iea expert workshop the role of process integration for … · 2018-04-11 · epfl-sci-sti-fm...

EPFL-SCI-STI-FM (IPESE) APRIL 2017 1

IEA Expert Workshop The Role of Process Integration for Greenhouse Gas Mitigation in Industry“PI in Industrial Clusters and Excess Heat: Large

Industrial Clusters”Prof François Marechal

Industrial Process and Energy Systems Engineering

EPFL Valais-Wallis

Switzerland


Impact of Energy system engineering

3 EXECUTIVE SUMMARY

step change in the rate of progress and broader engagement of the full range of countries, sectors and stakeholders.

ETP scenarios present options rather than forecasts

ETP 2010 analyses and compares various scenarios. This approach does not aim to forecast what will happen, but rather to demonstrate the many opportunities to create a more secure and sustainable energy future.

The ETP 2010 Baseline scenario follows the Reference scenario to 2030 outlined in the World Energy Outlook 2009, and then extends it to 2050. It assumes governments introduce no new energy and climate policies. In contrast, the BLUE Map scenario (with several variants) is target-oriented: it sets the goal of halving global energy-related CO2 emissions by 2050 (compared to 2005 levels) and examines the least-cost means of achieving that goal through the deployment of existing and new low-carbon technologies (Figure ES.1). The BLUE scenarios also enhance energy security (e.g. by reducing dependence on fossil fuels) and bring other benefits that contribute to economic development (e.g. improved health due to lower air pollution). A quick comparison of ETP 2010 scenario results demonstrates that low-carbon technologies can deliver a dramatically different future (Table ES.1).

Figure ES.1 � Key technologies for reducing CO2 emissions under the BLUE Map scenario

2010 2015 2020 2025 2030 2035 2040 2045 2050

Gt C

O2

05

1015202530354045505560

WEO 2009 450 ppm case ETP 2010 analysis

CCS 19%Renewables 17%Nuclear 6%

Power generation efficiencyand fuel switching 5%

End-use fuel switching 15%End-use fuel and electricityefficiency 38%

Baseline emissions 57 Gt

BLUE Map emissions 14 Gt

Key point

A wide range of technologies will be necessary to reduce energy-related CO2 emissions substantially.

Energy Technology Perspective 2010, International Energy Agency , 2010


Process Integration and CO2 mitigation

• Efficient energy and resources use and reuse • Efficient energy conversion • Integration of renewable energy resources • Large Scale and Complex System integration • Sustainable processes & Environmental impact


The challenge of the industry

Production [kg/y]

Intensity [MJ/y]

Energy [MJ/y]

Revenue [CHF/y]

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IPESEIndustrial Process and

Energy Systems Engineering

• Understanding the use of energy in industrial processes

Production Process

Energy is the driving force of the processes

ProductsRaw materials

Mass balance

Waste

Pumps Mixers Compressors Screws Conveyers

ElectricityEnergy balance

Heat

Cooling Refrigeration Freezing Condensation

Heating Evaporation Drying Distillation Reaction

HeatEnergy Audits

Characterising mass and energy flows

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Chaleur

Energy efficiency of the technologies

ProduitsRaw Materials

Déchets

Pompes Agitateur Compresseurs Malaxeurs Concasseurs

Electricity

Heat

Heat

Refroidisseur Réfrigération Congélation Condensation

Chauffage Evaporation Distillation Réaction

Insulation Compare (bench mark) New technologies Optimise operation Management

Efficiency Technology analysis

EPFL-SCI-STI-FM (IPESE) June 2015 ‹#›

• Interconnectivity (mass, heat, energy) • Emissions (Equipment, Emissions) • Cost (size => cost, maintenance)

The energy technology building block & interface

- Equipment sizing model - Cost estimation

Heat transfer requirement

Heat transfer

Thermo-chemical conversion Model

Material streamsProduct streams

ElectricityHeat transfer requirement

Water streamsWater streams

Waste streamsWaste streams

ElectricityUnit parameters

Decision Variables

Life cycle emissions

Life cycle of equipment - Production - Dismantling

MaintenanceInvestment cost

LCA models

LCA models


Defining Unit Operation heat exchange interfaces

Unit i Separation

Steam

Cooling water

Electricitiy

Condensate

Alternative Unit i

Process flows

Process flows

T

Q

Cold stream

Hot stream

Black box

grey box

white box

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Chale

Heat recovery

ProductsRaw Materials

Waste


Electricity

Heat

T


T

HeatHeat exchange

Streams to be heated Streams to be cooled

Heating Evaporation Drying Distillation Reaction

Isolation Compare New technologies Optimise operation Management

Heat recovery savings : 30%


Heat exchange interface selection

• # of heat exchangers not modified vs operating cost

0 5 10 15 20 25#of streams in bbx[C]

