Residential and commercial sectors - COFFEE-TEA
Note: The documentation of COFFEE-TEA is 'under review' and is not yet 'published'!| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | COPPE/UFRJ (Cenergia), Brazil, http://www.cenergialab.coppe.ufrj.br/. |
| Solution concept | General equilibrium (closed economy) |
| Solution method | The COFFEE model is solved through Linear Programming (LP). The TEA model is formulated as a mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE within GAMS using the PATH solver. |
| Anticipation | |
The residential sector is the second largest consumer of electricity worldwide, with almost 30% of total final consumption (IEA, 2011a; IEA, 2011b). The energy consumption of this sector is directly related to population size. However, the social structure and welfare, and consumption behaviour, are extremely important to determine the consumption profile.
The IEA database (IEA, 2011a; IEA, 2011b) was used to estimate the energy consumption in the residential sector. The energy consumption is actually driven by the energy services required by the households. The energy service categories used were the same as in IEA (2015), which served as basic information for this estimation. They are: Space Heating, Water Heating, Cooking, Lighting, Cooling (Ambient Conditioning) and Appliances. For these services the energy service intensity was calculated relative to the total estimated dwellings as a first indicator of the energy demand estimation. It is because some adjustments were done at the same time at the lightning sector was analyzed in a more detail.
For the lightning sector, besides electricity, non-electricity-based technology participation for lighting, such as kerosene, biomass and candles were also estimated. To accomplish this Several region-specific studies and reports were used to address this topics, such as: Africa (AFR) and South Africa (SAF) (WINKLER, 2006; GELIL, 2011; SOUTH AFRICA, 2012); Middle East (MEA) (GELIL, 2011); USA (DOE, 2012); Canada (CAN) (NRC, 2012); China (CHN) (PNNL, 2012); India (IND) (ELCOMA, 2015; INDIA, 2016; LAM et al., 2016); Resto f Asia and Oceania (RAS) (LAM et al., 2016); Australia (AUS) (ISAACS et al., 2006); and Brazil (BRA) (LUCENA, 2015). Additional global information was taken from IEA (2006) and IIASA (2012).
The services sector consists on the tertiary sector of the economy, which is characterized by the production of intangible goods, mostly, rather than products. Included in this sector are commercial activities, government facilities and general services, such as hospitals, restaurants, shopping malls, museums, and companies related to transportation, telecommunication, media, banking, etc. Afterwards just as for the Residential sector, the IEA database (IEA, 2011a; IEA, 2011b) was used to estimate the energy consumption in the services sector. This energy consumption was disaggregated into energy services categories, such as the ones used in IEA (2015). The categories for the Services sector are the same for the Residential sector. Following the same procedure applied for the residential sector, the energy intensity was estimated, for every service, relative to the floor space of non-residential buildings.
Once again the lighting service was analyzed in more detail considering the following sources: IEA (2006), WINKLER (2006), GELIL (2011) INDIA (2016) and PROCEL (2009). Besides the energy services for ambient heating and cooling were evaluated and estimated considering the database available in ATALLAH et al. (2015) to estimate the average HDD and CDD for every region.