Università di Pavia, Facoltà di Ingegneria SISTEMI DI TECNOLOGIE ENERGETICHE E MODELLI DI PROGRAMMAZIONE ECONOMICA G.C. Tosato – Pavia, 13 Maggio 2002

Università di Pavia, Facoltà di Ingegneria

SISTEMI DI TECNOLOGIE ENERGETICHE E MODELLI DI PROGRAMMAZIONE ECONOMICA

G.C. Tosato – <[email protected]>

Pavia, 13 Maggio 2002 - Dipartimento Ingegneria Elettrica, Aula Seminari, Piano C, - via Ferrata, 1

ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT

ARGOMENTI1. SETTORE ENERGETICO: PROBLEMATICHE

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -2. DESCRIZIONE QUANTITATIVA: ELEMENTI E

VARIABILI DEL SISTEMA, INVENTARI

3. SISTEMA: IDENTIFICAZIONE DELLE CORRELAZIONI, SPIEGAZIONE DEGLI EVENTI

4. MODELLI: RAPPRESENTAZIONE DEL SISTEMA, PROIEZIONI E VALUTAZIONI - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

5. GENERATORI DI MODELLI TECNOLOGICI

6. DOMANDE; ESEMPI: Modelli e scenari, Confronto di opzioni tecnologiche, Valutazione di politiche e misure


1 - Settore energia: domande strutturali

• Che problemi ci riserva nel suo sviluppo? Riserve sufficienti? Costi compatibili? Inquinamento? Sviluppo sostenibile o no? Equità intergenerazionale?

• Quanto siamo lontani dalla sostenibilità?• Quanto costa mitigare i cambiamenti climatici?• Che distanza fra prezzi attuali e costi sostenibili?• Quanto e come investire per cambiare rotta? ricerca?• Quale equilibrio di lungo termine tra sistema

energetico e resto del sistema economico? Tra paesi più e meno sviluppati? Equità internazionale?


2a - Nodi: tecnologie energetiche


Quale spazio per migliorare l’efficienza / il costo di

produzione? (ingegnere, tecnico)

• Settori

• Parametri di caratterizzazione

• Fonti di DB tecnologici

• Esempio: IKARUS (Germany)

• Essempio: EM (World Bank)

Settori


ENERGY TECHNOLOGIES

PRODUCTION (Supply) ENDUSE (Demand)

RESOURCES

Conversion

Transport & Distr

Mining

Transformation

Residential/Service

Industry

Transportation

Cross - sectors

5

Parametri di caratterizzazione


GENERAL TECHNICAL ECONOMIC ENVIRONMENTAL LABOUR & MAT. REF.

technology av. size currency GHG emissions materials titletechn. sector existing capacity costs solid waste - steel autordata quality construction time - investiment liquid waste - concrete editortechnical availability technical life - fixed o&m gaseous waste - … typecommercial availab. max. availability - variable o&m acustic impact - … yearprototype av. availability - fuel land use labour accesscommercialization energy input - total ex. fuel - constructionmarket share energy output - total incl. fuel - operation

- decommiss.

Esempio di caratterizzazione


CO2 g/kWh 957,4 840CO2-EQUIVALENTE g/kWh 143,2 -

COSTIMONETA $ 1994 1993

INVESTIMENTO $/KW 1800 1404FISSI ANNUI $/KW/a 45 39

VARIABILI NON FUEL $/kWh 0,003 0,003FUEL $/kWh 0,028 0,033

TOT NON FUEL $/kWh - -TOT $/kWh 0,072 -

NOTE PFBC, CC

Convenzionale a carboneRIFERIMENTO EM database (1995) Min. fur Wirtschaft, 1990LOCAZIONE generica GermaniaINPUT PRINCIPALE carbone carboneOUT PUT PRINCIPALE energia elettrica energia elettricaPOTENZA INSTALLATA MW 300 642DURATA DI UTILIZZAZIONE h/a 5000 -RENDIMENTO % 37 39,6

Data Bases


IKARUS - Germany: + LP optimization / sectoral simul.models

CO2DB - IIASA, Vienna: linked to simulation models

EM - World Bank: linked to simulation models

IPCC/TI - USA: mitigation technologies inventory

DECADES - IAEA, Vienna: elc tch + energy chains

GREENTIE - IEA, Paris: DB on technology providers

MARKAL country DBs, linked to optimisation models

other in UK, NL, USA, etc.