0.6

0.8

1

1.2

1.4

1.6

1.8

Ope

ratin

g Co

st[E

uro/

y]

×106

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Heat revalorisation : accros the pinch


Waste


Electricity



HeatHeat pumps

Change the temperature Level of waste heat

InvestmentHeat

Isoler Comparer Développer Optimiser Gérer

Heat pump + MVR : savings =75%

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Energy Conversion


Waste


Investment

Heat

• Combined heat and power • Steam cycles • Organic Rankine Cycles • Heat pumps • MVR • Waste conversion (Bio CH4)

Isoler Comparer Développer Optimiser Gérer

Electricity

Cogeneration

Fuel

Heat

Convert the fuel you buy into useful energy for the process

Plant Wide Process Integration methodology

3. Heat recovery

4. Heat pumping 6. Combined heat and power

2. Process units integration 7. Heat exchanger network5. Site scale integration

1. Process energy audits

Energy audits Define the energy needs

New technologies Separation Discontinuous vs continuous

8. Profitability analysis

Optimisation optimised operating conditions Mass and heat integration

E. M. Méchaussie, S. L. Bungener, F. Maréchal, V. Eetvelde, and G. Martha, “Methodology for streams definition and graphical representation in Total Site Analysis,” presented at the 29th International Conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems (ECOS), 2016. N. Pouransari, “Towards practical solutions for energy efficiency of large-scale industrial sites,” EPFL, Switzerland, 2015. N. Pouransari, G. Bocquenet, and F. Maréchal, “Site-scale process integration and utility optimization with multi-level energy requirement definition,” Energy Convers. Manag., vol. 85, pp. 774–783, Sep. 2014. N. Pouransari and F. Maréchal, “Heat exchanger network design of large-scale industrial site with layout inspired constraints,” Comput. Chem. Eng., vol. 71, pp. 426–445, 2015. N. Pouransari and F. Maréchal, “Heat recovery networks synthesis of large-scale industrial sites: Heat load distribution problem with virtual process subsystems,” Energy Convers. Manag., vol. 89, pp. 985–1000, Jan. 2015.

0

1 0

20

30

40

50

60

LLDPE Polymer EthylAcetate Phenol EO & EG Butadiene

CO2 Savings in %

Project 1 Project 2 Project 3 Project 4 Project 5 Project 6 Remaining

CO2 mitigation results (chemical industry)

CO2 emissions 100 kt/y

15 Projects realised in collaboration with industry

Polymer 1 Polymer 2 Chemical 1 Chemical 2 Chemical 3 Chemical 4


Fuel Cell System design and PI

CO2

E

CH4

O2

Facchinetti, M, Daniel Favrat, and Francois Marechal. “Sub-atmospheric Hybrid Cycle SOFC-Gas Turbine with CO2 Separation.” PCT/IB2010/052558, 2011.

E

H2O

O2 Products :Electricity :80 %CO2 capturedH2O

Heat : 20%

Air

Facchinetti et al.: Innovative Hybrid Cycle Solid Oxide Fuel Cell-Inverted Gas Turbine with CO2 Separation

fuel cell and thus reduced fuel cell cooling requirement.Indeed, the optimal HCP fuel cell air excess decreases withthe pressure ratio (Figure 4). HCox and HCair are character-ized by a nearly constant steam to carbon ratio and fuel cellair excess.

The cathodic turbine pressure ratio remains nearly con-stant for HCox while decreases slightly for HCair withrespect to the anodic pressure ratio (Figure 5).

Figure 6 displays the relation between the pressure ratioand the anodic and cathodic compressor inlet temperatures.Anodic and cathodic compressor inlet temperatures of HCair

are minimized in order to reduce the compression work.The compressor inlet temperatures of HCox are slightlyhigher than the lower limit of the range. This is due to thelow temperature heat load required by the system energyintegration.

