prof. paulo seleghim jr. universidade de são paulo

Energy Planning and Investments in Brazil

Prof. Paulo Seleghim Jr.

Universidade de São Paulo

LBE5010 Renewable Energies and Energy Planning

What is energy planning ?

Different perspectives, different

meanings...

“Strategies for the development

of local, regional, national and

global energy systems…”

Different perspectives, different

meanings...

Case studies:

A plan for fostering social and economical developments in

Piauí/Brazil (energy investments portfolio)

Multiobjective optimization of 1G2G sugarcane mill integrated to

an oxyfuel boiler for the production of scCO2

Energetic optimization and rationalization at the production and

distribution of water in São Carlos/ SP - Brazil

Energy planning strategies may involve:

“The evolution of energy systems is slow

(markets, technologies, regulation, etc.)

and subjected to objective as well as

subjective aspects...”

Fostering / sustainability... “yes, but not in my back yard”

Energy optimization.... “no red ribbons to cut”

Energy rationalization... “make it cheaper”

Three important questions in energy planning:

Growth of supply to meet demands…“Will there be enough

energy to sustain the quality of life for everybody ?”

Energy security... “How susceptible are the energy systems ?”

Climate changes... “The intensive and increasing

consumption of energy will trigger climate changes that

threaten our existence ?”

Growth of supply to meet

demands

Case study: A plan for the fostering of social and

economical developments in Piauí/Brazil (energy

investments portfolio)

https://www.google.com.br/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=5nC4UlTLcUV6rM&tbnid=Y9Z4ZEjlaVQ7AM:&ved=0CAUQjRw&url=https://twitter.com/CComPI&ei=lXW4UbTxIJC09gT_6IDgBw&bvm=bv.47810305,d.dmg&psig=AFQjCNETFaJE8MkltoJgaYKEBrvjOOYJXw&ust=1371129607801780

Energy and quality of life...

Aspects:

Indicators:

Dimension index:

life expectancyat birth

expected yearsof schooling

gross national income(GNI) per capita

health/longevity knowledge/awareness standard of living

LEI =LE − 20

85 − 20EI =

MYSI − EYSI

2II =

ln GNIpc − ln(100)

ln 75000 − ln(100)

LE = life expectancy

MYSI = mean years of schooling

EYSI = expected years of schooling

GNIpc = gross national income per papita

When GNIpc = $75000 → II = 1

When GNIpc = $100 → II = 0

Brazil: GNIpc = $15140 → II = 0.76

HDI =3LEI ∙ EI ∙ II

Energy and quality of life...

Wcpt = exp(a ∙ IDH + b) − 0,6911

0,156

Correlation between HDI and the per capita energy demands

W =pop ∙ Wcpt

Parameters a and b are calibrated to compensate for

small methodological differences regarding the HDI assessment

time (years)

demand: vegetative growth + social

development cf. perspectives

energy supply

Energy demand growth projection...

planned investment

(supply/demand)

total

demand

(MW)

demand: vegetative growth only

today

development scenario no longer

possible

overinvestment


improvement cf. development scenario

energy supply

total

demand

(MW)



time (years)today

time (years)today

losses of quality of life (HDI reduction)



energy supply

total

demand

(MW)




possible

time (years)today

losses of quality of life (HDI reduction)



energy supply

total

demand

(MW)




possible

demand under

economic recession

HDI evolution in in Piauí’s municipalities

0

10

20

30

40

50

60

0 0,2 0,4 0,6 0,8 1

fre

qu

ên

cia

(%)

DHM

1990

0

10

20

30

40

50

60

0 0,2 0,4 0,6 0,8 1

fre

qu

ên

cia

(%)

DHM

2000

0

10

20

30

40

50

60

0 0,2 0,4 0,6 0,8 1

fre

qu

ên

cia

(%)

DHM

2010

Life quality improvement in terms of:

Average HDI increase

Decrease of the dispersion around HDI (less

inequalities)