Esempio: IKARUS, Germania

ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT Struttura dei dati in IKARUS

Dati relativi alla tecnologia selezionata

Processo (tecnologia)

Schema di impianto

9

EM, World Bank


Data structure in EMProducts (fuels)

Processes (technologies)

Emissioni

Costs (technologies)

Composition (fuels)

Costs (fuels)

10

2b - Flussi: statistiche e bilanci energetici

Quanto costa l’energia alla nazione? Quanto inquina? (statistico, economista)

• Statistiche energetiche nazionali (enr_ita2.xls)• Statistiche energetiche (ex: IEA, ENERDATA)• Bilancio Energetico Nazionale (MAP/DGERM)• Bilanci Energetici di sintesi (ex: IEA)• Bilanci energetici di dettaglio (ex: IEA)• Matrici Input / Output (generali, energetiche)


ITALYCode série Title Source Unit 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984I - GENERAL DATApib GDP in current national money ISTAT M*10**3 67178 72994 79810 96738 122198 138632 174869 214398 253536 309834 387669 464030 545124 633436 725760pibxx GDP at constant prices, national moneyISTAT M*10**3 524825 534071 548947 586660 616932 601477 640624 662420 686482 726409 756197 760366 761991 769370 790036pibecu85 GDP at constant prices, in ECUS of 1985ISTAT M*10**3 367 373 384 410 431 420 448 463 480 508 529 531 533 538 552cpr Private consumption of households in current national moneyISTAT M*10**3 40363 44091 48611 59175 74461 87075 107799 131895 154336 189671 241358 289137 342500 396138 452431cprxx Private consumption of households at constant prices, national moneyISTAT M*10**3 305212 316032 328093 350568 363647 365486 384552 399949 412906 442414 467517 474627 480312 483621 493167cprecu85 Private consumption of households at constant prices, in ECUS of 1985ISTAT M*10**3 213 221 229 245 254 255 269 280 289 309 327 332 336 338 345pop Resident population ISTAT k 53832 54005 54381 54751 55111 55441 55718 55955 56155 56318 56416 56502 56639 56836 57005toccp Total primary energy consumption of conventional energiesMICA Ktoe 120100 124800 132000 139800 139100 133000 142400 140600 144100 149200 147030 143590 139980 139530 143490toccpcc Total primary energy consumption of conventional energies, reference climateENEA Ktoe 119799 124132 132928 138784 139867 133700 142359 142169 143240 149335 145296 143810 141097 139435 142659toccf Total final energy consumption of conventional energiesMICA Ktoe 93300 97198 102884 108019 106306 101251 107817 105458 108165 111327 107794 105790 103042 102305 104922elccf Total electricity energy consumption MICA Ktoe 8903 9238 9866 10589 11026 10817 11859 12281 12767 12855 13782 13701 13895 13833 14615petcfind Consumption of oil products of industryMICA Ktoe 21443 21001 20871 21834 21941 17652 18535 17798 16242 16971 15994 14161 12715 12326 10972gazcfind Consumption of gas of industry MICA Ktoe 4948 5485 6501 7073 7897 8338 9348 9509 9314 9325 9163 8724 7976 7721 8192chacfind Consumption of coal of industry MICA Ktoe 4100 3979 4104 4450 4776 4403 4487 4398 4520 4487 4676 5142 5411 4767 5504elecfind Consumption of electricity of industry MICA Ktoe 5315 5397 5694 6641 6899 6560 7269 7450 7596 7361 8077 7798 7611 7461 7902vapcfind Consumption of steam of industryothcfind Consumption of others of industry MICA Ktoe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0petcftra Consumption of oil products of transportMICA Ktoe 14380 15061 17291 18661 17375 18098 19249 20523 21721 23640 23633 23606 24430 24496 25543gazcftra Consumption of gas of transport MICA Ktoe 78 91 109 124 174 253 298 256 250 250 257 258 259 257 256chacftra Consumption of coal of transport MICA Ktoe 196 195 143 134 107 81 47 38 42 48 2 0 0 0 0elecftra Consumption of electricity of transportMICA Ktoe 313 317 323 325 334 362 438 