Saving money by Ana S.

SAVING MONEY

By Ana Sophie Sánchez Wurm and Ana Baraibar Jiménez

THOUSAND FLOORPLANS WINTER TERM 2016/17 DIGITAL DESIGN UNIT PROF. Oliver Tessmann Anton Savov Roger Winkler Felix Dannecker

SAVING MONEY

There is a lot of factors that affect people when looking for a new home. Distribution, orientation, and personal preferences are some of the most important ones. But what about money? Most people have to work with a limited budget when buying a new house, and the electricity, water and heat bills will be a fundamental part in the expenses of the family from the moment they start living in the house. That is the reason why we focused our effort in making a tool that allows users to calculate how big some of the bills will be while living in a chosen house, particularly the electricity ones, based in their living style. Our app also shows users how that house can help them reduce this costs using solar panels to provide their own solar energy and saving money. Each house has its own â&#x20AC;&#x17E;savingâ&#x20AC;&#x153; rate, and the app sorts them to make easier for the user the choosing of their dream house. 4

SURVEY The first step of the project was making a survey in order to find which parameters concern users more when looking for a new house.

During this two weeks, a total of 27 persons had filled our survey. Most of them were in the group of age between 18 and 24 years old, but we also have significant answers from other age-sectors. The only age sector from which we have no information is between 0 and 17 years old, but we donâ&#x20AC;&#x2122;t consider it to be a relevant sector, because there is no potential house buyers on it.

We adapted the given survey to digital media to simplify the process. Both the English and German versions were used, and we also decided to translate it to Spanish to reach more people. The survey was shared in different social media. That way we ensured that it reached as much users as possible, giving them the privacy of the anonymity.

The most popular parameters are the ones related to views, followed by the energy and water, that focus mostly in the efficient management of both of them. The less relevant parameter is spatial organization. There was not many suggestions for new parameters, but we would like to mention the acoustic insulation from inside and outside noises.

Views Energy Orientation Costs

3.70 %

22.2%

14.8 %

11.11 %

Daylight Water

14.8%

37.0 % 51.8 %

Other

29.63 % 62.96 %

66.7 %

29.6 % 7.41 %

Age

Live-in family 18 - 24 25 - 34 35 - Pension Pension

Alone With Partner With Children With Parents Other

Home ownership House-owner Rented place Intend of acquiring a house in the future

Most of the participants were young people looking for their first house and adults who are already owners. This sectors of age are determinants in the results, as we have noticed that both choose similar parameters, even if their motivations to do so are different. 6

RESULTS Fifth sorting criteria

First sorting criteria

Views

Daylight

Orientation Costs

Amount of sky (18.52 %) Greenery (14.81 %) Neighbourhood houses (3.71 %) Horizon (3,71 %) Outside watching (7.41 %) On the whole house (29.63 %) Living rooom (3.7 %) Time most sunlight master bedroom (29.63 %) Time most sunlight livingroom (3.70) % South position and living room (7,41 %) Cost of the building shell (11,11 %)

Views Energy

Daylight

Orientation Water

Second sorting criteria Views (51.85 %) Energy (22.22 %) Daylight (7.41 %) Orientation (11.11 %) Water (3.71 %) Other (3.71 %)

Third sorting criteria Views (22.22 %) Energy (18.52 %) Daylight (40.74 %) Orientation (7.41 %) Water (3.71 %) Costs (11.11 %) Other (11.11 %)

Fourth sorting criteria Views (14.81 %) Energy (14.81%) Daylight (44.43%) Orientation (14.81%) Water (11.11 %) Costs (7.4 %) Other (3.7 %)

The first parameters chosen where mostly related to daylight and views. This two groups of parameters are the most atractive in the first instance, probably because they have a direct impact in how the user perceives a home. 8

Greenery (3.71 %) Neighbourhood houses (3.71 %) Horizon (3.71 %) Someone seeing from the outside (11.11%) Total amount of energy used (3.71 %) Amount of heat lost (3.71 %) On the whole house (3.71 %) Living rooom (3.7 %) Time most sunlight master bedroom (3.71 %) Time most sunlight livingroom (3.70) % Time most sunlight master bedroom (3.71 %) South direction Living rooom (3.7 %) South direction kitchen (3.70 %) Colected rain water (3.71 %) Recycling or reusing water (11.11 %) Average use (3.71%)