Social development prospective scenarios

%Pop

%Pop

DIDHmed

%Pop

IDHmed

%Pop

IDHmed

IDHmax

%Pop

IDHmed

%Pop

IDHmed

IDHmax

IDHmax

DIDHmed

DIDHmax

IDHmed

IDHmed

DIDHmed

cenário 1 cenário 2 cenário 3

2013

2050

population

growth model

scenario 1: IDHmed , IDH = cte, IDHmax = cte

scenario 2: IDHmed , IDH , IDHmax = cte

scenario 3: IDHmed , IDH , IDHmax

scenario 0: vegetative growth without changes in the HDI


Table 1: HDI macro parameters histograms corresponding to the three

development scenarios and corresponding dispersions

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055

de

man

da

tota

l po

r e

ne

rgia

(M

W)

ano referência

scenario 3

scenario 1

scenario 2

scenario 0

Investment planning enables

a controlled supply growth

which prevents problems

related to over and

underinvestment

supply growth

beacons


0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055

de

man

da

tota

l po

r e

ne

rgia

(M

W)

ano referência

scenario 3

scenario 1

scenario 2

scenario 0

actual supply

Investment planning enables

a controlled supply growth

which prevents problems

related to over and

underinvestment


supply growth

beacons

Demanda total por energia (MW)

Litoral Meio Norte Cerrado Sertão Total Diferença

Referência: 2013 184,1 1650,2 256,3 400,5 2491,2 0

Cenário 1: 2050 412,4 (228%)(2) 3819,1 (231%)(1) 549,6 (214%) 844,3 (211%) 5625,4 (226%) 3134,2

Cenário 2: 2050 387,7 (210%) 2850,1 (172%) 561,5 (219%)(2) 900,3 (225%)(1) 4699,5 (188%) 2208,3

Cenário 3: 2050 735,9 (400%) 5410,6 (328%) 1066,0 (416%)(2)

1709,1 (427%)(1)

8921,7 (358%) 6430,5

Electricity = 16,9%

Fuel = 35,3%

Heat = 47,8%

Reference data for Piauí by administrative regions

0

200

400

600

800

1 000

1 200

1 400

1 600

1 800

2010 2015 2020 2025 2030 2035 2040 2045 2050

po

tên

cia

(MW

)

ano referência

Supply: CCEE bids

until 11/2013

✓ Electrical energy exporter

(significant potential in wind and

photovoltaics)

✓ Demand for other vectors is

higher for smaller HDIs

(transportation and industrial

activities)

✓ Vehicular fuel – production near

the consumers to avoid

aggregating logistics costs

✓ Possible wind / biorefinery

integration

Reference data for Piauí by administrative regions

Development scenarios and investments portfolios

MACRO REGIÃOTERRITÓRIO DE

DESENVOLVIMENTOCÓDIGO TD TIPO DE INVESTIMENTO DESCRIÇÃO

VALORES ESTIMADOS DE

INVESTIMENTO

LITORAL Planície Litorânea TD1

Cocais TD2

Carnaubais TD3

Entre Rios TD4

Vale do Sambito TD5 Central de geração eólica Capacidade instalada de 28MW R$ 90 000 000,00

Vale do Rio Guaribas TD6 Central de geração eólica Capacidade instalada de 28MW R$ 90 000 000,00

Vale do Rio Canindé TD7 Central de geração eólica Capacidade instalada de 28MW R$ 90 000 000,00

Serra da Capivara TD8 Central de geração eólica Capacidade instalada de 28MW R$ 90 000 000,00

Vale dos Rios Piauí e

ItaueiraTD9 Usina 1G (cana-energia)

Capacidade instalada de 50MW +

40m3/h de etanol R$ 200 000 000,00

Tabuleiros do Alto Parnaíba TD10 Usina 1G (cana-energia)Capacidade instalada de 50MW +

40m3/h de etanol R$ 200 000 000,00

Chapada das Mangabeiras TD11 Usina 1G (cana-energia)Capacidade instalada de 50MW +

40m3/h de etanol R$ 200 000 000,00

TOTAL R$ 960 000 000,00

MEIO NORTE

SEMI-ÁRIDO

CERRADOS

CARTEIRA 1

scenario 1: IDHmed , IDH = cte, IDHmax = cte




INVESTIMENTO


Cocais TD2

Carnaubais TD3

Entre Rios TD4






ItaueiraTD9 Usina 1G2G (cana-energia)


56m3/h de etanol R$ 312 000 000,00

Tabuleiros do Alto Parnaíba TD10 Usina 1G2G (cana-energia)Capacidade instalada de 40MW +

56m3/h de etanol R$ 312 000 000,00

Chapada das Mangabeiras TD11 Usina 1G2G (cana-energia)Capacidade instalada de 40MW +