448 455 465 460 443 455 462 486vapcftra Consumption of steam of transportothcftra Consumption of others of transport MICA Ktoe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0petcfret Consumption of oil products of other sectorsMICA Ktoe 18603 20860 22790 22949 21940 21615 21754 19092 20962 20679 19441 18268 17297 17140 16740gazcfret Consumption of gas of other sectors MICA Ktoe 2466 2323 2758 3615 4475 5637 6717 7094 7911 7982 8558 8799 9057 9643 10398chacfret Consumption of coal of other sectors MICA Ktoe 740 593 521 483 379 303 296 273 240 259 292 297 307 275 273elecfret Consumption of electricity of other sectorsMICA Ktoe 2802 2851 3110 3388 3542 3662 3966 4188 4505 4805 5010 5205 5552 5620 5933vapcfret Consumption of steam of other sectorsothcfret Consumption of others of other sectorsCESENKtoe 1535 1213 1086 1028 822 669 662 619 553 606 697 650 599 577 624petcfres Consumption of oil products of residentialCESENKtoe 13232 15167 16937 17272 16461 16221 16392 14174 15789 15476 14666 13760 13030 12915 12743gazcfres Consumption of gas of residential CESENKtoe 1829 2182 2467 3028 3591 4351 5057 5302 5833 5878 6255 6414 6605 7032 7582chacfres Consumption of coal of residential CESENKtoe 612 474 416 386 304 245 239 220 193 207 233 240 253 224 219elecfres Consumption of electricity of residentialCESENKtoe 1681 1849 2026 2206 2304 2372 2571 2705 2912 3101 3236 3357 3583 3622 3833vapcfres Consumption of steam of residentialothcfres Consumption of others of residential CESENKtoe 1535 1213 1086 1028 822 669 662 619 553 606 697 650 599 577 624petcfagr Consumption of oil products of agricultureMICA Ktoe 1754 1976 2014 2053 2188 2145 2127 2177 2160 2337 2188 2110 2092 2107 1939gazcfagr Consumption of gas of agriculture MICA Ktoe 2 2 2 2 3 3 5 7 12 15 14 13 10 11 12chacfagr Consumption of coal of agriculture MICA Ktoe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0elecfagr Consumption of electricity of agricultureMICA Ktoe 95 100 100 113 122 143 155 180 194 217 223 240 254 263 265vapcfagr Consumption of steam of agricultureothcfagr Consumption of others of agriculture MICA Ktoe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0petcfdvr Consumption of oil products of others CESENKtoe 3617 3717 3839 3624 3292 3249 3234 2740 3013 2865 2587 2398 2174 2118 2059gazcfdvr Consumption of gas of others CESENKtoe 116 139 289 585 882 1283 1656 1785 2066 2089 2288 2372 2442 2600 2804chacfdvr Consumption of coal of others CESENKtoe 146 119 105 97 75 58 57 53 47 51 59 56 54 51 53elecfdvr Consumption of electricity of others CESENKtoe 831 902 985 1069 1115 1147 1240 1303 1399 1488 1551 1608 1716 1735 1835vapcfdvr Consumption of steam of othersothcfdvr Consumption of others of others CESENKtoe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0petso Bunkers MICA Ktoe 7813 8516 7711 7220 6019 5766 5615 5093 5561 5093 4203 3927 4087 3233 3202petcfnen Consumption of oil products for non energy usesMICA Ktoe 5943 5677 6197 6941 6408 4759 6115 5896 5308 5780 3844 5652 4362 5443 5626gazcfnen Consumption of gas for non energy usesMICA Ktoe 1751 1713 1735 1816 1801 1683 1884 1665 1940 2162 2065 1732 1507 1483 1883chacfnen Consumption of coal for non energy usesMICA Ktoe 507 437 367 362 399 369 341 312 297 299 308 230 272 233 257dj Degree days, base 18°c EUR degree 2120 2155 1994 2209 2038 2033 2100 1919 2142 2065 2273 2062 1977 2078 2164djref Normalized heating degree days, base 18°cENEA degree 2099 2096 2066 2061 2078 2093 2084 2082 2069 2081 2082 2072 2080 2050 2022gzlun Diesel oil conversion coeff. kcal/kg 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200 10200folun Residual fuel oil conversion coeff. kcal/kg 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800 9800