Costs (14.81 %) Other (3.7 %)

Time of construction (3.7 %) Amount of land left available (7.41%)

Sixth sorting criteria Views (14.81 %) Energy (14.81 %) Daylight (7.41 %) Orientation (11.11 %) Water (11.11 %) Costs (25.93 %) Other (18.52 %)

Seventh sorting criteria Energy

Total amount of energy used (7.41 %) Amount of heat lost (11.11 %) Amount of energy saved(3.71 %)

Daylight

On the whole house (3.71 %) Living room (3.7 %) Time most sunlight master bedroom (3.71 %) Time most sunlight livingroom (3.70) %

Orientation

South direction Living rooom (3.7 %)

Water

Colected rain water (3.71 %) Recycling or reusing water (7.41 %) Average use (7.41%)

Costs Other

Building the shell (7.41 %) Materials such as windows, plastering (3.71%) Time of construction (3.7 %) Amount of land left available (7.41%) Amount of floors, split-levels (11.11%)

In the second part of the survey we see a change of preferences. People tend to choose parameters related to saving resources and money. This is motivated by both the concern for the environment and a will to decrease the electricity and water bills. 9

PARAMETERS

Inputs

Outputs Roof area (m2)

Solar panels area (m2)

House area (m2)

Orientation

Floorplan Total energy produced (â&#x201A;Ź)

Location

Saving money

Lifestyle

House area (m2)

Consumed electric energy

Number of inhabitants

PARAMETERS Floorplants and roof surface The size of the house is an important factor that affect not only the available area to place the solar panels, but also the mount of energy consumed. The total area of the floorplan is not the only parmameter that matters when placing solar panels. In a flat roof we have less area but without a given direction we also have more freedom to place the panels. In a pitched roof the slope gives us more area but we canâ&#x20AC;&#x2DC;t choose the orientation.

Location As we can see in this graphics, the sunpath changes depending on the season and the latitude. This affects to the hours of sun that can be used to generate electricity. 340

350

340

330 320

300 290 28

80 90

270

260

100

250

110 120 9 14

220

Darmstadt

140

130

200

190

180

170

40 50 60 70

80 90

270

260

100

250

110 240

230

120

10 130 140

220

150

210

290

300

310

230

320

310

240

350

330

150

210

160

200

190

180

170

160

Madrid

Consume of energy The amount of energy consumed in a household each year depends on different factors, and the exact number is hard to calculate. To simplify the input of data, we decided that the best option was to ask the user how many people live in the household and how big the house is, and then use the estimation made by an electric company.

NUMBER OF USERS

ELECTRIC CONSUME (KWH)

TOTAL AMOUNT OF CONSUME

AVERAGE ELECTRIC CONSUME

1036,61

1050

2073,22

2100

3201,83

- 10 %

2798,84

2800

lightning loads (W/m2)

4146,44

- 20 %

3317,15

3300

LEd technology 3

less equipment 2

5183,05

- 30 %

3887,29

3900

incandescent 15

more equipment 15

CORRECTION FACTOR

EQUIPMENT loads (W/m2)

ANALYSIS ALGORITHM I Inputs

Solar Panels

OUTPUTS

Electric calculation

ANALYSIS ALGORITHM II Inputs

Ladybug & Honeybee

This two components are basic for running a simulation with HB and LB, being this the case.

Run EP & Solar Panels

These two toggles a re t he o nes that r un both of the simulations.

Location

This f ile path attaches t he c limatic i nformation from a given area, so that it changes according to the userâ&#x20AC;&#x2122;s location.

Floorplans

From t he f loorplans, t he v olume and the surface i s required, t he f irst o ne f or t he electric calculation a nd t he s econd one for the solar panels one. Therefore, we need to import the geometry of Rhinoceros, transform it into surfaces and then we can do both calculations.

Program

It i s necessary i n the case of t he e lectric calculation to specify the program, so that it t akes i nto account t he d iference between the rooms of the house.

