. Furthermore, the fuels are used in this Sector only for heat liberation which permits to weight the efficiencies for process heat and direct heating using the respective distribution coefficients and therefore there is only one efficiency associated with each group of fuel. The largest calculation effort is that of equivalent energy concerning electricity which has 5 different uses (motion force, heat process, direct heating, illumination and others). Actually, the adoption of natural gas as reference, justified by the coherence of the present work, which involves other sectors with a demand larger than that of the residential one, imposes the consideration of composed conversion processes, since in the uses concerning electricity it is necessary to assume that natural gas is converted into electricity in order to be used. The scheme below illustrates the composition of efficiencies for these cases.
If
the final energy is electric, R global ,electric / R global, NG = R use / R thermal x R electric x R use = 1/R thermal x R electric n the large electricity generators, R differs from unity less than the uncertainty of the remaining yields so that R@1. Therefore, for the electricity dedicated uses the NG equivalent factor would be 1 / 0,27 = 3,7. Data used. The calculation parameters, obtained according to what was described below (grouping and efficiency weighting) are given below as the product of the destination coefficient (first factor) and the efficiency. Biomassa (both BEN's) 1,0 x 0,10 Gases Electricity Motion F. Heat Illumination Others BEN 83 0,37 x 3,7 0,25 x 1,0 0,29 x 3,7 0,08 x 3,7 0,42 x 3,7 0,26 x 1,0 0,24 x 3,7 0,08 x 3,7 RESULTS. The attached spread sheet 1 shows the input data (Final Energy) and the results (Equivalent Energy of Natural Gas) year by year from 1970 on. The following graphics show the evolution of the equivalent energy and the corresponding logistic linear curve. For comparison purposes the final energy logistic straight line is also shown. It can be noticed that the equivalent energy presents a better fitting correlation that justifies the adoption of this concept for projection purposes. The equivalent energy logistic curve was obtained through approximations by comparing the equivalent energy per inhabitant of Brazil with that of Portugal in 1996. This choice is justified by the fact that Portugal is a European country just integrated into the European Union and because, among the countries with an intermediate per capita income, it has climatic conditions similar to those of Brazilian. The comparison resulted in an estimation of 42Mtp for the maximum equivalent energy.
Graphic 6 – Equivalent and final energy logistic linear curves. Finally, in order to evaluate the effects of urbanized population and of income on the use of equivalent energy a double correlation calculation was carried out and the resulting equation is EE (Mtoe) = 0,222 Urban Pop. (million) - 0,00261 GNP (B$ 94) - 5,508 emphasizing the predominance of the urban population, compared to income, already noticed in the final energy, as the determining parameters of residential equivalent energy use. |