56m3/h de etanol R$ 312 000 000,00

TOTAL R$ 1 296 000 000,00

MEIO NORTE

SEMI-ÁRIDO

CERRADOS

CARTEIRA 2

scenario 2: IDHmed , IDH , IDHmax = cte





INVESTIMENTO


Cocais TD2 Termoelétrica a gás natural Capacidade instalada de 500MW R$ 748 000 000,00

Carnaubais TD3

Entre Rios TD4








56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00

TOTAL R$ 2 044 000 000,00

SEMI-ÁRIDO

CERRADOS

CARTEIRA 3

MEIO NORTE

scenario 3: IDHmed , IDH , IDHmax





INVESTIMENTO


Cocais TD2 Termoelétrica a gás natural Capacidade instalada de 500MW R$ 748 000 000,00

Carnaubais TD3

Entre Rios TD4








56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00

TOTAL R$ 2 044 000 000,00

SEMI-ÁRIDO

CERRADOS

CARTEIRA 3

MEIO NORTE




INVESTIMENTO


Cocais TD2

Carnaubais TD3

Entre Rios TD4








56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00


56m3/h de etanol R$ 312 000 000,00

TOTAL R$ 1 296 000 000,00

MEIO NORTE

SEMI-ÁRIDO

CERRADOS

CARTEIRA 2




INVESTIMENTO


Cocais TD2

Carnaubais TD3

Entre Rios TD4






ItaueiraTD9 Usina 1G (cana-energia)


40m3/h de etanol R$ 200 000 000,00

Tabuleiros do Alto Parnaíba TD10 Usina 1G (cana-energia)Capacidade instalada de 50MW +

40m3/h de etanol R$ 200 000 000,00

Chapada das Mangabeiras TD11 Usina 1G (cana-energia)Capacidade instalada de 50MW +

40m3/h de etanol R$ 200 000 000,00

TOTAL R$ 960 000 000,00

MEIO NORTE

SEMI-ÁRIDO

CERRADOS

CARTEIRA 1

Energy generation investment contracts in Piauí until 01/2016

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052

potência física comissionada até o leilão de 01/2016MW


0

200

400

600

800

1000

1200

1400

1600

1800

2000

2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052

potência física comissionada até o leilão de 01/2016MW

demanda C1 p/ 2050

demanda C2 p/ 2050

demanda C3 p/ 2050


Piauí → electrical energy exporter

0

5

10

15

20

25

30

35

40

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052

potência física comissionada até o leilão de 01/2016MW GW

Brasil → depressed supply (opportunities !?)

Piauí → electrical energy exporter


Other examples/indicators...

Supply growth to meet increased demands due to

life quality improvements

Production of light vehicles by countries

Country 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

China 5,23 5,72 7,19 8,88 9,30 13,79 18,26 18,42 19,27 22,12 23,72

European Union 18,87 18,80 18,99 19,96 18,60 15,39 17,17 17,62 16,36 16,32 17,06

United States 11,99 11,95 11,26 10,78 8,67 5,71 7,74 8,66 10,34 11,07 11,66

Japan 10,51 10,80 11,48 11,60 11,58 7,93 9,63 8,40 9,94 9,63 9,77

Germany 5,57 5,76 5,82 6,21 6,05 5,21 5,91 6,15 5,65 5,72 5,91

South Korea 3,47 3,70 3,84 4,09 3,83 3,51 4,27 4,66 4,56 4,52 4,52

India 1,51 1,64 2,02 2,25 2,33 2,64 3,56 3,93 4,17 3,90 3,84

Mexico 1,58 1,68 2,05 2,10 2,17 1,56 2,34 2,68 3,00 3,05 3,37

Brazil 2,32 2,53 2,61 2,98 3,22 3,18 3,38 3,41 3,40 3,71 3,15

Spain 3,01 2,75 2,78 2,89 2,54 2,17 2,39 2,37 1,98 2,16 2,40

Canada 2,71 2,69 2,57 2,58 2,08 1,49 2,07 2,14 2,46 2,38 2,39

Russia 1,39 1,35 1,51 1,66 1,79 0,73 1,40 1,99 2,23 2,18 1,89

Thailand 0,93 1,12 1,19 1,29 1,39 1,00 1,64 1,46 2,43 2,46 1,88

France 3,67 3,55 3,17 3,02 2,57 2,05 2,23 2,24 1,97 1,74 1,82

United Kingdom 1,86 1,80 1,65 1,75 1,65 1,09 1,39 1,46 1,58 1,60 1,60

Indonesia 0,41 0,50 0,30 0,41 0,60 0,46 0,70 0,84 1,05 1,21 1,30

Total 75,02 76,35 78,43 82,43 78,37 67,92 84,10 86,42 90,41 93,77 96,28

milhões de veículos

International Organization of Motor Vehicle Manufacturers(OICA). "2014 Production Statistics". OICA. Retrieved 2015-04-25.