MINISTERO DELL'INDUSTRIA DEL COMMERCIO E DELL'ARTIGIANATOD IR E Z IO N E G E N E R A L E D E L L E F O N T I D I E N E R G IA E D E L L E R IS O R S E M IN E R A R IE

BILANCIO

ENERGETICO

NAZIONALE

1999

ultima modifica: 15/mar/2001

ENE44A85.mdb

DB statistiche energetiche


base content of most energy data bases:•socio - economic - land use data, maps (?)

•energy balances, flows data, prices, indicators,

•balances, capacity and reserves, etc.

•energy related environment data, indicators,

by country (or region), year, fuel, sector, unit, etc

main providers (free or at some cost)• International Energy Agency, Paris

• Energy Information Administration, Washington

• EUROSTAT, Luxemburg

• ENERDATA s.a., Grenoble, France

3 - Correlazioni nel sistema

Quale fenomeno spiega la situazione attuale, in termini di flussi, tecnologie, etc.? (economista dell’energia)

• Analisi econometriche– Macro– Micro

• Analisi dei fattori– Globale– Settoriale

• Reference energy system:– Bilanci dei flussi di energia e materiali– Bilanci delle tecnologie


3a -Relazione econometrica base

• Ln(TPES(t)) =– A +– B * Ln(GDP(t)) -– C * ln (Pr(t)) +– D * t

• TPES = Consumo naz. Di energia primaria eq.• GDP = prodotto interno lordo• Pr = prezzo medio dell’energia• T = anno; B, C = elasticità; D = miglioram. tecn


3b -Analisi dei fattori: identità di Kaya


G=Pop*(Gdp/Pop)*(En/Gdp)*(Fos/En)*(CO2/Fos)

= P * W * E * F * C

G : CO2 Emissions

P : Population

W : per capita Gross Domestic Product

E : energy intensity of the GDP

F : share of fossil fuels on Total Primary Energy Supply

C : carbon intensity of fossil fuel mix

Energy Service Carbon Intensity

15

3b -Analisi dei fattori settoriale (IEA,99) ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT

G = k(wk*Ak * i (Si * Ii *

jFij))

G : CO2 Emissions

w : Weighting factor: 1990 emissions in sector k

A : Activity in Sector k

S : Structure in Sector k (sub-sector i share of sector activity)

I : Energy Intensity in sub-sector i

F : Carbon Content of fuel j used in sub-sector i

Represents Changes in: 1) supply efficiency,

2) supply fuel mix

3) end-use fuel switch

Energy Service Carbon Intensity

16

3b - Analisi dei fattori, esempio (IEA,99) ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT

17

-3%

-2%

-1%

0%

1%

2%

3%

CO2 EnergyServices

Utility End-useFuel Mix

EnergyIntensity

Av

era

ge

% c

ha

ng

e p

er

yr.