Corrected composite curves of optimal solutions, charac-terized by the same pressure ratio, are compared inFigures 7–9. The decision variables describing those solutionsare presented in Table 2. The corrected composite curvesrepresent the relation between corrected temperature!T±!DT min!2"" and the heat load specific to the power output.

/ -

/ -

Fig. 3 Pressure ratio vs. steam to carbon ratio with max TIT = 1,573 K.

/ -

/ -

Fig. 4 Pressure ratio vs. fuel cell air excess with max TIT = 1,573 K.

/ -

/ -

Fig. 5 Pressure ratio vs. cathodic turbine pressure ratio with maxTIT = 1,573 K.

/ K

Fig. 6 Pressure ratio vs. compressor inlet temperature with maxTIT = 1,573 K.

/ K

Fig. 7 HCox composite curves of optimal solution with p = 3 and maxTIT = 1,573 K.

Table 2 Decision variables for optimal solutions p = 3 and maxTIT = 1,573 K.

Variables HCox HCair HCP

nsc 1.35 1.30 1.65Tsr [K] 1,065 1,073 1,071Tfc [K] 1,072 1,073 1,073k 3.3 2.6 2.6l 0.8 0.8 0.8p 3 3 3pcathode 2.9 3.0 –Tic cathode [K] 299 298 –Tic anode [K] 304 298 –

ORIG

INAL

RES

EARCH

PAPER

6 © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim FUEL CELLS 00, 0000, No. 0, 1–8www.fuelcells.wiley-vch.de

SOFC

François Maréchal (IPESE-EPFL) April 2017 16

The green boiler

Production SNG

WOOD 100 MWth, dry

67.5 MW SNG

CO2

INVESTMENT 86 Million USD

16.8 MW Waste heat

(108 kg CO2 avoided / MWh wood)

1.4 MW net electricity

• Co production of biofuel from wood

• Synthetic natural gas, methanol, DME, F-T fuels

• CO2 capture

• Exothermic => Heat supply

• Cogeneration of Heat

With market price of WOOD (40$/MWh) and NG (65 $/MWh) and with CO2 taxes (80 CHF/ton), also for capture 8000 hours/year of operation

COST OF HEAT 3.2 M$/year (-6.1 M$/year) 25 $/MWh (- 47 $/MWh)


Green boiler and RES storage

Production SNG

WOOD 100 MWth, dry

67.5 MW SNG

CO2

16.8 MW Waste heat

(108 kg CO2 avoided / MWh wood)


Production SNG

WOOD 100 MWth, dry

170 MW SNG

37 MW Waste heat

Electricity 145 MWth, dry

H2 123 MWth, dry

38 MW Useful heat


CC & GCC of aluminium production process

Preheating Cooling

solidification

melting

Al Mould

High temperature pinch Combustion Air preheating Low temperature waste heat


System integration

Production SNG

ε=68.2%

WOOD 100 MWth, dry

67.5 MW SNG

CO2

INVESTMENT 86 Million USD

16.8 MW Waste heat

(108 kg CO2 avoided / MWh wood), no sequestration


Integrating renewable energy sources

Motivation ■ RENEWABLE ENERGY AND INDUSTRY ■ Developing methods for sizing solar and heat pumping systems and

corresponding storage, considering time variations, process integration and investment cost.

■ Discover and elaborate synergies and competing aspects of such technologies.

Solar heat & heat pumping integrationMethods

Data collection Optimal sizing & operation

Post Computational

analysis

➢ Heat pump superstructure

➢ investment costs estimations ➢ CO2 eq emissions

➢ min TAC TAC = OPEX + CAPEX Optimization with multi-period (MILP) inc. storage

➢ Meteorological data clustering

➢ Process data

➢ Solar components & storage

2,ngGRID GRID,in BOI BOI2,tot 2,el ref BOI

1

COCO E + Q t occ

fp p p pp

CO u u=

⎞⎛= ⋅ ⋅ ⋅ ⋅ ⋅ Δ ⋅⎟⎜

⎝ ⎠∑P

Solar only

Ref+Solar ∑=19.1 kWh/traw

3.8 m2/0.01traw

Results : multi-period evaluation

Heatpump only

Ref+HPS 24 kWh/traw

combined

2.1 m2/0.01traw

Ref+HP+Solar ∑=10.1 kWh/traw

Natural gas 8.1 ct€/kWh

Grid electricity 14.2 ct€/kWh

Results : CO2 mitigation and costs

23

Max. heat recovery ⇒ Pinch analysis ⇒Optimizing the

HEN

Heat pumping

solar + heat pumping

Photovoltaic Electricity (150€/m2) 2'245m2 ! 2.38m2/unit

Flat plate thermal Heat (300€/m2) 1'369m2 !1.45 m2/unit

Flat plate + PV Hybrid Low efficiency

HCPVT Hybrid (500€/m2) High efficiency 1'988m2! 2.10m2/unit

Daytime process operationTAC = OPEX + ann(CAPEX)