Country 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

China 5,23 5,72 7,19 8,88 9,30 13,79 18,26 18,42 19,27 22,12 23,72

European Union 18,87 18,80 18,99 19,96 18,60 15,39 17,17 17,62 16,36 16,32 17,06

United States 11,99 11,95 11,26 10,78 8,67 5,71 7,74 8,66 10,34 11,07 11,66

Japan 10,51 10,80 11,48 11,60 11,58 7,93 9,63 8,40 9,94 9,63 9,77

Germany 5,57 5,76 5,82 6,21 6,05 5,21 5,91 6,15 5,65 5,72 5,91

South Korea 3,47 3,70 3,84 4,09 3,83 3,51 4,27 4,66 4,56 4,52 4,52

India 1,51 1,64 2,02 2,25 2,33 2,64 3,56 3,93 4,17 3,90 3,84

Mexico 1,58 1,68 2,05 2,10 2,17 1,56 2,34 2,68 3,00 3,05 3,37

Brazil 2,32 2,53 2,61 2,98 3,22 3,18 3,38 3,41 3,40 3,71 3,15

Spain 3,01 2,75 2,78 2,89 2,54 2,17 2,39 2,37 1,98 2,16 2,40

Canada 2,71 2,69 2,57 2,58 2,08 1,49 2,07 2,14 2,46 2,38 2,39

Russia 1,39 1,35 1,51 1,66 1,79 0,73 1,40 1,99 2,23 2,18 1,89

Thailand 0,93 1,12 1,19 1,29 1,39 1,00 1,64 1,46 2,43 2,46 1,88

France 3,67 3,55 3,17 3,02 2,57 2,05 2,23 2,24 1,97 1,74 1,82

United Kingdom 1,86 1,80 1,65 1,75 1,65 1,09 1,39 1,46 1,58 1,60 1,60

Indonesia 0,41 0,50 0,30 0,41 0,60 0,46 0,70 0,84 1,05 1,21 1,30

Total 75,02 76,35 78,43 82,43 78,37 67,92 84,10 86,42 90,41 93,77 96,28

milhões de veículos

International Organization of Motor Vehicle Manufacturers(OICA). "2014 Production Statistics". OICA. Retrieved 2015-04-25.


Strong per capita

demand increase in the

developing countries...

Petroleum geopolitics !

Bottleneck: fuel supply…


Energy security...

The three dimensions of energy security

Physical integrity of facilities

Systemic fragility

Cyberterrorism

NASA Earth Observatory/NOAA NGDC

Proximately 35% of

petroleum tankers

pass through the

straight of Ormuz

The three dimensions of energy security

Physical integrity of facilities

Systemic fragility

Cyberterrorism

Energy and climate changes

CO2

energy

chemical

compounds

PETRÓLEOE GÁS

Exergy needed to reconstitute earth’s atmosphere

today 1800Wmin

DMCO2

J 10×337.2W 18min =

J/day 10×25.0E 18terra

(electricity)

days 10→

)xlnx(lnxRTw kek

x

k0min −−=

=

%.

%.

%.

%.

x

x

x

x

eCO

eAr

eO

eN

03600

93400

946020

084078

2

2

2

=

%.

%.

%.

%.

x

x

x

x

CO

Ar

O

N

03000

93410

947320

088778

2

2

2

2015 United Nations Conference on Climate Change

equivalent

equivalent

INDC = Intended Nationally Determined Contributions

2015 United Nations Conference on Climate Change

Proposed actions to reduce GHG emissions until 2030

Energy efficiency→ Industry, transportation, buildings

Coal power plants → Retrofit to CCS

Renewables → Development / deployment

Methane → landfills, coal mines, fermentation, oil and gas

Subsidies → substitution of fossil sources in vulnerable countries

“...no red ribbons to cut !!!”


Case study: Multiobjective optimization of 1G2G

sugarcane mill integrated to an oxyfuel boiler for

the production of scCO2


Energy efficiency→ Industry, transportation, buildings

“Retrofitting1G sugarcane mills into Sun Powered CCS Machine...”