1975-19901990-19951995-20002000-2010 Baseline2000-2010 Target

21% Reduction 1990-2010 (= -5% from baseline 2010)

3c - Reference Energy System ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT

Exports

Residential

Commercial

Transport

Non-Energy

Electricity

O&Gas Proc. & Refining

Other Processing

Imports

Domestic

Sources Processing EndUse-Tech EU-Demands

Industrial

Other regions

DNE DNPNGD

NGU

STK

DNQ

S24

DHU

DHV

NGA

OHS

NGA

OBS

ORLDBN

DBO

DBP

DHP

OBS

OBI

DBU

OHG

DBS

OBN

OBMOSN

DLPOLG

STK

OHS

NG4

NG3

NAP

NG5

OLS

NG2NGS

DNS

DNR

NG2NGS

NGA

NGA

NGE

NGA

REFORLOROJTFGSL

REFASPHFO

STK

NGW

NGL

Alberta Oil & Gas

GAS

OIL

IC

IC1

ICD

ICG

ICK

ICR

ICS

ICI

ICOICFICE

SD6

SD7

SD8

SD9

SDE

SDG

SC6

SC7

SC8

SC9

SCE

SCG

N6A

N6B

N6C

N6D

ELC

NGH

N6A

N6B

N6C

N6D

COA

NGH

ICA

ICU

ICV

ICW

ICP

ICQ

ICT

ICH

ICC

IC1

ICM

ICN

ICJ

ICX

ICZ

SD0CA0

TCD

CCATHL

NGHELCCOF

NGHN6C

CA0 CA0

CM5

COR

CB1

C C 0

CM3

CM3

FOK

C M B

CM2

CM4

CA0

CM1

CMA

E LC

C S 2

E LC

C S 2

CBL

ELCNGHCS1

Cuivre(Millionsde tonne/Année)

(*n)

4 – Modelli di previsione


Modelli qualitativi / quantitativi (story lines vs. scenarios)

Caratteristiche distintive dei modelli energetici quantitativi:

- contenuto (scope) - materia: settoriale o globale;

geografico: locale, nazionale, regionale, mondiale

- approccio teorico (tipo di variabili e di equazioni)

top-down (macro) vs. bottom-up (tecnologico)

- orizzonte temporale: breve, medio, lungo

4 - Alcune categorie di modelli


Top-down, econometric

Bottom-up, engineering

Auto-regressive

Sectoral/technology

20

Sectoral Macro-economic

General equilibrium

OptimizationSimulationEnd usemodels

Short term Long term

5 – MARKAL: Diagramma di funzionamento ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT

Technological database

•Base Case Demands for energy services

•Demand Elasticities

•Oil Price

Environmental Scenario

•Cap(s)-&-Trade

•Taxes, Subsidies

•Sectors’ Measures

Economic Scenario

•Technology Investments and Market Shares

•Emission Trajectories

•Adjusted Demands for energy services

•Marginal Values of Energy Forms (Prices)

Equilibrium

MARKAL

5 – MARKAL: Variabili principali


• Mining/Import/Export (r, t, c, ts)

• Investment (r, t, p)

• Capacity (r, t, p)

• Operation (r, t, p)

• Demand Loss/Increase (r, t, dm, k)

5 – MARKAL: Equazioni principali, 1


• Demand (r, t, dm)– Production from all “related” end-use technologies +

Elastic variables End-use demand

• Commodity balance (r, t, c) prices– Production Consumption

• Process activity (r, t, p)– Operation Capacity Availability Factor

• Capacity transfer (r, t, p)– Capacity = Investments + “Residual” capacity

Demand

Price

D0

P0

P5

D

5 Elastic Variables



• Electricity sector– Time-sliced balance (r, t, ts)