Electric loads

The user needs to specify the lightning and equipment l oads, according to his/her lifestyle.

Inhabitants

Also, t he a mount o f house inhabitants its important f or t he calculation, c hanging the amount of electric energy consumed.

ANALYSIS ALGORITHM III Solar Panels

Solar panels surface

First, g iven t he r oof s urface a nd considering i t a flat r oof, we n eed to give a n estimation of the surface covered by solar panels. For that, we divide the roof surface into a considered domain, trying that t his new surfaces don’t overlap. Then w e transform t his surfaces w ith the “PVsurface” component, translating t his data for the next LB component.

Solar panels loses

According to the location, t he c limate, etc., the solar panels will a d ifferent amount of loses. In this case, not having an exact geographical i nformation f or t his hypothesis, w e suppose that the loses are from 11,4 %.

Running the simulation

Taking t he approximated s olar panels surface a nd t he a mount o f loses, w e can actually run the simulation. We w ant to obtain the total amount o f energy that can be produced by a general solar panel per year for the later comparision.

ANALYSIS ALGORITHM IV Electric calculation

Results We get t he r esults splitted in t wo categories: equipment l oads and lightning loads. Also, we get a ll o f the results splitted into rooms, s o we n eed t o add bot of the results for the final results.

HBZones

Having the data of t he v olume of t he house, w e have t he a rea for the electric calculation.

glazingCreator

Once w e have t he H BZones, w e take into account the area of the windows. We take the hypothesis of having smaller windows on the north and bigger on the south, so the energy waste is lower.

Electric simulation

For running t he s imulation, w e need t o indicate the location, both of the glazing and the HBzones. Also, we need to consider the period in which we calculate t he s imulation (in t his case the whole year, so w e get the same data as in the solar panels calculation).

ANALYSIS ALGORITHM V Solar panels results

In t he c ase of t he s olar panels, w e get splitted results according to the surfaces of the solar panels. We need to add them and then multiply it by t he v alue o f the production of s olar energy per kwh.

OUTPUTS

Electric calculation result s

The same case with t he e lectric calculation. The value for the electric consume i s actually b igger t han producing y our own energy, in this case the double. However, this v alue c hanges d uring the day - lower on the night time, higher in the mornings-, so we take an average value.

Final comparision

Finally, we get both of the values that are finally displayed for the user of the application.

APP CONCEPT

RESULTS

Hypothesis 1

floorplan 01

floorplan 02

floorplan 03

+ 658,84 €

+ 307,40 €

+ 699,83 €

- 1780,31 €

- 2397,70 €

- 1783,32 €

-1121,47

-2090,30

-1083,49

Results

2, 65 years old lightning load 15 W/ m2

equipment load 3 W/m2

2 bedrooms

100 m2

RESULTS

Hypothesis 2

floorplan 01

floorplan 02

floorplan 03

Results

5, family lightning load 10 W/ m2 + 658,84 €

+ 307,40 €

+ 699,83 €

- 1703,55 €

- 2277,07 €

- 1746,43 €

equipment load 6 W/m2

3 bedrooms

200 m2

-1044,71 30

-1969,67

-1046,60 31

BIBLIOGRAPHY http://www.electrocalculator.com/avanzado.php h t t p :// w w w. co m p a r a t a r i f a s e n e r g i a . e s/co m p a r a r- p r e cios-de-energia/consumo-medio http://www.comparatarifasenergia.es/upload/File/consumo%20 medio%20energia%20hogares%20en%20Espa%C3%B1a%20 2015.pdf http://www.sunearthtools.com/dp/tools/pos_sun.php?lang=es https://www.ocu.org/vivienda-y-energia/gas-luz/noticias/cuanta-energia-consume-una-casa-571584 https://upcommons.upc.edu/bitstream/handle/2117/15059/ Consumo%20energ%C3%A9tico%20y%20emisiones%20asociadas%20del%20sector%20residencial%20-%20Juan%20Manuel%20Hern%C3%A1ndez%20S%C3%A1nchez.pdf https://www.xataka.com/vivephilipstv/guia-para-medir-la-eficiencia-energetica-de-tu-tv http://tarifaluzhora.es/