Operational envelope – The Pareto frontier

scCO2exergy content

surplusexergy

1E

EEE

biomassa

excedsc2COoltane ++

exergy efficiency

maximum ethanol

production

simultaneous maximum production of ethanol, scCO2 and electricity

maximum scCO2

production

maximum electricity

production

ethanol exergycontent

maximum ethanol production

I’m so

smart !!!


scCO2exergy content

surplusexergy

maximum scCO2 production

maximum electricity

production

1E

EEE

biomassa

excedsc2COoltane ++

exergy efficiency


physical limit (1st law) to the simultaneous production of ethanol, scCO2 and electricity

Control problem: given the nominal operating conditions (ambient temperature, biomass composition, etc.) what is the best configuration of the control variables (combustion temperature, products mix,

et.) that increases the probability of operating near the Pareto frontier (multiobjective optimum) ?


scCO2exergy content

surplusexergy


Monte Carlo simulations...

process variables stochastic nature production

variables

control/decision parameters

deterministic nature

ethanol

scCO2

electricity

bagasse/straw mix for burning

fiber content

water content

sucrose content

ash content

cellulose content

hemicelluloses content

lignin content

cellulose yield

hemicelluloses yield

lignin yield

cellulose to glucose eff.

glucose to ethanol eff.

hemicellulose to xylose eff.

xylose to ethanol eff.


x

y

c


x

y

c

)c|x(fy

=


]x[px

]y[py

]c[pc

)p|p(fp cxy =


)p|p(fp cxy =

lignina

pdf

teor fibras

pdf

eletricidade

pdf

etanol

pdf

umidade

pdf

CO2sc

pdf

bagaço

pdf

palha

pdf


Application: oxyfuel thermal power plant

Restrictions

1) m = 10kg/s

2) Tcond = 100ºC

3) Pmax 150bar

4) Pint 70bar

5) Tcomb 700ºC

6) xf 0,9

Optimization ()

1) Potência nas turbinas

2) CAPEX + OPEX

)QQ(KTKPK)AA(KC debcQcombTcPdebcA +++++=

temperatura

entropia

Tcomb

Tcond

a

b

c

e

d

f

Pmax Pint

Abc

Ade

P @ Tsat = Tcond

abefcd WWWW −+=

scale (capex) fuel (opex)materials (capex)

liqW

(%)C/Cmax

Wmax → Cmax

Wmin → Cmin

Fronteira de Pareto:Família dos Melhores Projetos

Bioinspired heuristics: swarming ants method

liqW

(%)C/Cmax Wliq = 130 MW

Pmax

bar

Pint

bar

Abc

m2

Ade

m2

Tcomb

oC

111,23 80,66 1498,87 646,57 675,24

Goal: fixed capacity and maximum income generation

Qbc

MW

Qde

MW

324,69 25,08


liqW

(%)C/Cmax

capital disponível

capacidade de geração de receita

custo/benefício

138,37 72,33 1216,16 629,16 699,11

Pmax

bar

Pint

bar

Abc

m2

Ade

m2

Tcomb

oC

Goal: cost/benefits and fixed performance intervals


Operational optimization and

rationalization

fiber content

water content

sucrose content

ash content

cellulose content


lignin content

cellulose yield


lignin yield





Operational optimization and rationalization

ethanol

scCO2

electricity


fiber content

water content

sucrose content

ash content

cellulose content


lignin content

cellulose yield


lignin yield





external feedstock(cost optimization)

internal processes(process optimization)

decision variables(operational control)

revenues(market)

ethanol

scCO2

electricity


Operational optimization and rationalization

Energy rationalization...

Case study: optimization and

rationalization of the production and

distribution of water in São Carlos/ SP -

Brazil

Energy planning strategies may involve:

Fostering / sustainability... “yes, but not in my back yard”

Energy optimization.... “no red ribbons to cut”

Energy rationalization... “make it cheaper”

Hourly variation of urban demands...

Av. 23 de Maio / Obelisco aos Heróis de 32

Circulation of vehicles

Electrical energy supply

Circulation of data (telephones, etc.)

Water distribution Etc.

Herd behavior

Planning is necessary to optimize the infrastructure

capacity (capex) regarding the variability of the

instantaneous demand !

Hourly variation of urban demands...