• Production Consumption

– Seasonal reservoir management• Essentially lets you specify seasonal plus an annual

availability factor

– Peaking• Total ELC capacity (1+ERESERVE) Capacity needed to

meet the energy requirement

– Base load• Total night production of Base-Load-Techs

Base-load-fraction total night demand



• User defined constraints– Any of the variables can be used to define a

new constraint

• Salvage– The investment cost of “unused” technology

stock is refunded

• Objective function– NPV of (tech costs + mining/import costs -

export revenues + taxes - subsidies)

5 – MARKAL - MACRO


MARKAL MACRO

Labor

Consumption

Energy Costs

Energy

InvestmentCapital

Y

5 – Variabili MACRO


• Utility

• Consumption (t)

• Investment (t)

• Energy costs (t)

• Production (t) [Excluding energy sector]

• Capital stock (t)

• End-use demand (t, dm)

5 – Equazioni MACRO


• Utility Disc-fact Log(Consumption)

• Use– Production = Consumption + Investment +

Energy Costs

• Production– Production = f(Energy, Capital, Labor)

• Capital accumulation

6a – Scenari nazionali: energia


CONSUMI DI ENERGIA (Mtep di energia primaria eq.)

150

160

170

180

190

200

210

220

1990 1995 2000 2005 2010 2015 2020

Business as Usual

CASO BASE (leastcost)

CO2 Emission cost of10$/ton

CO2 EMISSIONCOST OF 50$ / ton



6a – Scenari nazionali: emissioni


Emissione di CO2 da fonti energetiche, MtCO2/a(bunkers e voli int. esclusi, secondo Guidelines

FCCC)BAU

base

10$

50$100$

200$

300

350

400

450

500

550

1990 1995 2000 2005 2010 2015 2020

6b - Costi complessivi di mitigazione in Italia (GDP 0.5-1.0% al 2010, tassa eq. 80-250 $/tCO2)


CO2 reduction marginal cost curve (Markal Italy, 1998)

50$/tCO2

100$/tCO2

200$/tCO2

10$/tCO2

base

10$/tCO2con P&M

50$/tCO2con P&M

100$/tCO2con P&M

200$/tCO2con P&M

-100

-80

-60

-40

-20

0

20

40

60

80

100

0 20 40 60 80 100 120

CO2 emission reductions in 2010

14 y

ears

red

uctio

n co

sts

MM

Lit

bau

6b -Opzioni di mitigazione ottimali: sintesi


Sector:CO2Mt/a

Inv.M.Eu

Subs.M.Eu

Renewable sources 11.0 11400 2900Energy transformation 14.3 8200 1300Industry 28.2 6750 800Residential and commercial 26.0 5700 -500Mobility and transport 26.0 30300 2500Agriculture and forestry 13.2 10050 7050Wastes management 21.1 130 100

TOTAL 139.8 72530 14150

6c - Politiche e misure di mitigazione: naz.


Economic Instruments: Liberalised Internal Market in electricity and gas, Carbon tax, Subsidies (-, +),

Legal instruments: Codes to improve the thermal insulation of buildings, Minimum Efficiency standards for end use devices including cars, IPPC, traffic restrictions,

Voluntary agreements: RUE in industry/municipalities, Energy audits in industry, services, buildings, Phase out of the less efficient end use devices, ..

Diffusion of information: Monitoring mechanism, Energy Labels of end use devices,

Direct investments: Energy RD&D, procurement,…Other

6c - Potenziale dei meccanismi flessibili


Evaluation tool: Markal, an energy technology based shadow price generator

The model of the Italian energy system (15000 eq.)is run first with the Indian model (+5000 equations),then with the model of USA + Canada (+60 Keq)

In the base scenarios, the total systems costs are minimised.Other scenarios: with/without the Kyoto target to 2030,Italy can/cannot purchase emission permits from India,excluding / including purchases from USA, Canada.