Solar only

A. S. Wallerand, R. Voillat, and F. Maréchal, “Towards optimal design of solar assisted industrial processes: Case study of a dairy,” Proc. ECOS 2016, 2016

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Industrial symbiosis

Chauffage Evaporation Distillation Réaction Products

Raw Materials

Heat

Use the heat for another purpose ?

Use the waste for another purpose ?

Waste

HeatElectricity

Cogeneration

Fuel

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• Looking at synergies …



Cogeneration

Products

Raw Materials WasteIndustrial site

Products

Heat

Heat

Sharing resources & material flows Cascading Heat Sharing Equipments Waste Management

Electricity

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Electricity


Cogeneration

Industrial site

Heat

Heat

Reforming

Synthesis

Polymers

Separation

Steel Glass

Cement

Minerals

Food

Greenhouses

Aluminium

Fine chemicals

Cracking

T Cross sectors

27

Industrial site analysis

Single Process Integration

Black-box

System A

28


Black-box Simple model

System A


29



Black-box

System B

System A


30



Black-box Detailed model

System B

System A


31

Single Processes Integration



System C

System B

System A


All Process Total hot utility bill

Current 100 % (Base)

SP Integrated 70 %

32

Single Process Integration Total Site IntegrationI. All the units represent by Black-Box analysis



System C

System B

System A


33


II. System A upgrades by Simple-Model analysis



System C

System B

System A


34

Single Process Integration Total Site Integration

III. System B upgrades by Detailed-Model analysis

I. All the units represent by Black-Box analysis



System C

System B

System A


Industrial site analysis : choosing the interfaces

35

Case study: TSI vs SPI with multi-layer data extraction, The site with A, B and C systems




System C

System B

System A

All Process P-P heat exchanger Reduction of consumption Total hot utility bill

Current 32 % - 100 % (Base)

SP Integrated 55 % 23 % 70 %

TS Integrated 62 % 30 % 63 %

III. System B upgrades by Detailed-Model analysis


36

Case study: Heat recovery improvement options with TSI

Process modification: Increasing the pressure, ΔP= 0.35 bar

TSI

All Process Hot utility requirement Heat recovery Reduction of consumption Total hot utility bill

Current 100 % 32 % - 100 % (Base)

TS Integrated 70% 62 % 30 % 63 %

62% 50%

37


Process modification: Increasing the pressure, ΔP= 0.4 bar

All Process Reduction of consumption Total hot utility bill

Current - 100 % (Base)

TS Integrated 30 % 63 %

Press.Inc Integrated 38 % 52 %

Increased Pressure

62% 50%

72% 42%

38


Advance technology: Integration of MVR and HP, two stage MVR

TSI




62% 50%

39

Case study: Heat recovery improvement options with heat pumping

Advance technology : Integration of MVR and HP, two stage MVR




MVR & HP Integrated 53 % 45 %

MVR & HP Integrated

62% 50%

99% 27%

Mechanical power= 6%

40

Case study: Energy conversion units integration & optimization

Utility options: Boiler, CHP (Gas turbine and Steam network), Refrigeration cycle

Balanced electricity production/Equivalent kJ of current natural gas consumption

TSI

Current Site TSI

Heat requirement [%] 100 70

Relative Natural Gas [-] 1.0 1.08

Relative balanced Electricity [-] 0 0.33

Relative total cost 1.0 0.78

41



Balanced electricity production/Equivalent kJ of current natural gas consumption

TSI Increased pressure

Current Site TSI TSI Press.Inc

Heat requirement [%] 100 70 62

Relative Natural Gas [-] 1.0 1.08 0.92

Relative balanced Electricity [-] 0 0.33 0.25

Relative total cost 1.0 0.78 0.72

42



Balanced electricity production/Equivalent kJ of current natural gas consumption (Gn cost/El Cost=0.8) Total incl. investment