Naypyidaw - Myanmar (Burma)

MW/$RMWh/$RTDdemandaTCconsumoC +=

Electrical energy tariff:

supply infrastructure scale

consumed volume+

use of the distribution grid

Obs.: in residential supply

contracts there are no

demand tariffs in Brazil

The energy planning problem: best supply contract considering...

1) typical water use hourly variations

2) typical energy demand hourly variation

3) water storage capacity

4) energy storage capacity

demand

contracteddemand

24000000 0300 0600 0900 1200 1500 1800 2100

consumption increase

in the peak period

water/energy

reservoir

water/energyreservoir





tariff

demand

contracteddemand

24000000 0300 0600 0900 1200 1500 1800 2100

consumption increase

in the peak period

water/energy

reservoir






bettertariff

How to control reservoirs and pumps during the day

assuring water supply and, simultaneously,

complying with the requirements of the energy

contract with hour-seasonal differentiation ?

Portaria N Portaria No33, de 11 de fevereiro de 1988

1) Adapta critérios vigentes às tarifas horo-sazonais;

Portaria N Portaria No1569, de 23 de dezembro de 1993

1) Muda o limite do FP de 0,85 para 0,92;

2) A verificação da energia reativa pode ser feita: de hora em

hora (indutiva e capacitiva) ou valor médio mensal (indutiva)

3) Pode ser avaliado o fator de potência capacitivo no período

das 0 h às 6h; (Mais recentemente, algumas concessionárias

que adotam a medição horária, mudaram esse período para:

0:30 h às 6:30 h)

4) O antigo ajuste é desmembrado em faturamento de

demanda e consumo;

Resolução ANEEL no 456, de 29 de novembro de 2000

1) Estabelece as condições de fornecimento e tarifação de

energia elétrica.

Legislation – tariff structure

Tariff modalities

Convencional Tariff

Hour-seasonal Tariff (THS):

Green Tariff

Blue Tariff

Tariff components

Consumption and use of the distribution grid

Power demand [kW]

1) Single tariff

2) Intra hour-seasonal period tariff (P)

3) Out of hour-seasonal period tariff (FP)

Energy comsumption [kWh]

1) Intra hour-seasonal period tariff / “wet” period

2) Out of hour-seasonal period tariff / “wet” period

3) Intra hour-seasonal period tariff / “dry” period

4) Out of hour-seasonal period tariff / “dry” period


Industrial


tensão de fornecimento < 69 kV

demanda máxima > 30 kW.


Energy consumption

planning:

Reductions in contracted

demand

+Strong reduction in

energy cost...

... however, fines for

exceeding limits, etc.

Apple's Four Quadrant product grid

Product line A1

consumer professional

high end

low endProduct line B1

Product line A2

Product line B2

Application to different urban environments:

IV Mostra de Ciência e Tecnologia em Políticas Municipais

Jorge Nicolau dos SANTOS e Paulo SELEGHIM Jr.

Núcleo de Engenharia Térmica e Fluidos

Escola de Engenharia de São Carlos

Universidade de São Paulo

ENERGY OPTIMIZATION AND

RATIONALIZATION IN WATER

DISTRIBUTION URBAN NETWORKS

Bairro do Douradinho

A estação do bairro do Douradinho, situado próximo ao campus da Universidade

Federal de São Carlos. Trata-se de um bairro criado recentemente cuja rede de

abastecimento ainda está isolada da rede da cidade. É constituída por um poço

de cerca de 300m de profundidade, dotado de uma bomba submersa de 100 HP,

modelo Ebara – BHS 813-8, e de um reservatório elevado com nível mínimo de 15

mca e volume total de cerca de 600 m3.

Bairro do Santa Felícia

A estação de produção e armazenamento do bairro do Santa Felícia em São

Carlos obtém água de um poço de 450m através de uma bomba submersa

acionada com auxílio de um motor elétrico de 500 HP. O armazenamento é feito

em três reservatórios com capacidades e elevações diferentes, denominados

doravante de elevado (capacidade 200m3 e cota mínima 8m), apoiado

(capacidade 400m3 e cota mínima 1.5m) e metálico (capacidade 2000m3 e

cota mínima 1m). O reservatório apoiado está ligado a uma caixa de passagem

de onde duas bombas de recalque de 40 HP enviam água para o reservatório

elevado, através do qual o bairro é abastecido.