Project based analysis (Clean Development Mechanism)calculating the marginal system cost (strategic elements to guess which might be the price of Emission Permits)

6c - FlexMex:punto di vista del venditore


CO2 emissions in India in 1995: 760 MtCO2/y, and a strong increase is expected: +100% in 2015, +200% in 2030

If the trade of emission rights is permitted, these emissions reduce by 10% in 2010 and by 20-25% in 2020-2030

at a marginal price of 25-35 US$’96/tCO2, by investing in Gas CC power plants instead of Coal PP

(the concepts of baseline and additionality)

The extra energy system costs are about 1.7% (investments),the economic surplus of selling on the emission trade market these CO2 reduction units is double (3.6% of the total s.cost)

CDM or Trade of Emission Permits?

6c - FlexMex: punto di vista del compratore


Which part of the national commitments is worth buying?

67% at 10-12 US$’96/tCO2 (India->Italy exchange)52% at 25-35 US$’96/tCO2 (India->USA-Canada-Italy)

33% at 40-80 US$’96/tCO2 (Eu proposed ceiling)

0% at about 200 US$’96/tCO2

6 - Studi recenti


• Impact of different schemes for international flexible mechanism for mitigation (Can-US-India-It, CH-Columbia, NL-CH-SW, Nordic Eu countries)

• Environmental effects of reducing/removing energy subsidies or of adding a Carbon Tax (Italy, Australia)

• National MARKAL models contribute to identify climate change mitigation options and the evaluation of climate change policies (Can, National Communic. to FCCC of Aus, Be, Cz, It, Latvia, NL, Sw, Us)

• Effect of including in the energy system materials, full fuel cycle analysis and endogenous technology learning for mitigation strategies

6 - Modelli globali multiregionali


• US MARKAL+MERGE for other regions (DWI-Stanford)• The Global Markal Macro Trade model with Endogenous

Technology Learning (PSI-IIASA)• The SAGE Project at the US Energy Information Administration

(System to Analyse Global Energy markets) with Time Stepped Technology Learning

• The IEA Energy Technologies Perspectives Project adds technological insight to 2002 World Energy Outlook with a bottom-up multiregional global model

• Multi-regional Global TIMES (NRCanada, GERAD)• Long time horizon multiregional global model for SERF3

(Socio Economic Research on Fusion)

6 - Energia e ambiente su scala locale


Under ETSAP and ALEP (Advanced Local Energy Planning, IEA IA on Energy Conservation in Buildings and Community Systems)

District energy grids expansion, waste management, local pollution vs global mitigation (local Agenda 21), energy conservation policies in buildings, public vs private transportation, local tax/subsidies– Germany (Mannheim, – Italy (Bologna, Torino, Aosta, Basilicata,– The Netherlands (Delft, – Sweden (Jancheping, Norcheping, – Switzerland (Geneve, – China (Hong Kong, etc.

7 - Il progetto ETSAP/IEA

• Present participants:

Australia, Austria, Belgium, Canada, EU, Finland, Germany, Greece, Irland, Italy, Japan, Korea, The Netherlands, Norway, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States

• Main goals:- to develop modelling tools that represent different systems of energy

flows and technologies

- to improve the knowledge of global, regional, national and local energy and environment systems

- to contribute to the energy environment debate with quantitative and methodologically sound analyses

7 - Generatore di modelli MARKAL (1979)

(sometimes called marginal price generating model)

• fixed multi-time periods Pareto Optimal models minimising the discounted total system cost

• energy flows and technologies (energy system only)

• single region

• with price sensitive supply curves, non price sensitive demand curves expressed in final/useful energy terms

• time/Reference Energy System (RES) perfect foresight

• calculated trade-off curves among cost, energy security and emissions

• 2 versions of the code: FORTRAN and OMNI

7 - Versioni del MARKAL (1980-2002)

• MARKAL Materials, can represent tens of pollutants and in principle the whole economy