TSI Increased pressure MVR & HP Integration

Current Site TSI TSI Press.Inc TSI Intg.MVR & HP

Heat requirement [%] 100 70 62 47

Relative Natural Gas [-] 1.0 1.08 0.92 0.60

Relative balanced Electricity [-] 0 0.33 0.25 0.09

Relative total cost 1.0 0.78 0.72 0.70

Mechanical power= 6%




Electricity


Cogeneration

Products


Products

Heat

Heat



Local heat recovery

-20

0

20

40

60

80

0 50 100 150 200 250 300 350 400

T(C

)

Q(kW)

AirWaste Water

Heating Hot water

recoveryRecoverable

Heat requirement


Buildings and efficiency

• Definition of the energy requirements

• Heating

• Air renewal

• Hot water

• Waste Water

• Air renewal

Tw Twmin

TrTs

Refurbishment up to 66%

Do not forget Carnot (Exergy demand) : * Heat with the lower possible temperature * Cool with the highest possible temperature

Heating temperature


Multi-period problem

Buildings : 35 % of the final energy demand Industry : 29 % of the final energy demand


Local Heat pumping on building waste heat

-20

0

20

40

60

80

0 50 100 150 200 250 300 350 400

T(C

)

Q(kW)

AirWaste Water

Heating Hot water

recoveryRecoverable

Heat requirement

20 kWe

Heat pumping on water supply ?

COP = Heat/Elec = 5 to 6

Heat pumping on waste water - Heat exchange - Heat storage - Water storage


Integrating the demand : the whole region

0 200 400 600 800 1000 12000

10

20

30

40

50

60

70

80

Required Thermal Power Q [MW]

Tem

pera

ture

[°C]

2030

Summer

Mid-Season Winter

-6°C Minimum power requirement for heating and hot water production (Mid-Season)

Minimum cooling power requirement

2005Scenarios:

Cooling range

4.3. Period dependent requirements using Q–T composites

The time scale is first decomposed into a limited number ofrepresentative periods (P). The definition of the periods depends onthe design problem to be solved. In the case of urban planning, thevariation of temperatures may be compensated by the uncer-tainties of the data and a multi-period analysis is made over threeperiods (winter, mid-season and summer) as shown in Fig. 6. Whena more detailed model is needed, for example for the design ofdistrict network [13], the integration of solar heat or when storagetanks have to be designed, a higher number of periods like typicaldays representation [4] should be applied. The building modelbeing defined as a function of the outdoor and room temperature,any time discretization may be applied as soon as the buildingmodel remains valid, e.g. the building structure inertia is not rele-vant. Considering the building dependent threshold temperatures,a typical mean temperature Theat

ext;P;c is associated with each building/category. This is done for each period using equation (11), andsimilarly for the cold requirement.

Theatext;P;c ¼ min

0

BBBBBB@

Z

t˛P:Text<Theattr;c

TextðtÞdt

Z

t˛P:Text<Theattr;c

dt; Theat

tr;c

1

CCCCCCA(11)

Using the heating signature (3), the hot/cold mean power ð _QjP;zÞ is

computed for each period (P) by equations (12) and (13) (seeTable 3). The sum over the different types of buildings defines therequired power of a given area. The equivalent operating time (DP)of the period for the area is defined as the energy/power ratio (14).

_QhotP;z ¼

Xnc

c¼1

!kheat

1c$Theat;ext

P;c þ kheat2cþ _qhw

c

"$Ac;z (12)

_QcoldP;z ¼

Xnc

c¼1

!kcool

1c$Tcool;ext

P;c þ kcool2c

"$Ac;z (13)

DjP ¼

QjP

_QjP

; j :¼ hot; cold (14)

Considering the list of buildings in a given area and applyingprocess integration techniques [14], it is possible to compute theheat–temperature composite curves ðð _Qk; TkÞP ; k ¼ 1;.;nk þ 1Þz,that defines in each zone the net hot/cold services to be delivered ina typical period. The heat cascade integrates the hot waterproduction, the heating and the cooling requirements of all the

intT Q

supplyT returnT

mcpextT

Fig. 4. Heat exchange of the domestic hydronic system.

20253035404550556065707580

Dis

trib

utio

n t

em

pe

ra

tu

re

s [

°C

]

-12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16Text [°C]

25.523.6

21.820.0

18.216.4

14.512.7

10.99.1 7.3 5.5 3.6 1.8 0

q [W/m2]

Supply curveReturn curve

Design points

Fig. 5. Example of heating distribution curves sized at 65/50 %C for Text, 0¼&6 %C.

