The study showed that energy vulnerability affects both wealthy and poor districts in the city; now, researchers are investigating the feasibility of natural gas as a complementary energy source for home.

A partial result of one of the projects of the FAPESP Shell Research Center for Gas Innovation (RCGI), the recently released, brand-new Energy Vulnerability Map of Residential Areas of the City of São Paulo, could be an important tool for the city’s power supply planning, as well as such sectors as the real estate market, for example. With the study, RCGI researchers of Project 28, coordinated by professor and geographer Luís Antonio Bittar Venturi, created a matrix where five indicators come together to arrive at a scale of four types of vulnerability: very high, high, medium, and low. The objective of the study is to diagnose, rate, and map the areas of the city that are most prone to power outages.

“We reviewed the literature, in order to identify and select the indicators, and chose five for the vulnerability map: the size of the area supplied by a single substation; the existence of an alternative or complementary energy source; the distance of the district from the power arteries; its proximity to areas considered to be priorities for power supply, like hospitals; and the density of trees along the local arteries, since electricity is distributed in residential areas predominantly by aerial means and, therefore, vulnerable to falling trees.” 

Each one of these indicators was weighted according to the Analytic Hierarchy Process (AHP) proposed by Thomas Saaty (1980). This set of indictors generated a matrix, upon which the four types of vulnerability were defined.

The white areas are those that are not residential or that do not have at least a 60% residential occupation. The types were validated by the ANEEL table that indicates the duration and frequency of electrical power outages, by region.

Trends – At first glance, it is possible to identify a trend of increasing vulnerability, moving from downtown to the expanded downtown area, and from there to the peripheral regions. Another partial conclusion has to do with the fact that the variation in vulnerability is not directly related to the socioeconomic level of the districts, meaning that there can be areas of high or very high vulnerability in more wealthy districts (Alto de Pinheiros, no. 2, Campo Belo, no. 15, and Morumbi, no. 54) as well as in lower socioeconomic districts (São Mateus, no. 73, and Ermelino Matarazzo, no. 28).

In the case of Alto de Pinheiros, Campo Belo, and Morumbi, the reference indicator regarding the density of trees must have been more important than the others, since those areas usually have more trees. Another partial conclusion comes from observing contiguous and urbanistically similar districts, but with distinct levels of vulnerability, like Campo Limpo and Capão Redondo. The first is much less vulnerable than the second. In this case, the first indicator was most important, since Capão Redondo is located in a large power supply area that includes other municipalities, like Embu das Artes, thus its greater vulnerability.

On the other hand, the greater proximity to a number of hospitals in the region of Paulista Avenue could help explain the low vulnerability of the adjacent areas, taking in parts of Bela Vista (no. 7), Jd. Paulista (no. 45), and Vila Mariana (no. 90), besides the fact that these areas are also well-served by main arteries. “In order for this map to support the city’s energy planning, it must identify which indicators are most important in the areas studied,” says Venturi.

Replicable methodology – He points out that more important than the map is the methodology that the team shaped for the job. “The methodology can be applied to any city in the world. The researchers only need to choose the indicators that best adapt to the context under study.”

Furthermore, other indicators may be included as the team obtains more precise and georeferenced data about them, such as the pressure of the demand for energy by region, the different types of electrical network (linear, ring, reticulated, etc.), besides more complex data, like the frequency and efficiency of network maintenance and tree trimming, and even the occurrence of stolen cable, which is not uncommon in São Paulo. Each new piece of information included in the matrix can generate some type of alteration in the extension and distribution of the areas of each type of energy vulnerability, so that the map is dynamic, able to be altered immediately in the ArcGis platform, when each new piece of information is inserted or for each change in the weight of the indicators.

Venturi believes that the map is an innovative product. “In the literature, only the indicators are mentioned. The mapping done by cross-matching the indicators in matrices, with different weights, in order to define the types of vulnerability, was our methodology, created within the scope of RCGI’s Project 28.”

Equitable use – The ideal, according to Venturi, would be to know what proportion of gas and electricity are consumed in the residences, taking into consideration that the variety of sources and their equitable use would indicate less vulnerability. “Since we still do not have these data, once again we are considering that all households are supplied with electricity, primarily, and that they have at least gas for cooking.”

According to the Energy Balance of the State of São Paulo (SÃO PAULO, 2015), cooking is responsible for 27% of the energy expended in a residence. The remaining 73% care for the other uses that require electricity, as reported in the available literature. Based on this proportion between electricity and natural gas, the researchers simulated a scenario in which the households would be served by natural gas and electricity in equal proportions. A second map generated by this scenario shows a significant change for each type of energy source.

The districts where vulnerability was very high, which currently comes to 20.4% of all of the residential areas that were mapped, within the scenario of equal use proportions, in terms of electricity and natural gas, lowered to 7%. By the same token, the districts of high vulnerability lowered from 37% to 28.5%. On the other hand, districts with medium-level vulnerability increased from 31.9% to 39.4% and, finally, the districts with low vulnerability rose from 10.7 to 25.1%.  “We concluded that, generally speaking, the equal use of natural gas and electricity would lower the energy vulnerability for households in the city of São Paulo by 11%. That is, the increased use of natural gas would make residences less vulnerable, because with the complementary use of two energy sources, when one was lacking, there would be another that would supply at least half of the domestic functions that need power.”

Despite the existence of evidence that the increased use of natural gas is possible, given the presence of a good distribution infrastructure from the pre-salt exploration, as well as a national and worldwide trend to an increased use of natural gas, there are other variables, besides vulnerability, that will be included in the study yet this year. “For example: in light of this scenario of a more balanced use of electricity and natural gas, who would that affect the quality of the are in the city, since natural gas, no matter how clean its combustion is, is a hydrocarbon, while electricity comes predominantly from cleaner and more durable sources, like hydroelectric plants?” Venturi asks.

Another issue that will be addressed has to do with costs. Would the increased use of gas (natural or LPG) in residences result in a higher or lower energy bill for the end users? That needs to be studied. Yet this year, the team will also work on another variable: technical feasibility. One of the issues to be dealt with, for example, will be whether or not there are home appliances on the market that run on gas and that would allow increased consumption of this energy source.

References

GHISI, Enedir; GOSCH, Samuel; LAMBERTS, Roberto. Electricity end-uses in the residential sector of Brazil. Energy Policy, v. 35, n. 8, p. 4107–4120, 2007.

SAATY, Thomas L. (2008) Decision making with the analytic hierarchy process.  International Journal Services Sciences, Vol. 1, No. 1, 83. Available in:
http://www.colorado.edu/geography/leyk/geog_5113/readings/saaty_2008.pdf 

SÃO PAULO, Secretaria de Energia. Balanço Energético do Estado de São Paulo – 2015: ano base 2014. p. 270, 2015. Disponível em: http://ci.nii.ac.jp/naid/40020358184/