• MACRO, NLP general equilibrium version, with a single production function

• MICRO, NLP partial equilibrium version, with demand elastic to prices (own/cross)

• Stochastic to calculate optimal hedging strategies

• Elastic Demand, linearised partial equilibrium version

• Multi-regional, with endogenous trade

• Endogenous Technology Learning (MIP)

7 - Evoluzione del Software

• automatic creation of a reference energy system from the IEA energy balances (TEMPLATE spreadsheets)

• projections of the demand for energy services from common drivers and own price elasticities

• common technologies repository, with efficiencies, emissions, materials use, costs and learning of existing and new technologies

• multiple model shells (MUSS, Answer, VEDA FE)• multiple model generator programs (GAMS)• multiple LP, NLP, MIP solvers• multiple / flexible reporting tools (VEDA BE, Answer)

7 - MARKAL/TIMES oggi


• variable time periods length (TIMES) competitive partial equilibrium models maximising the discounted sum of the consumer and producer surplus

• models flow and technologies of energy systems + materials + wastes + pollutants + other sectors

• multi-grids, multi-regional with endogenous trade• price sensitive supply and demand curves (free units)• clairvoyant, or stochastic, or time-stepped• In each market technologies with the best marginal benefit / cost

ratio are chosen, including externalities• coded in GAMS

7 - Equilibrio statico


• hundreds of energy good and commodity markets are represented (from coal to passenger*km)

• the stepwise supply and demand curves of each market are calculated including independent investment, fixed, variable, fuel, environment, material costs (based upon separate variables)

• the equilibrium point in each market of the RES calculates Quantities, Prices and indicates both supply and demand marginal technologies

• the distance from competitiveness of each technology and the technology gaps for reaching the desired equilibrium points are calculated by the model

7 - Equilibrio dinamico


The reaction of the energy system to exogenous dynamic changes is represented in the model through

• starting point is the present stock of technologies and the possible future availability of well defined technologies (not upon past behaviour)

• substitution among competing and time improving processes commodities, similar to the mechanism of optimal Von Neumann multiple producers/multiple commodities I/O models (not through price dependent technical coefficients of a Leontief I/O square matrix)

• variable depreciation plans for investments

7 - Visita i siti web del gruppo …

• www.iea.org/

• www.ecn.nl/unit_bs/etsap/main.html

• www.crt.umontreal.ca/~amit/THEMODEL/

• www.ier.uni-stuttgart.de/

• www.kier.re.kr/

• www. abare.gov.au/

• www.tokai.jaeri.go.jp/

• etc.

.. o contatta i ricercatori del gruppo • Fridtjof Unander <[email protected]>, IEA desk officer• Prof. <[email protected]>• <[email protected]>• Prof. Enzo Cuomo <[email protected]>• <[email protected]>• Gary Goldstein <[email protected]>, SW coordinator• Prof Alain B. Haurie <[email protected]>• Amit Kanudia <[email protected]>• Barry Kapilow-Cohen <[email protected]'• Anna Krook <[email protected]>• Socrates Kypreos <[email protected]>• <[email protected]>

.. altri ricercatori del gruppo

• Prof. Evasio Lavagno <[email protected]>• John C. Lee <[email protected]>• Prof. Richard <[email protected]>• Prof. Alan S. Manne <[email protected]>• Ken Noble <[email protected]>• Osamu Sato <[email protected]>• Chris Schlenzig <[email protected]>• Heesung Shin <[email protected]>• Prof. Shukla <[email protected]>• Peter Taylor <[email protected]>• GianCarlo Tosato <[email protected]>, project head• Phillip Tseng <[email protected]>, chairman

TITOLO 1

• TESTO 1


Documents

Università di Pavia, Facoltà di Ingegneria SISTEMI DI TECNOLOGIE ENERGETICHE E MODELLI DI PROGRAMMAZIONE ECONOMICA G.C. Tosato – Pavia, 13 Maggio 2002