data loggers


Santa Felícia

Santa Felícia

~40 mil habitantes

~2 mil habitantes

input flow rate

output flow rate

reservoir level

tempo

nívelvazão


Douradinho neighborhood

Conventional pump activation strategy:

input flow rate

output flow rate

reservoir level


Conventional pump activation strategy:

tempo

Energy consumption is not controlled: the pump is activated and

deactivated respectively when the high and low level sensors are triggered

→ conventional energy supply contract (no hour-seasonal differentiation)

nívelvazão


máximo

input flow rate

output flow rate

reservoir level


Rationalized pump activation strategy:

tempo

During the day the low level trigger is progressively increased to maximize

the probability of the reservoir being full at the beginning of the peak period

and, consequently, minimizing the probability of activating the pump

→ hour-seasonal differentiation energy supply contract


nível

mínimo

máximo

ponta12h00



input flow rate

output flow rate

reservoir level

acionamento convencional

acionamento controlado

66% reduction on energy cost



input flow rate

output flow rate

reservoir level

200 m3

Sta. Felícia

500HP

Bairro do Sta. Felícia


200 m3

400 m3

Sta. Felícia

500HP

ETA



200 m3

2000 m3

400 m3

Sta. Felícia

500HP

ETA



Contrato original tarifa verde com diferenciação horosazonal → operador 24/24200 m3

2000 m3

400 m3

Sta. Felícia

ETA500HP



The elevated reservoir attains its minimum

level during peak periods

→ the pump is activated to avoid shortages, despite the fact that there is

water available in the other reservoirs !

Contrato original tarifa verde com diferenciação horosazonal → operador 24/24



200 m3

2000 m3

400 m3

Sta. Felícia

ETA500HP

7.8%

Original contract: green tariff with hour-seasonal differentiation → 24/24 operator

Application to different urban environments:Bairro do Sta. Felícia

200 m3

2000 m3

400 m3

Sta. Felícia

ETA500HP

... DC = +23.5%with frequent complaints of

water shortages


Application to different urban environments:Bairro do Sta. Felícia

200 m3

2000 m3

400 m3

Sta. Felícia

ETA500HP

200 m3

2000 m3

400 m3 Sta. Felícia

nível

NM100NM50

NM0

NE100NE50NE0

Novo layout da estação:baixo custo




200 m3

2000 m3

400 m3

Sta. Felícia

ETA500HP

OPERAÇÃO DAS BOMBAS DE RECALQUE

se BR = 0 e HORA = noite e Nelev < NE0 → BR = 1se BR = 1 e HORA = noite e Nelev NE100 → BR = 0se BR = 0 e HORA = dia e Nelev < NE50 → BR = 1se BR = 1 e HORA = dia e Nelev NE100 → BR = 0se BR = 0 e HORA = ponta e Nelev < NE0 → BR = 1se BR = 1 e HORA = ponta e Nelev NE50 → BR = 0

OPERAÇÃO DA BOMBA DO POÇO

se BP = 0 e (HORA = noite ou dia) e Nmet < NM0 → BP = 1se BP = 1 e (HORA = noite ou dia) e Nmet NM100 → BP = 0se BP = 1 e HORA = ponta → BM = 0

CONDIÇÃO DE ALARME

se HORA = ponta e Nelev < NE0 e Nmet < NM0 → ALARME = 1

DC → 0


“Strategies for the

development of energy

systems…”

Strategies: involve basic scientific knowledge (“hard

sciences”) and technology (engineering), in addition to

economic and social analysis techniques…

Daniel Yergin

Renewable Energies and Energy Planning:

→ “ENERGY ERUDITION”

Renewable Energies and Energy Planning:

“Strategies for the

development of energy

systems…”

Strategies: involve basic scientific knowledge (“hard

sciences”) and technology (engineering), in addition to

economic and social analysis techniques…

Daniel Yergin

science and

technology

economicsplanning and

regulation

Areas

involved in this

course

“... to analyze and equate the problems associated to the transition of the energy grid transition,

from a few non renewable sources to a great number of renewable sources…

…. CREATIVE DESTRUCTION !”

Prof. Paulo Seleghim Jr.

[email protected]


OBRIGADOProf. Paulo Seleghim Jr.

[email protected]


Pareto Frontier

eeth

escCO2

W

Pareto Frontier

eeth

escCO2

W

Spsb

Sopt

prof. paulo seleghim jr. universidade de são paulo

Documents