Summer Mid-Season

WinterMid-Season

Te

xt [

°C

]

Fig. 6. Outdoor temperature in Geneva (2005) and periods definition.

Table 3Heat power requirements _qP;c for residential and administrative buildings.

Category Heating [W/m2] HW [W/m2] Cooling [W/m2]

Summer Mid-season

Winter Annual Summer Mid-season

Winter

Resid1 3.71 11.29 27.72 6.26 0.00 0.00 0.00Resid2 4.27 12.68 30.86 6.26 0.00 0.00 0.00Resid3 3.98 12.05 29.51 6.26 0.00 0.00 0.00Resid4 2.89 8.56 21.25 6.26 0.00 0.00 0.00Resid5 1.33 3.83 9.58 6.26 0.00 0.00 0.00Resid6 0.89 2.62 6.60 6.26 0.00 0.00 0.00Resid7 1.18 3.46 8.69 6.26 0.00 0.00 0.00Resid8 1.75 5.13 12.83 6.26 0.00 0.00 0.00Resid9 1.62 4.66 11.66 6.26 0.00 0.00 0.00Resid10 1.85 5.38 13.42 6.26 0.00 0.00 0.00Admin1 3.73 10.99 27.64 2.09 0.00 0.00 0.00Admin2 3.72 10.97 27.60 2.09 0.00 0.00 0.00Admin3 3.96 11.44 28.60 2.09 7.77 4.95 0.00Admin4 3.35 9.88 24.92 2.09 11.30 7.19 0.00Admin5 1.92 5.50 14.13 2.09 15.00 9.55 0.00Admin6 1.55 4.39 11.36 2.09 16.55 10.53 0.00Admin7 1.76 5.15 13.30 2.09 15.36 9.78 0.00Admin9 2.30 6.72 17.15 2.09 15.39 9.79 0.00Admin0 2.19 6.29 16.06 2.09 16.29 10.37 0.00Admin10 2.41 6.95 17.69 2.09 15.07 9.59 0.00

L. Girardin et al. / Energy 35 (2010) 830–840 835

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Industrial symbiosis and district heating

• Multi-period process integration problem : MILP problem inc. storage management

Electricity


Cogeneration

Products


Products

Heat District Heating

Heat


0 200 400 600 800 1000 12000

10

20

30

40

50

60

70

80

Required Thermal Power Q [MW]

Tempe

rature

[°C]

2030

Summer

Mid-Season Winter

-6°C Minimum power requirement for heating and hot water production (Mid-Season)

Minimum cooling power requirement

2005Scenarios:

Cooling range


PI for Waste management integration

Ecole Polytechnique Fédérale de Lausanne

T

40°C

15 °C

5 °C

-5 °C

Data centersAir conditionning

Hot waterHeating

RefrigerationLake CO2Liquid Gas

80°C

Waste water

CH4

CO2

Industrial waste heat

Electricity

Suciu et al. , Ecos Proceedings, 2016

NEW PARADIGME : LOW T DISTRICT SYSTEM

Electrical grid

Solar PV

Bio-waste multi-energy grids


Conclusions : PI & Large scale integration

• Do not sell your inefficiency ! • Efficiency is the hidden fuel for CO2 mitigation

• and PI reveals the system efficiency • Energy conversion

• Heat revalorisation => heat pumps

• Combined Heat and Power • Combined Fuel and Power

• Integrate renewable energy sources

• Multi-period problems • Storage

• Large system integration • District heating

• Energy management

• Take actions at the system level • Identify targets

• Evaluate paths for implementation

• Find economic evaluation

Energy section of EFCE in preparation

Chair and Co-ChairF. Marechal (EPFL, CH) & Fabrizio Bezzo (UnPd, IT)

Chair

WP representativesSections representative

Fuels

Chair


Biomass

Chair


CO2

Chair


Hydrogen

Efficiency


Chair

Conversion


Chair

WWE Nexus


Chair

Chair


Storage

CAPESep. Thermo.

Memb.

Drying

CAPE

Sep.Thermo. Memb.

Electro-chemReaction

Reaction

Sust.

Sust.

Energy in chemical engineering

Chemical engineering in Energy

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